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researcher

P. Goyal

4 papers hereh-index 338 citations16 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
  • cs.LG1
same name
  • P. Goyal — 46 papers, h 18
  • P. Goyal — 21 papers, h 10
  • P. Goyal — 15 papers, h 11
  • P. Goyal — 2 papers, h 32
  • P. Goyal — 2 papers, h 0
  • P. Goyal — 1 paper, h 25

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

activity
20242026
most citedMultimodal Fusion Learning with Dual Attention for Medical Imaging

2 citations · 2 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2026

Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention

Joy Dhar, Manish Kumar Pandey, Nayyar Zaidi +4

Multimodal fusion learning (MFL) has shown great potential in the medical domain, where we are faced with disparate data modalities such as imaging, clinical records, and omics. Ho…

cs.LG2026

LightMedSeg: Lightweight 3D Medical Image Segmentation with Learned Spatial Anchors

Kavyansh Tyagi, Vishwas Rathi, Puneet Goyal

Accurate and efficient 3D medical image segmentation is essential for clinical AI, where models must remain reliable under stringent memory, latency, and data availability constrai…

cs.CV2025

Camera Model Identification with SPAIR-Swin and Entropy based Non-Homogeneous Patches

Protyay Dey, Rejoy Chakraborty, Abhilasha S. Jadhav +3

Source camera model identification (SCMI) plays a pivotal role in image forensics with applications including authenticity verification and copyright protection. For identifying th…

cs.CV2024★ 2 cited

Multimodal Fusion Learning with Dual Attention for Medical Imaging

Joy Dhar, Nayyar Zaidi, Maryam Haghighat +4

Multimodal fusion learning has shown significant promise in classifying various diseases such as skin cancer and brain tumors. However, existing methods face three key limitations.…

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