activity
20172026
most citedHybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classification

1.9k citations · 3.2k across the 26 of their papers we have counts for

collaborators

30 papers

cs.CV2026

A PyTorch Library for Hyperspectral Image Models: Technical Report

Tanishq Rachamalla, Aryan Das, Srishti Kaushik +1

Hyperspectral remote sensing has advanced across diverse deep learning paradigms, including spectral spatial CNNs, Vision Transformers, Mamba, graph neural networks, Kolmogorov Arn…

cs.CV2026★ 2 cited

MixerSENet: A Lightweight Framework for Efficient Hyperspectral Image Classification

Mohammed Q. Alkhatib, Swalpa Kumar Roy, Ali Jamali

In this paper, a novel framework, MixerSENet, is introduced for hyperspectral image (HSI) classification, designed to address the challenges of computational efficiency and limited…

cs.CV2026

Efficient Text-Guided Convolutional Adapter for the Diffusion Model

Aryan Das, Koushik Biswas, Swalpa Kumar Roy +2

We introduce the Nexus Adapters, novel text-guided efficient adapters to the diffusion-based framework for the Structure Preserving Conditional Generation (SPCG). Recently, structu…

cs.CV2026

Uncertainty-Aware Vision-Language Segmentation for Medical Imaging

Aryan Das, Tanishq Rachamalla, Koushik Biswas +2

We introduce a novel uncertainty-aware multimodal segmentation framework that leverages both radiological images and associated clinical text for precise medical diagnosis. We prop…

cs.CV2025

SceneMixer: Exploring Convolutional Mixing Networks for Remote Sensing Scene Classification

Mohammed Q. Alkhatib, Ali Jamali, Swalpa Kumar Roy

Remote sensing scene classification plays a key role in Earth observation by enabling the automatic identification of land use and land cover (LULC) patterns from aerial and satell…

cs.CE2025

RoadBench: A Vision-Language Foundation Model and Benchmark for Road Damage Understanding

Xi Xiao, Yunbei Zhang, Janet Wang +9

Accurate road damage detection is crucial for timely infrastructure maintenance and public safety, but existing vision-only datasets and models lack the rich contextual understandi…