Z
Ziyan Wu
Researcher at Siemens
Publications - 96
Citations - 3883
Ziyan Wu is an academic researcher from Siemens. The author has contributed to research in topics: Computer science & Convolutional neural network. The author has an hindex of 19, co-authored 82 publications receiving 2269 citations. Previous affiliations of Ziyan Wu include Princeton University & Shanghai University.
Papers
More filters
Journal ArticleDOI
Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19
Feng Shi,Jun Wang,Jun Shi,Ziyan Wu,Qian Wang,Zhenyu Tang,Kelei He,Yinghuan Shi,Dinggang Shen +8 more
TL;DR: This review paper covers the entire pipeline of medical imaging and analysis techniques involved with COVID-19, including image acquisition, segmentation, diagnosis, and follow-up, and particularly focuses on the integration of AI with X-ray and CT, both of which are widely used in the frontline hospitals.
Proceedings ArticleDOI
Tell Me Where to Look: Guided Attention Inference Network
TL;DR: This work makes attention maps an explicit and natural component of the end-to-end training for the first time and provides self-guidance directly on these maps by exploring supervision from the network itself to improve them, and seamlessly bridge the gap between using weak and extra supervision if available.
Proceedings ArticleDOI
Learning Without Memorizing
TL;DR: This work proposes a novel approach, called `Learning without Memorizing (LwM), to preserve the information about existing (base) classes, without storing any of their data, while making the classifier progressively learn the new classes.
Proceedings Article
Counterfactual Visual Explanations
TL;DR: In this article, a technique to produce counterfactual visual explanations was developed for fine-grained bird classification, where a visual explanation identifies how a query image could change such that the system would output a different specified class.
Journal ArticleDOI
Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19
Feng Shi,Jun Wang,Jun Shi,Ziyan Wu,Qian Wang,Zhenyu Tang,Kelei He,Yinghuan Shi,Dinggang Shen +8 more
TL;DR: In this article, the authors reviewed the rapid responses in the community of medical imaging (empowered by AI) toward COVID-19, including image acquisition, segmentation, diagnosis, and follow-up.