Bo Zhao
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- Multimodal Machine Learning Applications 14
- Generative Adversarial Networks and Image Synthesis 12
- Advanced Neural Network Applications 9
- Advanced Image and Video Retrieval Techniques 9
- Radiation top 5%
- Advanced Radiotherapy Techniques 17
- Artificial Intelligence top 5%
- Analytical Chemistry top 5%
- Spectroscopy and Chemometric Analyses 9
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- Smart Agriculture and AI 15
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- Medical Imaging Techniques and Applications 8
- Co-authors
- Xiao WuShuicheng YanJiashi FengHakan BilenYajun ChenYuanyuan DingXiaobing KangLeonid Sigal
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignRadiation
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Bo Zhao
86 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Computer Vision and Pattern Recognition 956
- Computer Graphics and Computer-Aided Design 73
- Radiation 144
- Artificial Intelligence 398
- Analytical Chemistry 98
Countries citing papers authored by Bo Zhao
This map shows the geographic impact of Bo Zhao'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 Bo Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bo Zhao more than expected).
Fields of papers citing papers by Bo Zhao
This network shows the impact of papers produced by Bo Zhao. 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 Bo Zhao. The network helps show where Bo Zhao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bo Zhao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 4 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 3 | |
| 7 | 2022 | 45 | |
| 8 | Dataset Condensation with Gradient Matching | 2021 | 3 |
| 9 | Review of Weed Detection Methods Based on Computer Visionbreakdown → | 2021 | 185 |
| 10 | 2021 | 12 | |
| 11 | 2020 | 63 | |
| 12 | 2019 | 6 | |
| 13 | 2018 | 8 | |
| 14 | 2017 | 22 | |
| 15 | 2017 | 1 | |
| 16 | 2017 | 97 | |
| 17 | 2017 | 25 | |
| 18 | 2016 | 1 | |
| 19 | 2010 | 14 | |
| 20 | 2002 | 10 |
About Bo Zhao
Bo Zhao is a scholar working on Computer Vision and Pattern Recognition, Radiation and Analytical Chemistry, having authored 93 papers that have together received 1.9k indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (17 papers), Smart Agriculture and AI (15 papers), Multimodal Machine Learning Applications (14 papers), Generative Adversarial Networks and Image Synthesis (12 papers), Advanced Neural Network Applications (9 papers), Spectroscopy and Chemometric Analyses (9 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Medical Imaging Techniques and Applications (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (956 citations), Computer Graphics and Computer-Aided Design (73 citations) and Radiation (144 citations). Bo Zhao has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiao Wu, Shuicheng Yan, Jiashi Feng, Hakan Bilen, Yajun Chen, Yuanyuan Ding, Xiaobing Kang, Leonid Sigal, Lili Meng and Jianguo Xiao.
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.