◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Chengyu Song

19 papers hereh-index 314k citations83 works total

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

author position
  • middle author18
  • last author1

Across the 19 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • cs.CR6
  • cs.LG2
  • cs.AR1
  • cs.CL1
same name
  • Chengyu Song — 4 papers, h 3
  • Chengyu Song — 3 papers, h 2
  • Chengyu Song — 2 papers, h 6
  • Chengyu Song — 2 papers, h 2
  • Chengyu Song — 2 papers, h 4
  • Chengyu Song — 2 papers, h 4

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
20182026
most citedIoTSan: Fortifying the Safety of IoT Systems

118 citations · 284 across the 16 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.CV2021

Context-Aware Transfer Attacks for Object Detection

Zikui Cai, Xinxin Xie, Shasha Li +5

Blackbox transfer attacks for image classifiers have been extensively studied in recent years. In contrast, little progress has been made on transfer attacks for object detectors.…

cs.CV2021★ 7 cited

Adversarial Attacks on Black Box Video Classifiers: Leveraging the Power of Geometric Transformations

Shasha Li, Abhishek Aich, Shitong Zhu +4

When compared to the image classification models, black-box adversarial attacks against video classification models have been largely understudied. This could be possible because,…

cs.CV2021★ 1 cited

ADC: Adversarial attacks against object Detection that evade Context consistency checks

Mingjun Yin, Shasha Li, Chengyu Song +3

Deep Neural Networks (DNNs) have been shown to be vulnerable to adversarial examples, which are slightly perturbed input images which lead DNNs to make wrong predictions. To protec…

cs.CV2021★ 1 cited

Exploiting Multi-Object Relationships for Detecting Adversarial Attacks in Complex Scenes

Mingjun Yin, Shasha Li, Zikui Cai +4

Vision systems that deploy Deep Neural Networks (DNNs) are known to be vulnerable to adversarial examples. Recent research has shown that checking the intrinsic consistencies in th…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.