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Kaushik Roy

6 papers hereh-index 326 citations6 works total

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

author position
  • last author6

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.AR1
  • cs.ET1
same name
  • Kaushik Roy — 18 papers
  • Kaushik Roy — 17 papers, h 19
  • Kaushik Roy — 10 papers, h 4
  • Kaushik Roy — 9 papers, h 4
  • Kaushik Roy — 8 papers, h 6
  • Kaushik Roy — 8 papers, 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

most citedTowards Two-Stream Foveation-based Active Vision Learning

2 citations · 4 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

FAVE: Foveated Adaptive Visual Encoding for Efficient Fine-Grained Visual Understanding

Amitangshu Mukherjee, Kaushik Roy

Fine-grained visual understanding depends on local detail, yet visual encoders face a trade-off between costly full-image high-resolution processing and compact global encoding tha…

cs.CV2024★ 2 cited

Towards Two-Stream Foveation-based Active Vision Learning

Timur Ibrayev, Amitangshu Mukherjee, Sai Aparna Aketi +1

Deep neural network (DNN) based machine perception frameworks process the entire input in a one-shot manner to provide answers to both "what object is being observed" and "where it…

cs.CV2024

On Inherent Adversarial Robustness of Active Vision Systems

Amitangshu Mukherjee, Timur Ibrayev, Kaushik Roy

Current Deep Neural Networks are vulnerable to adversarial examples, which alter their predictions by adding carefully crafted noise. Since human eyes are robust to such inputs, it…

cs.CV2024

Semantic-Syntactic Discrepancy in Images (SSDI): Learning Meaning and Order of Features from Natural Images

Chun Tao, Timur Ibrayev, Kaushik Roy

Despite considerable progress in image classification tasks, classification models seem unaffected by the images that significantly deviate from those that appear natural to human…

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