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researcher

Q. Song

14 papers hereh-index 193.1k citations40 works total

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

author position
  • middle author11
  • last author1

Across the 12 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CV12
  • cs.CR1
  • eess.IV1
same name
  • Q. Song — 65 papers, h 19
  • Q. Song — 27 papers, h 15
  • Q. Song — 20 papers, h 51
  • Q. Song — 14 papers, h 15
  • Q. Song — 11 papers, h 9
  • Q. Song — 11 papers, h 12

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
20172022
most citedRisk Stratification of Lung Nodules Using 3D CNN-Based Multi-task Learning

163 citations · 224 across the 12 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.CV2021

Stochastic Actor-Executor-Critic for Image-to-Image Translation

Ziwei Luo, Jing Hu, Xin Wang +5

Training a model-free deep reinforcement learning model to solve image-to-image translation is difficult since it involves high-dimensional continuous state and action spaces. In t…

eess.IV2021

Stochastic Planner-Actor-Critic for Unsupervised Deformable Image Registration

Ziwei Luo, Jing Hu, Xin Wang +6

Large deformations of organs, caused by diverse shapes and nonlinear shape changes, pose a significant challenge for medical image registration. Traditional registration methods ne…

cs.CR2021★ 4 cited

Adaptive Warden Strategy for Countering Network Covert Storage Channels

Mehdi Chourib, Steffen Wendzel, Wojciech Mazurczyk

The detection and elimination of covert channels are performed by a network node, known as a warden. Especially if faced with adaptive covert communication parties, a regular warde…

cs.CV2021

Transferable Adversarial Examples for Anchor Free Object Detection

Quanyu Liao, Xin Wang, Bin Kong +5

Deep neural networks have been demonstrated to be vulnerable to adversarial attacks: subtle perturbation can completely change prediction result. The vulnerability has led to a sur…

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