Featured papers

The paper focuses on interrogating the effect of the IceNet's input feature with a gradient-based analysis.

Introducing the SuperCM technique to significantly improve classification results across various types of image data.

We approach the representation learning task by tackling the hubness problem.

We propose DeepMVC – a unified framework which includes many recent methods as instances.

ProtoVAE explainability paper by Srishti Gautam and co-authors is published to NeurIPS 2022.

We present a novel pyramid attention and gated fusion method (MultiModNet) for multi-modality land cover mapping in remote sensing.

How can we remove the redundant or less-informative edges in a graph without changing its main structural properties?

Developing artificial intelligence methods to help pathologists in analysis of whole slide images for cancer treatment and detection.

Detecting pneumonia using self-explainable methods.