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Tao Chen

11 papers hereh-index 11333 citations19 works total

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

author position
  • first author2
  • middle author7
  • last author1

Across the 10 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CV5
  • cs.CL2
  • cs.SE2
  • astro-ph.GA1
  • cs.AI1
same name
  • Tao Chen — 49 papers, h 49
  • Tao Chen — 37 papers, h 25
  • Tao Chen — 30 papers, h 14
  • Tao Chen — 18 papers, h 3
  • Tao Chen — 17 papers, h 10
  • Tao Chen — 16 papers, h 5

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
20212025
most citedGeneralizable Pancreas Segmentation via a Dual Self-Supervised Learning Framework

10 citations · 23 across the 11 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CV2023

Boosting Residual Networks with Group Knowledge

Shengji Tang, Peng Ye, Baopu Li +5

Recent research understands the residual networks from a new perspective of the implicit ensemble model. From this view, previous methods such as stochastic depth and stimulative t…

cs.CV2023

Attention Consistency Refined Masked Frequency Forgery Representation for Generalizing Face Forgery Detection

Decheng Liu, Tao Chen, Chunlei Peng +3

Due to the successful development of deep image generation technology, visual data forgery detection would play a more important role in social and economic security. Existing forg…

cs.AI2023★ 1 cited

Adversarial Amendment is the Only Force Capable of Transforming an Enemy into a Friend

Chong Yu, Tao Chen, Zhongxue Gan

Adversarial attack is commonly regarded as a huge threat to neural networks because of misleading behavior. This paper presents an opposite perspective: adversarial attacks can be…

cs.CV2023

Semi-Supervised Semantic Segmentation With Region Relevance

Rui Chen, Tao Chen, Qiong Wang +1

Semi-supervised semantic segmentation aims to learn from a small amount of labeled data and plenty of unlabeled ones for the segmentation task. The most common approach is to gener…

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