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Ming Hu

7 papers here

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

author position
  • first author2
  • middle author4

Across the 6 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cond-mat.mtrl-sci1
  • cs.LG1
  • physics.app-ph1
ORCID 0000-0002-8209-0139
same name
  • Ming Hu — 8 papers, h 49
  • Ming Hu — 4 papers, h 14
  • Ming Hu — 4 papers
  • Ming Hu — 2 papers, h 14
  • Ming Hu — 1 paper, h 2
  • Ming Hu — 1 paper

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
20162024
most citedOn the mechanism of hydrophilicity of graphene

188 citations · 198 across the 7 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024

Texture Re-scalable Universal Adversarial Perturbation

Yihao Huang, Qing Guo, Felix Juefei-Xu +5

Universal adversarial perturbation (UAP), also known as image-agnostic perturbation, is a fixed perturbation map that can fool the classifier with high probabilities on arbitrary i…

cs.CV2023★ 4 cited

NurViD: A Large Expert-Level Video Database for Nursing Procedure Activity Understanding

Ming Hu, Lin Wang, Siyuan Yan +7

The application of deep learning to nursing procedure activity understanding has the potential to greatly enhance the quality and safety of nurse-patient interactions. By utilizing…

cs.CV2023★ 6 cited

MammalNet: A Large-scale Video Benchmark for Mammal Recognition and Behavior Understanding

Jun Chen, Ming Hu, Darren J. Coker +5

Monitoring animal behavior can facilitate conservation efforts by providing key insights into wildlife health, population status, and ecosystem function. Automatic recognition of a…

cs.CV2023

Architecture-agnostic Iterative Black-box Certified Defense against Adversarial Patches

Di Yang, Yihao Huang, Qing Guo +4

The adversarial patch attack aims to fool image classifiers within a bounded, contiguous region of arbitrary changes, posing a real threat to computer vision systems (e.g., autonom…

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