Yizhou Yu

19.4k total citations · 9 hit papers
221 papers, 9.5k citations indexed

About

Yizhou Yu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Yizhou Yu has authored 221 papers receiving a total of 9.5k indexed citations (citations by other indexed papers that have themselves been cited), including 139 papers in Computer Vision and Pattern Recognition, 68 papers in Artificial Intelligence and 54 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Yizhou Yu's work include Advanced Image and Video Retrieval Techniques (35 papers), Computer Graphics and Visualization Techniques (34 papers) and Advanced Neural Network Applications (33 papers). Yizhou Yu is often cited by papers focused on Advanced Image and Video Retrieval Techniques (35 papers), Computer Graphics and Visualization Techniques (34 papers) and Advanced Neural Network Applications (33 papers). Yizhou Yu collaborates with scholars based in China, Hong Kong and United States. Yizhou Yu's co-authors include Guanbin Li, Xiaoguang Han, Hong-Yu Zhou, Sibei Yang, Baoyuan Wang, Weifeng Ge, Zhicheng Yan, Hao Zhang, Xiangru Lin and Yezhou Yang and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Yizhou Yu

216 papers receiving 9.3k citations

Hit Papers

Visual saliency based on multiscale deep features 2015 2026 2018 2022 2015 2016 2015 2019 2016 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Visual saliency based on multiscale deep features
    2015 671 citations Yizhou Yu et al. The HKU Scholars Hub (University of Hong Kong) profile →
  2. Deep Contrast Learning for Salient Object Detection
    2016 490 citations Yizhou Yu et al. profile →
  3. HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition
    2015 482 citations Zhicheng Yan, Hao Zhang et al. The HKU Scholars Hub (University of Hong Kong) profile →
  4. Neural Style Transfer: A Review
    2019 457 citations Yizhou Yu et al. IEEE Transactions on Visualization and Computer Graphics profile →
  5. Visual Saliency Detection Based on Multiscale Deep CNN Features
    2016 295 citations Yizhou Yu et al. IEEE Transactions on Image Processing profile →
  6. nnFormer: Volumetric Medical Image Segmentation via a 3D Transformer
    2023 287 citations Hong-Yu Zhou, Jiansen Guo et al. IEEE Transactions on Image Processing profile →
  7. A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics
    2023 168 citations Hong-Yu Zhou, Yizhou Yu et al. profile →
  8. The long-term health outcomes, pathophysiological mechanisms and multidisciplinary management of long COVID
    2023 60 citations Jiechao Ma, Yizhou Yu et al. profile →
  9. TransXNet: Learning Both Global and Local Dynamics With a Dual Dynamic Token Mixer for Visual Recognition
    2025 19 citations Shu Zhang, Hong-Yu Zhou et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yizhou Yu China 51 6.2k 2.3k 1.5k 830 727 221 9.5k
Enhua Wu China 21 5.8k 0.9× 2.1k 0.9× 1.0k 0.7× 664 0.8× 649 0.9× 198 10.1k
Antonio Criminisi United Kingdom 57 10.2k 1.6× 1.9k 0.8× 962 0.6× 1.1k 1.3× 585 0.8× 153 13.6k
Chi‐Wing Fu Hong Kong 53 6.8k 1.1× 1.5k 0.6× 1.7k 1.1× 1.6k 2.0× 2.5k 3.5× 211 11.2k
Yuri Boykov Canada 27 11.2k 1.8× 1.8k 0.8× 1.5k 1.0× 876 1.1× 1.1k 1.5× 67 14.6k
Stephen M. Pizer United States 42 6.3k 1.0× 1.1k 0.5× 1.9k 1.2× 970 1.2× 1.2k 1.6× 234 9.8k
Dimitris Metaxas United States 48 5.3k 0.8× 1.4k 0.6× 1.1k 0.7× 255 0.3× 715 1.0× 281 8.4k
Ghassan Hamarneh Canada 39 2.7k 0.4× 1.8k 0.8× 1.9k 1.2× 271 0.3× 552 0.8× 252 6.7k
Nikos Paragios France 46 6.2k 1.0× 1.4k 0.6× 3.1k 2.0× 266 0.3× 750 1.0× 198 10.5k
W. Eric L. Grimson United States 48 13.9k 2.2× 3.0k 1.3× 1.7k 1.1× 410 0.5× 604 0.8× 142 16.9k
Bart M. ter Haar Romeny Netherlands 39 4.7k 0.8× 880 0.4× 2.8k 1.9× 255 0.3× 384 0.5× 195 8.9k

Countries citing papers authored by Yizhou Yu

Since Specialization
Citations

This map shows the geographic impact of Yizhou Yu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yizhou Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yizhou Yu more than expected).

Fields of papers citing papers by Yizhou Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yizhou Yu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yizhou Yu. The network helps show where Yizhou Yu may publish in the future.

Co-authorship network of co-authors of Yizhou Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Yizhou Yu. A scholar is included among the top collaborators of Yizhou Yu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yizhou Yu. Yizhou Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Xiaoxia, Xiaofei Hu, Hua Yang, et al.. (2025). Automatic Segmentation and Molecular Subtype Classification of Breast Cancer Using an MRI-based Deep Learning Framework. Radiology Imaging Cancer. 7(3). e240184–e240184. 1 indexed citations
2.
Hu, Ge, et al.. (2024). Predicting Invasiveness of Lung Adenocarcinoma at Chest CT with Deep Learning Ternary Classification Models. Radiology. 311(1). e232057–e232057. 16 indexed citations
3.
Peng, Fei, Fandong Zhang, Shiyu Lu, et al.. (2024). Intracranial aneurysm instability prediction model based on 4D-Flow MRI and HR-MRI. Neurotherapeutics. 22(1). e00505–e00505. 3 indexed citations
4.
Liu, Feng, et al.. (2023). Automated detection and classification of acute vertebral body fractures using a convolutional neural network on computed tomography. Frontiers in Endocrinology. 14. 1132725–1132725. 19 indexed citations
5.
Zhang, Shu, Zihao Li, Hong-Yu Zhou, Jiechao Ma, & Yizhou Yu. (2023). Advancing 3D medical image analysis with variable dimension transform based supervised 3D pre-training. Neurocomputing. 529. 11–22. 5 indexed citations
6.
Zhou, Hong-Yu, Jiansen Guo, Yinghao Zhang, et al.. (2023). nnFormer: Volumetric Medical Image Segmentation via a 3D Transformer. IEEE Transactions on Image Processing. 32. 4036–4045. 287 indexed citations breakdown →
7.
Zhu, Qikui, Jiongcheng Li, Xiujun Cai, et al.. (2022). A Knowledge-Guided Framework for Fine-Grained Classification of Liver Lesions Based on Multi-Phase CT Images. IEEE Journal of Biomedical and Health Informatics. 27(1). 386–396. 15 indexed citations
8.
Zhao, Gangming, Kongming Liang, Chengwei Pan, et al.. (2022). Graph Convolution Based Cross-Network Multiscale Feature Fusion for Deep Vessel Segmentation. IEEE Transactions on Medical Imaging. 42(1). 183–195. 32 indexed citations
9.
Li, Chenxin, Xin Lin, Yijin Mao, et al.. (2021). Domain generalization on medical imaging classification using episodic training with task augmentation. Computers in Biology and Medicine. 141. 105144–105144. 59 indexed citations
10.
Lian, Jie, Jingyu Liu, Shu Zhang, et al.. (2021). A Structure-Aware Relation Network for Thoracic Diseases Detection and Segmentation. IEEE Transactions on Medical Imaging. 40(8). 2042–2052. 35 indexed citations
11.
Liu, Yuhang, et al.. (2021). Act Like a Radiologist: Towards Reliable Multi-View Correspondence Reasoning for Mammogram Mass Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(10). 5947–5961. 23 indexed citations
12.
Du, Dong, Yinyu Nie, Xiaoguang Han, et al.. (2020). Learning Part Generation and Assembly for Sketching Man‐Made Objects. Computer Graphics Forum. 40(1). 222–233. 3 indexed citations
13.
Song, Xiao, Xu Zhao, Liangji Fang, Hanwen Hu, & Yizhou Yu. (2020). EdgeStereo: An Effective Multi-task Learning Network for Stereo Matching and Edge Detection. International Journal of Computer Vision. 128(4). 910–930. 116 indexed citations
14.
Zhang, Dingwen, Qiang Zhang, Jungong Han, et al.. (2020). Exploring Task Structure for Brain Tumor Segmentation From Multi-Modality MR Images. IEEE Transactions on Image Processing. 29. 9032–9043. 135 indexed citations
15.
Cao, Kun, Min Cao, Xiao-Ting Li, et al.. (2020). Improving the Diagnostic Accuracy of Breast BI-RADS 4 Microcalcification-Only Lesions Using Contrast-Enhanced Mammography. Clinical Breast Cancer. 21(3). 256–262.e2. 18 indexed citations
16.
Tian, Yan, Judith Gelernter, Xun Wang, Jianyuan Li, & Yizhou Yu. (2019). Traffic Sign Detection Using a Multi-Scale Recurrent Attention Network. IEEE Transactions on Intelligent Transportation Systems. 20(12). 4466–4475. 73 indexed citations
17.
Han, Xiaoguang, Kangcheng Hou, Dong Du, et al.. (2018). CaricatureShop: Personalized and Photorealistic Caricature Sketching. IEEE Transactions on Visualization and Computer Graphics. 26(7). 2349–2361. 25 indexed citations
18.
Li, Zhen & Yizhou Yu. (2016). Protein secondary structure prediction using cascaded convolutional and recurrent neural networks. International Joint Conference on Artificial Intelligence. 2560–2567. 9 indexed citations
19.
Yan, Zhicheng, Hao Zhang, Robinson Piramuthu, et al.. (2015). HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition. The HKU Scholars Hub (University of Hong Kong). 2740–2748. 482 indexed citations breakdown →
20.
Edwards, A. David, et al.. (2003). Motion Field Estimation for Temporal Textures. 389–400. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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