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20232026
most citedPredicting Missing Light Curves of Gamma-Ray Bursts with Bidirectional-LSTM: An Approach for Enhanced Analysis

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cs.CV2026

FairRSFM: A Biome-Aware Benchmark and Debiasing Framework for Remote Sensing Foundation Models

Md Aminur Hossain, Omkumar Vaghasiya, Rajeev Ranjan Dwivedi +2

Remote sensing foundation models (RSFMs) are commonly evaluated using aggregate metrics, which can hide systematic performance disparities across ecological regions. We introduce F…

cs.CV2026

AlignJEPA: Predictive Vision-Language Alignment for Remote Sensing Foundation Models

Md Aminur Hossain, Omkumar Vaghasiya, Rajeev Ranjan Dwivedi +2

Remote sensing (RS) foundation models provide transferable Earth observation representations across sensors, resolutions, and geographies, yet most remain weakly aligned with natur…

cs.CV2026

Histogram Assisted Quality Aware Generative Model for Resolution Invariant NIR Image Colorization

Abhinav Attri, Rajeev Ranjan Dwivedi, Samiran Das +1

We present HAQAGen, a unified generative model for resolution-invariant NIR-to-RGB colorization that balances chromatic realism with structural fidelity. The proposed model introdu…

cs.CV2025

Grad-CL: Source Free Domain Adaptation with Gradient Guided Feature Disalignment

Rini Smita Thakur, Rajeev Ranjan Dwivedi, Vinod K Kurmi

Accurate segmentation of the optic disc and cup is critical for the early diagnosis and management of ocular diseases such as glaucoma. However, segmentation models trained on one…

cs.CV2025

Multi Attribute Bias Mitigation via Representation Learning

Rajeev Ranjan Dwivedi, Ankur Kumar, Vinod K Kurmi

Real world images frequently exhibit multiple overlapping biases, including textures, watermarks, gendered makeup, scene object pairings, etc. These biases collectively impair the…

cs.CV2024

CosFairNet:A Parameter-Space based Approach for Bias Free Learning

Rajeev Ranjan Dwivedi, Priyadarshini Kumari, Vinod K Kurmi

Deep neural networks trained on biased data often inadvertently learn unintended inference rules, particularly when labels are strongly correlated with biased features. Existing bi…