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20182026
most citedSensor-invariant Fingerprint ROI Segmentation Using Recurrent Adversarial Learning

13 citations · 19 across the 18 of their papers we have counts for

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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

CLFSeg: A Fuzzy-Logic based Solution for Boundary Clarity and Uncertainty Reduction in Medical Image Segmentation

Anshul Kaushal, Kunal Jangid, Vinod K. Kurmi

Accurate polyp and cardiac segmentation for early detection and treatment is essential for the diagnosis and treatment planning of cancer-like diseases. Traditional convolutional n…

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.CV2025

Strategic Base Representation Learning via Feature Augmentations for Few-Shot Class Incremental Learning

Parinita Nema, Vinod K Kurmi

Few-shot class incremental learning implies the model to learn new classes while retaining knowledge of previously learned classes with a small number of training instances. Existi…