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publications
Prototypical Quadruplet for Few-Shot Class Incremental Learning
Published in Procedia Computer Science, 2023
A prototypical few-shot class-incremental learning framework with contrastive embedding optimization and prototype re-centering for mitigating catastrophic forgetting and improving robust classification under limited data settings
Recommended citation: Sanchar Palit, Subhasis Chaudhuri, and Biplab Banerjee, "Prototypical Quadruplet for Few-Shot Class Incremental Learning", Procedia Computer Science, presented at INNS DLIA, IJCNN 2023
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Variational Distribution and Experience Replay for 3D Reconstruction in a Continual Learning Framework
Published in Proceedings of the Fifteenth Indian Conference on Computer Vision Graphics and Image Processing, 2024
A continual learning framework for single-image 3D reconstruction that leverages variational latent priors and saliency map-based replay to preserve geometric structure and accurately reconstruct both previously seen and newly learned object classes. Best Paper Award — ICVGIP 2024
Recommended citation: Sanchar Palit and Sandika Biswas, "Variational Distribution and Experience Replay for 3D Reconstruction in a Continual Learning Framework", ICVGIP, 2024.
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Revised Regularization for Efficient Continual Learning through Correlation-Based Parameter Update in Bayesian Neural Networks
Published in Proceedings of the Fifteenth Indian Conference on Computer Vision Graphics and Image Processing, 2024
A variational continual learning framework for Bayesian neural networks with parameter-efficient distribution learning, revised KL-based regularization, and importance-weighted ELBO for reducing catastrophic forgetting and improving knowledge transfer
Recommended citation: Sanchar Palit, Subhasis Chaudhuri, and Biplab Banerjee, "Revised Regularization for Efficient Continual Learning through Correlation-Based Parameter Update in Bayesian Neural Networks", ICVGIP, 2024.
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Local-global context-aware and structure-preserving image super-resolution
Published in Neurocomputing, 2026
A multi-step diffusion-based image super-resolution framework that integrates local-global context-aware attention and distribution alignment for perceptually faithful image reconstruction.
Recommended citation: Sanchar Palit, Subhasis Chaudhuri, and Biplab Banerjee, "Local-Global Context-Aware and Structure-Preserving Image Super-Resolution," Neurocomputing, Elsevier, 2026.
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Discontinuity-Preserving Image Super-Resolution using MRF-Regularized One-Step Diffusion
Published in Transactions on Machine Learning Research, 2026
A single-step diffusion-based image super-resolution framework with MRF prior regularization for efficient, sharp, and fast image super-resolution.
Recommended citation: Sanchar Palit, Subhasis Chaudhuri, and Biplab Banerjee, "Discontinuity-Preserving Image Super-Resolution using MRF-Regularized One-Step Diffusion", accepted at Transactions on Machine Learning Research (TMLR), 2026
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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