1
Generative Adversarial Networks
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A probabilistic neighbourhood pooling-based attention network for hyperspectral image classification
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Adaptive Edge Preserving Maps in Markov Random Fields for Hyperspectral Image Classification
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Artifacts of different dimension reduction methods on hybrid CNN feature hierarchy for Hyperspectral Image Classification
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SpectralFormer: Rethinking Hyperspectral Image Classification With Transformers
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Regularized CNN Feature Hierarchy for Hyperspectral Image Classification
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Interpretable Hyperspectral Artificial Intelligence: When nonconvex modeling meets hyperspectral remote sensing
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Hyperspectral imaging-based unsupervised adulterated red chili content transformation for classification: Identification of red chili adulterants
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FCCDN: Feature Constraint Network for VHR Image Change Detection
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AngularGrad: A New Optimization Technique for Angular Convergence of Convolutional Neural Networks
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A Lightweight Convolutional Neural Network for Hyperspectral Image Classification
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Hyperspectral Imaging for Bloodstain Identification
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A New Max-Min Convolutional Network for Hyperspectral Image Classification
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A survey: Deep learning for hyperspectral image classification with few labeled samples
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Generative Adversarial Capsule Network With ConvLSTM for Hyperspectral Image Classification
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Ground truth labeling and samples selection for Hyperspectral Image Classification
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Generative Adversarial Minority Oversampling for Spectral–Spatial Hyperspectral Image Classification
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Attention-Based Adaptive Spectral–Spatial Kernel ResNet for Hyperspectral Image Classification
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Hyperspectral Imaging for Minced Meat Classification Using Nonlinear Deep Features
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Myoglobin-Based Classification of Minced Meat Using Hyperspectral Imaging
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Joint and Progressive Subspace Analysis (JPSA) With Spatial–Spectral Manifold Alignment for Semisupervised Hyperspectral Dimensionality Reduction
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Hyperspectral Imaging for Color Adulteration Detection in Red Chili
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More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification
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DARecNet-BS: Unsupervised Dual-Attention Reconstruction Network for Hyperspectral Band Selection
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Graph Convolutional Networks for Hyperspectral Image Classification
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Multiclass Non-Randomized Spectral–Spatial Active Learning for Hyperspectral Image Classification
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Feature extraction for hyperspectral image classification: a review
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Semi-supervised hyperspectral image classification algorithm based on graph embedding and discriminative spatial information
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A Fast and Compact 3-D CNN for Hyperspectral Image Classification
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Gradient Centralization: A New Optimization Technique for Deep Neural Networks
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FuSENet: fused squeeze-and-excitation network for spectral-spatial hyperspectral image classification
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An Adaptive Multiview Active Learning Approach for Spectral–Spatial Classification of Hyperspectral Images
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Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox
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Spatial-prior generalized fuzziness extreme learning machine autoencoder-based active learning for hyperspectral image classification
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Semi-supervised convolutional generative adversarial network for hyperspectral image classification
36
Transfer learning for hyperspectral image classification using convolutional neural network
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Subpixel-Pixel-Superpixel-Based Multiview Active Learning for Hyperspectral Images Classification
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Scalable recurrent neural network for hyperspectral image classification
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Hyperspectral Image Classification With Convolutional Neural Network and Active Learning
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Training- and Test-Time Data Augmentation for Hyperspectral Image Segmentation
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Lightweight Spectral–Spatial Squeeze-and- Excitation Residual Bag-of-Features Learning for Hyperspectral Classification
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Multiscale Deep Spatial Feature Extraction Using Virtual RGB Image for Hyperspectral Imagery Classification
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Semi-Supervised Hyperspectral Image Classification via Spatial-Regulated Self-Training
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Convolutional Neural Network for Remote-Sensing Scene Classification: Transfer Learning Analysis
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Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification
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Deep learning classifiers for hyperspectral imaging: A review
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Active Semi-Supervised Random Forest for Hyperspectral Image Classification
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Learning to propagate labels on graphs: An iterative multitask regression framework for semi-supervised hyperspectral dimensionality reduction
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A survey on semi-supervised learning
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Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional Network
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Spatial–Spectral Jointed Stacked Auto-Encoder-Based Deep Learning for Oil Slick Extraction from Hyperspectral Images
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diffGrad: An Optimization Method for Convolutional Neural Networks
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Hyperspectral imagery classification based on semi-supervised 3-D deep neural network and adaptive band selection
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On the Variance of the Adaptive Learning Rate and Beyond
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A Data Augmentation-Assisted Deep Learning Model for High Dimensional and Highly Imbalanced Hyperspectral Imaging Data
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A survey on Image Data Augmentation for Deep Learning
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A Review of Change Detection in Multitemporal Hyperspectral Images: Current Techniques, Applications, and Challenges
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Band Attention Convolutional Networks For Hyperspectral Image Classification
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Spectra-spatial Graph-based Deep Restricted Boltzmann Networks for Hyperspectral Image Classification
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A CNN With Multiscale Convolution and Diversified Metric for Hyperspectral Image Classification
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Fourier-Based Rotation-Invariant Feature Boosting: An Efficient Framework for Geospatial Object Detection
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Spatial Prior Fuzziness Pool-Based Interactive Classification of Hyperspectral Images
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Generative Adversarial Networks and Conditional Random Fields for Hyperspectral Image Classification
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Caps-TripleGAN: GAN-Assisted CapsNet for Hyperspectral Image Classification
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Deep Learning for Hyperspectral Image Classification: An Overview
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Hyperspectral Image Classification Using Random Occlusion Data Augmentation
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Unsupervised Spatial–Spectral Feature Learning by 3D Convolutional Autoencoder for Hyperspectral Classification
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3-D Convolution-Recurrent Networks for Spectral-Spatial Classification of Hyperspectral Images
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Hyperspectral Classification Based on Lightweight 3-D-CNN With Transfer Learning
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Unsupervised Feature-Learning for Hyperspectral Data with Autoencoders
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Feature fusion by using LBP, HOG, GIST descriptors and Canonical Correlation Analysis for face recognition
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Data Augmentation for Hyperspectral Image Classification With Deep CNN
73
Hyperspectral Data Augmentation
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Classification of Hyperspectral Images Based on Multiclass Spatial–Spectral Generative Adversarial Networks
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A State-of-the-Art Survey on Deep Learning Theory and Architectures
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Active Transfer Learning Network: A Unified Deep Joint Spectral–Spatial Feature Learning Model for Hyperspectral Image Classification
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Multi-layer Extreme Learning Machine-based Autoencoder for Hyperspectral Image Classification
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HybridSN: Exploring 3-D–2-D CNN Feature Hierarchy for Hyperspectral Image Classification
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An Overview of Restricted Boltzmann Machines
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Learning Compact and Discriminative Stacked Autoencoder for Hyperspectral Image Classification
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A Parallel Gaussian–Bernoulli Restricted Boltzmann Machine for Mining Area Classification With Hyperspectral Imagery
82
Deep Pyramidal Residual Networks for Spectral–Spatial Hyperspectral Image Classification
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Deep learning and process understanding for data-driven Earth system science
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Feature Extraction With Multiscale Covariance Maps for Hyperspectral Image Classification
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Spectral–Spatial Graph Convolutional Networks for Semisupervised Hyperspectral Image Classification
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ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features
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Semisupervised Stacked Autoencoder With Cotraining for Hyperspectral Image Classification
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Semi-supervised deep learning for hyperspectral image classification
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Recent developments and applications of hyperspectral imaging for rapid detection of mycotoxins and mycotoxigenic fungi in food products
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LiSHT: Non-Parametric Linearly Scaled Hyperbolic Tangent Activation Function for Neural Networks
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Hyperspectral image classification using k-sparse denoising autoencoder and spectral-restricted spatial characteristics
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Deep Belief Network for Spectral–Spatial Classification of Hyperspectral Remote Sensor Data
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Learnable manifold alignment (LeMA): A semi-supervised cross-modality learning framework for land cover and land use classification
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CoSpace: Common Subspace Learning From Hyperspectral-Multispectral Correspondences
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Integrating Convolutional Neural Network and Gated Recurrent Unit for Hyperspectral Image Spectral-Spatial Classification
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Local morphological pattern: A scale space shape descriptor for texture classification
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Active-Learning-Incorporated Deep Transfer Learning for Hyperspectral Image Classification
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Discrimination of Chrysanthemum Varieties Using Hyperspectral Imaging Combined with a Deep Convolutional Neural Network
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Shorten Spatial-spectral RNN with Parallel-GRU for Hyperspectral Image Classification
100
An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing
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Deep&Dense Convolutional Neural Network for Hyperspectral Image Classification
102
Hyperspectral Image Classification Based on Parameter-Optimized 3D-CNNs Combined with Transfer Learning and Virtual Samples
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Joint Alternate Small Convolution and Feature Reuse for Hyperspectral Image Classification
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Deep Transfer Learning for Hyperspectral Image Classification
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Hyperspectral image classification via a random patches network
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Hyperspectral Anomaly Detection With Multiscale Attribute and Edge-Preserving Filters
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Spectral-Spatial Classification of Hyperspectral Images: Three Tricks and a New Learning Setting
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Semi-Supervised Classification of Hyperspectral Data Based on Generative Adversarial Networks and Neighborhood Majority Voting
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Spatial Sequential Recurrent Neural Network for Hyperspectral Image Classification
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Exploring Hierarchical Convolutional Features for Hyperspectral Image Classification
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Active Learning With Convolutional Neural Networks for Hyperspectral Image Classification Using a New Bayesian Approach
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Convolutional neural network for medical hyperspectral image classification with kernel fusion
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Hyperspectral Image Classification Based on Deep Deconvolution Network With Skip Architecture
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Fast dimensionality reduction and classification of hyperspectral images with extreme learning machines
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Multi-scale hierarchical recurrent neural networks for hyperspectral image classification
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Deformable Convolutional Neural Networks for Hyperspectral Image Classification
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Hyperspectral Image Super-Resolution Based on Spatial and Spectral Correlation Fusion
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Multi-Scale Convolutional Neural Network for Remote Sensing Scene Classification
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3-D Deep Learning Approach for Remote Sensing Image Classification
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Hyperspectral Image Classification With Deep Learning Models
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Semi-Supervised Deep Learning Classification for Hyperspectral Image Based on Dual-Strategy Sample Selection
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Spectral-spatial classification of hyperspectral data with mutual information based segmented stacked autoencoder approach
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Two-Stream Deep Architecture for Hyperspectral Image Classification
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Generative Adversarial Networks for Hyperspectral Image Classification
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Classifying Wheat Hyperspectral Pixels of Healthy Heads and Fusarium Head Blight Disease Using a Deep Neural Network in the Wild Field
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Hyperspectral Classification Based on Texture Feature Enhancement and Deep Belief Networks
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Active Learning Improved by Neighborhoods and Superpixels for Hyperspectral Image Classification
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Fisher discriminant ratio based multiview active learning for the classification of remote sensing images
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Semi-Supervised Deep Learning Using Pseudo Labels for Hyperspectral Image Classification
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Diverse Region-Based CNN for Hyperspectral Image Classification
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Wavelet Pooling for Convolutional Neural Networks
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Multiview Intensity-Based Active Learning for Hyperspectral Image Classification
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Semisupervised Hyperspectral Image Classification Based on Generative Adversarial Networks
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Deep Learning for Computer Vision: A Brief Review
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Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework
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Multisource Remote Sensing Data Classification Based on Convolutional Neural Network
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Variety Identification of Single Rice Seed Using Hyperspectral Imaging Combined with Convolutional Neural Network
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Dimensionally Reduced Features for Hyperspectral Image Classification Using Deep Learning
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Classification of Hyperspectral Imagery Using a New Fully Convolutional Neural Network
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Fuzziness-based active learning framework to enhance hyperspectral image classification performance for discriminative and generative classifiers
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Pretraining for Hyperspectral Convolutional Neural Network Classification
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Hardware Accelerator Design for Machine Learning
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A new deep convolutional neural network for fast hyperspectral image classification
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Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art
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Hyperspectral Band Selection Based on Deep Convolutional Neural Network and Distance Density
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Decoupled Weight Decay Regularization
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Hyperspectral Images Classification With Gabor Filtering and Convolutional Neural Network
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Hyperspectral Image Enhancement and Mixture Deep-Learning Classification of Corneal Epithelium Injuries
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Stacked sparse autoencoder in hyperspectral data classification using spectral-spatial, higher order statistics and multifractal spectrum features
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Optimization Landscape and Expressivity of Deep CNNs
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Encoding Spectral and Spatial Context Information for Hyperspectral Image Classification
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Active multi-kernel domain adaptation for hyperspectral image classification
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Generative Adversarial Networks-Based Semi-Supervised Learning for Hyperspectral Image Classification
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Hyperspectral Image Classification Using Spectral-Spatial LSTMs
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Recursive Autoencoders-Based Unsupervised Feature Learning for Hyperspectral Image Classification
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Deep learning in remote sensing: a review
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A Hyperspectral Image Classification Framework with Spatial Pixel Pair Features
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A survey on heterogeneous transfer learning
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A Spectral-Spatial Multicriteria Active Learning Technique for Hyperspectral Image Classification
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A Batch-Mode Regularized Multimetric Active Learning Framework for Classification of Hyperspectral Images
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CNN-Based Identification of Hyperspectral Bacterial Signatures for Digital Microbiology
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Multi-scale 3D deep convolutional neural network for hyperspectral image classification
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Graph-based spatial-spectral feature learning for hyperspectral image classification
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Structured Sparse Coding-Based Hyperspectral Imagery Denoising With Intracluster Filtering
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Structure Preserving Transfer Learning for Unsupervised Hyperspectral Image Classification
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Deep Fully Convolutional Network-Based Spatial Distribution Prediction for Hyperspectral Image Classification
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Metric similarity regularizer to enhance pixel similarity performance for hyperspectral unmixing
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Multiscale Morphological Compressed Change Vector Analysis for Unsupervised Multiple Change Detection
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Application of Deep Belief Network to Land Cover Classification Using Hyperspectral Images
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Convolutional Neural Networks Based Hyperspectral Image Classification Method with Adaptive Kernels
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Unsupervised Multi-manifold Classification of Hyperspectral Remote Sensing Images with Contractive Autoencoder
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Auto-Encoder Based for High Spectral Dimensional Data Classification and Visualization
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Remote Sensing Image Classification Based on Ensemble Extreme Learning Machine With Stacked Autoencoder
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A semi-supervised convolutional neural network for hyperspectral image classification
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Hyperspectral Band Selection Using Unsupervised Non-Linear Deep Auto Encoder to Train External Classifiers
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Learning and Transferring Deep Joint Spectral–Spatial Features for Hyperspectral Classification
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Deep learning in remote sensing scene classification: a data augmentation enhanced convolutional neural network framework
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Hyperspectral Image Classification With Markov Random Fields and a Convolutional Neural Network
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Cascaded Recurrent Neural Networks for Hyperspectral Image Classification
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Superpixel-Based Multiple Local CNN for Panchromatic and Multispectral Image Classification
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Joint Hyperspectral Superresolution and Unmixing With Interactive Feedback
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Semi-supervised techniques based hyper-spectral image classification: A survey
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Learning to Diversify Deep Belief Networks for Hyperspectral Image Classification
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Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification
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Convolutional Recurrent Neural Networks forHyperspectral Data Classification
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Advanced Spectral Classifiers for Hyperspectral Images: A review
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Iterative Reweighting Heterogeneous Transfer Learning Framework for Supervised Remote Sensing Image Classification
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Hyperspectral image reconstruction by deep convolutional neural network for classification
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Remote Sensing Image Scene Classification: Benchmark and State of the Art
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Semisupervised Hyperspectral Image Classification Using Small Sample Sizes
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Hyperspectral Image Classification Using Deep Pixel-Pair Features
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Spectral-spatial classification of hyperspectral imagery using a dual-channel convolutional neural network
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Spectral-Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network
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Convolutional neural networks for hyperspectral image classification
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Spectral-Spatial Classification of Hyperspectral Imagery Based on Stacked Sparse Autoencoder and Random Forest
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Hyperspectral image analysis using deep learning — A review
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Active Deep Learning for Classification of Hyperspectral Images
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Cube-CNN-SVM: A Novel Hyperspectral Image Classification Method
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Semi-Supervised Classification with Graph Convolutional Networks
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Blind spectral unmixing based on sparse component analysis for hyperspectral remote sensing imagery
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Hyperspectral Remote Sensing Classifications: A Perspective Survey
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Active learning based autoencoder for hyperspectral imagery classification
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Fusion of hyperspectral and LiDAR data using morphological component analysis
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Object detection in VHR optical remote sensing images via learning rotation-invariant HOG feature
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Feature significance-based multibag-of-visual-words model for remote sensing image scene classification
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Scene classification using local and global features with collaborative representation fusion
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Remote Sensing Image Scene Classification Using Multi-Scale Completed Local Binary Patterns and Fisher Vectors
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Hierarchical Coding Vectors for Scene Level Land-Use Classification
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Bag-of-Visual-Words Scene Classifier With Local and Global Features for High Spatial Resolution Remote Sensing Imagery
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Dirichlet-Derived Multiple Topic Scene Classification Model for High Spatial Resolution Remote Sensing Imagery
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Anomaly Detection in Hyperspectral Images Based on Low-Rank and Sparse Representation
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Incorporating visual adjectives for image classification
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Semantic Classification of High-Resolution Remote-Sensing Images Based on Mid-level Features
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A Color-Texture-Structure Descriptor for High-Resolution Satellite Image Classification
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Sift Descriptors Modeling and Application in Texture Image Classification
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The Fisher Kernel Coding Framework for High Spatial Resolution Scene Classification
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A Deep Learning Approach to Unsupervised Ensemble Learning
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Nonlinear Multiple Kernel Learning With Multiple-Structure-Element Extended Morphological Profiles for Hyperspectral Image Classification
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Recent advances in convolutional neural networks
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Deep Residual Learning for Image Recognition
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A Comparative Study of Sampling Analysis in the Scene Classification of Optical High-Spatial Resolution Remote Sensing Imagery
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Transferring Deep Convolutional Neural Networks for the Scene Classification of High-Resolution Remote Sensing Imagery
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Learning to Diversify Patch-Based Priors for Remote Sensing Image Restoration
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Deep Learning Based Feature Selection for Remote Sensing Scene Classification
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Auto-encoder-based shared mid-level visual dictionary learning for scene classification using very high resolution remote sensing images
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Diversity priors for learning early visual features
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Deep Convolutional Neural Networks for Hyperspectral Image Classification
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Land-Use Classification With Compressive Sensing Multifeature Fusion
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Deep supervised learning for hyperspectral data classification through convolutional neural networks
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Scene Classification Based on the Multifeature Fusion Probabilistic Topic Model for High Spatial Resolution Remote Sensing Imagery
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A Comparative Study of Bag-of-Words and Bag-of-Topics Models of EO Image Patches
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Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
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Adam: A Method for Stochastic Optimization
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Striving for Simplicity: The All Convolutional Net
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Multi-class geospatial object detection and geographic image classification based on collection of part detectors
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On the Properties of Neural Machine Translation: Encoder–Decoder Approaches
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Hyperspectral Image Restoration Using Low-Rank Matrix Recovery
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Deep Learning-Based Classification of Hyperspectral Data
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Dimensionality Reduction of Hyperspectral Images Based on Robust Spatial Information Using Locally Linear Embedding
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Mapping vegetation morphology types in a dry savanna ecosystem: integrating hierarchical object-based image analysis with Random Forest
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Advances in Hyperspectral Image Classification: Earth Monitoring with Statistical Learning Methods
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Fusion of Global and Local Descriptors for Remote Sensing Image Classification
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Hyperspectral Remote Sensing Data Analysis and Future Challenges
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Advances in Spectral-Spatial Classification of Hyperspectral Images
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High-Resolution Remote-Sensing Image Classification via an Approximate Earth Mover's Distance-Based Bag-of-Features Model
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Object-based urban vegetation mapping with high-resolution aerial photography as a single data source
248
A Comparative Study on Linear Regression-Based Noise Estimation for Hyperspectral Imagery
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Automatic landslide detection from remote-sensing imagery using a scene classification method based on BoVW and pLSA
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ImageNet classification with deep convolutional neural networks
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Recent advances in hyperspectral image processing
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Real-time target detection in hyperspectral images based on spatial-spectral information extraction
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Improving neural networks by preventing co-adaptation of feature detectors
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High-resolution satellite scene classification using a sparse coding based multiple feature combination
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Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches
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Segment Optimization and Data-Driven Thresholding for Knowledge-Based Landslide Detection by Object-Based Image Analysis
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UPAL: Unbiased Pool Based Active Learning
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Contractive Auto-Encoders: Explicit Invariance During Feature Extraction
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Adaptive Markov Random Field Approach for Classification of Hyperspectral Imagery
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Parallel Hyperspectral Image and Signal Processing [Applications Corner]
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Endmember Extraction of Hyperspectral Remote Sensing Images Based on the Ant Colony Optimization (ACO) Algorithm
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Bag-of-visual-words and spatial extensions for land-use classification
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Guided Image Filtering
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Multi-manifold Clustering
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Object Classification of Aerial Images With Bag-of-Visual Words
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Why Does Unsupervised Pre-training Help Deep Learning?
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Semi-supervised hyperspectral image segmentation
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A comparative study of spatial approaches for urban mapping using hyperspectral ROSIS images over Pavia City, northern Italy
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A Survey of Semi-Supervised Learning Methods
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Comparing SIFT descriptors and gabor texture features for classification of remote sensed imagery
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Classification of Hyperspectral imagery Using SIFT for Spectral Matching
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An experimental comparison of parallel algorithms for hyperspectral analysis using heterogeneous and homogeneous networks of workstations
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Supervised Machine Learning: A Review of Classification Techniques
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Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis
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Machine learning: a review of classification and combining techniques
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A Fast Learning Algorithm for Deep Belief Nets
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Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
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Histograms of oriented gradients for human detection
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Local discriminant embedding and its variants
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Kernel-based methods for hyperspectral image classification
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Classification of hyperspectral data from urban areas based on extended morphological profiles
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Investigation of the random forest framework for classification of hyperspectral data
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Classification of hyperspectral remote sensing images with support vector machines
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Diverse ensembles for active learning
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Nonparametric weighted feature extraction for classification
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Anomaly detection from hyperspectral imagery
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Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
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Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
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A new approach for the morphological segmentation of high-resolution satellite imagery
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Object recognition from local scale-invariant features
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Imaging Spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)
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Long Short-Term Memory
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Learning long-term dependencies with gradient descent is difficult
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A Learning Algorithm for Continually Running Fully Recurrent Neural Networks
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Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position
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Textural Features for Image Classification
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Adaptive Control Processes: A Guided Tour
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Revisiting Deep Hyperspectral Feature Extraction Networks via Gradient Centralized Convolution
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Separable Attention Network in Single- and Mixed-Precision Floating Point for Land-Cover Classification of Remote Sensing Images
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Lightweight Heterogeneous Kernel Convolution for Hyperspectral Image Classification With Noisy Labels
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CyCU-Net: Cycle-Consistency Unmixing Network by Learning Cascaded Autoencoders
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Morphological Convolutional Neural Networks for Hyperspectral Image Classification
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A Novel Feature Fusion Approach for VHR Remote Sensing Image Classification
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Remote Sensing (WHISPERS)
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Rotation Equivariant Convolutional Neural Networks for Hyperspectral Image Classification
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Structure Aware Generative Adversarial Networks for Hyperspectral Image Classification
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Prediction of Microbial Spoilage and Shelf-Life of Bakery Products Through Hyperspectral Imaging
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Adaptive Spatial-Spectral Feature Learning for Hyperspectral Image Classification
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Spectral–Spatial Active Learning with Attribute Profile for Hyperspectral Image Classification
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He is currently an Assistant Professor with the Key Laboratory of Digital Earth Science, Aerospace Information Research Institute
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Cloud implementation of logistic regression for hyperspectral image classification
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ST-IRGS: A Region-Based Self-Training Algorithm Applied to Hyperspectral Image Classification and Segmentation
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Feature-Driven Active Learning for Hyperspectral Image Classification
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“Land cover classification from multi-temporal, multi-spectral remotely sensed imagery using patch-based recurrent neural networks,”
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Deep Recurrent Neural Networks for Hyperspectral Image Classification
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Superpixel-Based Active Learning and Online Feature Importance Learning for Hyperspectral Image Analysis
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Stacked Denoise Autoencoder Based Feature Extraction and Classification for Hyperspectral Images
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Batik Image Classification Using SIFT Feature Extraction, Bag of Features and Support Vector Machine
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Active Learning: A Survey
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Integrated visual vocabulary in latent Dirichlet allocation–based scene classification for IKONOS image
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Convolutional Neural Network and Convex Optimization
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A Survey of Hyperspectral Image Classification in Remote Sensing
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Hyperspectral Remote Sensing : Dimensional Reduction and End member Extraction
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Neural networks for machine learning lecture 6a overview of mini-batch gradient descent
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He is currently a Professor at the Institute of Artificial Intelligence and Data Science
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Recent Advances in Techniques for Hyperspectral Image Processing
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Active Learning Literature Survey
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This PDF file includes: Materials and Methods
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ISPRS journal of photogrammetry and remote sensing, report for the period 1996-2000
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On the momentum term in gradient descent learning algorithms
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Stochastic Gradient Learning in Neural Networks
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On the mean accuracy of statistical pattern recognizers
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Receptive fields, binocular interaction and functional architecture in the cat's visual cortex
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Linear Unmixing and Target Detection of Hyperspectral Imagery Using OSP
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A New Statistical Approach for Band Clustering and Band Selection Using K-Means Clustering
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AIK Method for Band Clustering Using Statistics of Correlation and Dispersion Matrix
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Strathprints Institutional Repository Shuhui and Ren, Jinchang (2015) Effective and Efficient Midlevel Visual Elements-oriented Land-use Classification Using Vhr Remote Sensing Images. Ieee Transactions on Geoscience and Remote Sensing, 53 (8). Pp. 4238-4249. Issn 0196-2892 Effective and Efficient M
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This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1 Hyperspectral Image Segmentation Using a New Bayesian App
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Recognition Unit, Indian Statistical Institute, Kolkata
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interest includes Hyperspectral Imaging, Remote Sensing, Machine Computer Vision, and Wearable Computing
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[ Swalpa Kumar Roy (S’15) received the bachelor’s
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engineering teachers mentoring fellowship program by INAE Fellows in 2021 and also a recipient of the Outstanding Paper Award
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international/national universities
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from University of Calcutta, Kolkata in 2021. From July 2015 to March 2016, he was a Project Linked Person with the Optical Character
