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P. Biswas

4 papers hereh-index 293.4k citations192 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • eess.IV1
same name
  • P. Biswas — 3 papers, h 4
  • P. Biswas — 1 paper, h 0
  • P. Biswas — 1 paper, h 3
  • P. Biswas — 1 paper, h 0
  • P. Biswas — 1 paper, h 1
  • P. Biswas — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.CV2026

Sharing the Learned Knowledge-base to Estimate Convolutional Filter Parameters for Continual Image Restoration

Aupendu Kar, Krishnendu Ghosh, Prabir Kumar Biswas

Continual learning is an emerging topic in the field of deep learning, where a model is expected to learn continuously for new upcoming tasks without forgetting previous experience…

cs.CV2025

Light-Field Dataset for Disparity Based Depth Estimation

Suresh Nehra, Aupendu Kar, Jayanta Mukhopadhyay +1

A Light Field (LF) camera consists of an additional two-dimensional array of micro-lenses placed between the main lens and sensor, compared to a conventional camera. The sensor pix…

eess.IV2025

Artificially Generated Visual Scanpath Improves Multi-label Thoracic Disease Classification in Chest X-Ray Images

Ashish Verma, Aupendu Kar, Krishnendu Ghosh +3

Expert radiologists visually scan Chest X-Ray (CXR) images, sequentially fixating on anatomical structures to perform disease diagnosis. An automatic multi-label classifier of dise…

cs.CV2025

Self-supervision via Controlled Transformation and Unpaired Self-conditioning for Low-light Image Enhancement

Aupendu Kar, Sobhan K. Dhara, Debashis Sen +1

Real-world low-light images captured by imaging devices suffer from poor visibility and require a domain-specific enhancement to produce artifact-free outputs that reveal details.…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.