Xiongwei Wu
-
- Advanced Neural Network Applications 5
- Robotic Path Planning Algorithms 3
- Media Technology top 5%
-
- Cooperative Communication and Network Coding 6
- Caching and Content Delivery 5
- Artificial Intelligence top 5%
- Domain Adaptation and Few-Shot Learning 4
-
- Advanced MIMO Systems Optimization 4
- Advanced Wireless Communication Technologies 3
-
- Congenital Heart Disease Studies 2
- Co-authors
- Steven C. H. HoiDoyen SahooVictor C. M. LeungP.C. ChingXiuhua LiXian‐Sheng HuaQianru SunTan Wang
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyComputer Networks and Communications
In The Last Decade
Xiongwei Wu
20 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Computer Vision and Pattern Recognition 646
- Media Technology 126
- Computer Networks and Communications 213
- Artificial Intelligence 291
- Industrial and Manufacturing Engineering 88
Countries citing papers authored by Xiongwei Wu
This map shows the geographic impact of Xiongwei Wu'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 Xiongwei Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiongwei Wu more than expected).
Fields of papers citing papers by Xiongwei Wu
This network shows the impact of papers produced by Xiongwei Wu. 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 Xiongwei Wu. The network helps show where Xiongwei Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiongwei Wu, 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 | 2024 | 0 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 0 | |
| 4 | 2022 | 24 | |
| 5 | 2022 | 2 | |
| 6 | Class Re-Activation Maps for Weakly-Supervised Semantic Segmentationbreakdown → | 2022 | 138 |
| 7 | 2021 | 76 | |
| 8 | 2021 | 31 | |
| 9 | 2021 | 53 | |
| 10 | PolarNet: Learning to Optimize Polar Keypoints for Keypoint Based Object Detection | 2021 | 4 |
| 11 | 2021 | 0 | |
| 12 | 2020 | 19 | |
| 13 | 2020 | 22 | |
| 14 | 2020 | 5 | |
| 15 | Recent advances in deep learning for object detectionbreakdown → | 2020 | 711 |
| 16 | 2020 | 2 | |
| 17 | 2019 | 18 | |
| 18 | 2019 | 9 | |
| 19 | 2018 | 8 | |
| 20 | 2018 | 4 |
About Xiongwei Wu
Xiongwei Wu is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 23 papers that have together received 1.3k indexed citations. Recurring topics across this work include Cooperative Communication and Network Coding (6 papers), Caching and Content Delivery (5 papers), Advanced Neural Network Applications (5 papers), Advanced MIMO Systems Optimization (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Advanced Wireless Communication Technologies (3 papers), Robotic Path Planning Algorithms (3 papers) and Congenital Heart Disease Studies (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (646 citations), Media Technology (126 citations) and Computer Networks and Communications (213 citations). Xiongwei Wu has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Steven C. H. Hoi, Doyen Sahoo, Victor C. M. Leung, P.C. Ching, Xiuhua Li, Xian‐Sheng Hua, Qianru Sun, Tan Wang, Hanwang Zhang and Jun Li. Their work appears in journals such as IEEE Transactions on Communications, IEEE Transactions on Wireless Communications and Neurocomputing.
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.