10 papers
Prototype-Rectified Iterative Self-supervised Manifold Denoising under Severe Acoustic Shift
Ashish Anand Shukla, Rini Smita Thakur, Aryan Das +1
Audio-Text Foundation Models (ATMs) fail catastrophically under severe acoustic noise, yet existing adaptation strategies either rely on gradient-based Test-Time Adaptation (TTA),…
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…
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…
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…
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…
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…