Zizhou Wang

565 total citations
27 papers, 344 citations indexed

About

Zizhou Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Zizhou Wang has authored 27 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 15 papers in Computer Vision and Pattern Recognition and 9 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Zizhou Wang's work include AI in cancer detection (10 papers), Domain Adaptation and Few-Shot Learning (8 papers) and Advanced Neural Network Applications (6 papers). Zizhou Wang is often cited by papers focused on AI in cancer detection (10 papers), Domain Adaptation and Few-Shot Learning (8 papers) and Advanced Neural Network Applications (6 papers). Zizhou Wang collaborates with scholars based in China, Singapore and United States. Zizhou Wang's co-authors include Lei Zhang, Xin Shu, Yi Zhang, Qing Lv, Yangqin Feng, Lituan Wang, Yan Wang, Yan Wang, Yan Wang and Chaoyue Chen and has published in prestigious journals such as IEEE Transactions on Medical Imaging, Information Sciences and Journal of Medical Internet Research.

In The Last Decade

Zizhou Wang

23 papers receiving 337 citations

Peers

Zizhou Wang

RNMI

CVPR

NEURO

Xin Shu China

Nicola Rieke United Kingdom

Vivek Natarajan United States

Aaron Loh United States

Cheng Bian China

Shiliang Ai China

Mingquan Lin United States

Adnan N. Qureshi Pakistan

Nor Aniza Azmi Malaysia

Xin Shu China

Zizhou Wang

191 ×0.8

141 ×0.8

RNMI

86 ×0.7

CVPR

58 ×1.0

NEURO

28 ×1.0

Citations per year, relative to Zizhou Wang Zizhou Wang (= 1×) peers Xin Shu

Countries citing papers authored by Zizhou Wang

Since Specialization

Citations

This map shows the geographic impact of Zizhou Wang'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 Zizhou Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zizhou Wang more than expected).

Fields of papers citing papers by Zizhou Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zizhou Wang. 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 Zizhou Wang. The network helps show where Zizhou Wang may publish in the future.

Co-authorship network of co-authors of Zizhou Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Zizhou Wang. A scholar is included among the top collaborators of Zizhou Wang 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 Zizhou Wang. Zizhou Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Wang, Zizhou, et al.. (2025). A multi-stage multi-modal learning algorithm with adaptive multimodal fusion for improving multi-label skin lesion classification. Artificial Intelligence in Medicine. 162. 103091–103091. 1 indexed citations

Zhang, Lei, et al.. (2024). Class-Center-Based Self-Knowledge Distillation: A Simple Method to Reduce Intra-Class Variance. Applied Sciences. 14(16). 7022–7022.

Huang, Wei, Lei Zhang, Zizhou Wang, & Lituan Wang. (2024). Exploring Inherent Consistency for Semi-Supervised Anatomical Structure Segmentation in Medical Imaging. IEEE Transactions on Medical Imaging. 43(11). 3731–3741. 7 indexed citations

Zang, Liguo, et al.. (2024). Angle-Weighted trilateration method fusing multi-data processing technologies in indoor scene. Digital Signal Processing. 147. 104417–104417. 3 indexed citations

Wang, Zizhou, Yan Wang, Yangqin Feng, et al.. (2024). Continuous Disentangled Joint Space Learning for Domain Generalization. IEEE Transactions on Neural Networks and Learning Systems. 36(7). 13122–13134. 1 indexed citations

Huang, Wei, Lei Zhang, Xin Shu, Zizhou Wang, & Yi Zhang. (2024). Adaptive Annotation Correlation Based Multi-Annotation Learning for Calibrated Medical Image Segmentation. IEEE Journal of Biomedical and Health Informatics. 28(12). 7175–7183.

Wang, Yan, Liangli Zhen, Tien‐En Tan, et al.. (2024). Geometric Correspondence-Based Multimodal Learning for Ophthalmic Image Analysis. IEEE Transactions on Medical Imaging. 43(5). 1945–1957. 15 indexed citations

Shu, Xin, Lei Zhang, Zizhou Wang, Lituan Wang, & Yi Zhang. (2023). Fine-grained recognition: Multi-granularity labels and category similarity matrix. Knowledge-Based Systems. 273. 110599–110599. 7 indexed citations

Chen, Chaoyue, et al.. (2023). Performance Test of a Well-Trained Model for Meningioma Segmentation in Health Care Centers: Secondary Analysis Based on Four Retrospective Multicenter Data Sets. Journal of Medical Internet Research. 25. e44119–e44119. 2 indexed citations

10.

Feng, Yangqin, Jordan Sim, Xinxing Xu, et al.. (2023). Deep Neural Network Augments Performance of Junior Residents in Diagnosing COVID-19 Pneumonia on Chest Radiographs. Diagnostics. 13(8). 1397–1397. 3 indexed citations

11.

Shu, Xin, Lei Zhang, Lituan Wang, et al.. (2022). Deep Slice-Crossed Network With Local Weighted Loss for Brain Metastases Segmentation. IEEE Transactions on Cognitive and Developmental Systems. 15(3). 1419–1429. 2 indexed citations

12.

Feng, Yangqin, Zizhou Wang, Xinxing Xu, et al.. (2022). Contrastive domain adaptation with consistency match for automated pneumonia diagnosis. Medical Image Analysis. 83. 102664–102664. 19 indexed citations

13.

Huang, Wei, Xin Shu, Zizhou Wang, et al.. (2022). Boundary-Aware Network With Topological Consistency Constraint for Optic Chiasm Segmentation. IEEE Transactions on Artificial Intelligence. 4(6). 1504–1513. 4 indexed citations

14.

Wang, Zizhou, Xin Shu, Yan Wang, et al.. (2022). A Feature Space-Restricted Attention Attack on Medical Deep Learning Systems. IEEE Transactions on Cybernetics. 53(8). 5323–5335. 12 indexed citations

15.

Wang, Yan, Yangqin Feng, Lei Zhang, et al.. (2021). Deep adversarial domain adaptation for breast cancer screening from mammograms. Medical Image Analysis. 73. 102147–102147. 23 indexed citations

16.

Wang, Zizhou, et al.. (2021). Image Caption and Medical Report Generation Based on Deep Learning: a Review and Algorithm Analysis. 373–379. 5 indexed citations

17.

Wang, Yan, Zizhou Wang, Yangqin Feng, & Lei Zhang. (2021). WDCCNet: Weighted Double-Classifier Constraint Neural Network for Mammographic Image Classification. IEEE Transactions on Medical Imaging. 41(3). 559–570. 23 indexed citations

18.

Wang, Zizhou, et al.. (2021). A semi-symmetric domain adaptation network based on multi-level adversarial features for meningioma segmentation. Knowledge-Based Systems. 228. 107245–107245. 7 indexed citations

19.

Wang, Zizhou, Lei Zhang, Xin Shu, Qing Lv, & Yi Zhang. (2020). An End-to-End Mammogram Diagnosis: A New Multi-Instance and Multiscale Method Based on Single-Image Feature. IEEE Transactions on Cognitive and Developmental Systems. 13(3). 535–545. 21 indexed citations

20.

Wang, Yan, Lei Zhang, Lituan Wang, & Zizhou Wang. (2018). Multitask Learning for Object Localization With Deep Reinforcement Learning. IEEE Transactions on Cognitive and Developmental Systems. 11(4). 573–580. 43 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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