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researcher

J. Zhang

4 papers hereh-index 282.8k citations219 works total

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

author position
  • last author4

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

fields
  • cs.CV3
  • eess.IV1
same name
  • J. Zhang — 183 papers
  • J. Zhang — 167 papers, h 57
  • J. Zhang — 159 papers, h 58
  • J. Zhang — 159 papers, h 48
  • J. Zhang — 157 papers, h 48
  • J. Zhang — 54 papers, h 46

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
20172021
most citedAugmented Reality for Depth Cues in Monocular Minimally Invasive Surgery

8 citations · 8 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2021

Surgical Instruction Generation with Transformers

Jinglu Zhang, Yinyu Nie, Jian Chang +1

Automatic surgical instruction generation is a prerequisite towards intra-operative context-aware surgical assistance. However, generating instructions from surgical scenes is chal…

eess.IV2020

Symmetric Dilated Convolution for Surgical Gesture Recognition

Jinglu Zhang, Yinyu Nie, Yao Lyu +4

Automatic surgical gesture recognition is a prerequisite of intra-operative computer assistance and objective surgical skill assessment. Prior works either require additional senso…

cs.CV2018

Context-Aware Mixed Reality: A Framework for Ubiquitous Interaction

Long Chen, Wen Tang, Nigel John +2

Mixed Reality (MR) is a powerful interactive technology that yields new types of user experience. We present a semantic based interactive MR framework that exceeds the current geom…

cs.CV2017★ 8 cited

Augmented Reality for Depth Cues in Monocular Minimally Invasive Surgery

Long Chen, Wen Tang, Nigel W. John +2

One of the major challenges in Minimally Invasive Surgery (MIS) such as laparoscopy is the lack of depth perception. In recent years, laparoscopic scene tracking and surface recons…

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