fine-grained-image-classification
Displaced People Recognition
3260 papers • 126 benchmarks • 313 datasets
Recognise displaced people from images. ( Image credit: DisplaceNet: Recognising Displaced People from Images by Exploiting Dominance Level )
(Image credit: Papersgraph)
Benchmarks
These leaderboards are used to track progress in fine-grained-image-classification
Trend
Dataset
Best Model
Actions
Human Righst Archive (HRA)
Human Righst Archive (HRA)
Libraries
iUse these libraries to find fine-grained-image-classification models and implementations
Datasets
No datasets available.
Subtasks
No subtasks available.
Most implemented papers
DisplaceNet: Recognising Displaced People from Images by Exploiting Dominance Level
Grigorios Kalliatakis, Shoaib Ehsan, Maria Fasli, K. Mcdonald-Maier•Thu May 02 2019
This work introduces DisplaceNet, a novel model which infers potential displaced people from images by integrating the control level of the situation and conventional convolutional neural network (CNN) classifier into one framework for image classification.
5