Xiang Bai
- Computer Vision and Pattern Recognition top 0.5%
- Media Technology top 0.5%
- Artificial Intelligence top 5%
- Aerospace Engineering top 10%
- Industrial and Manufacturing Engineering top 2%
- Co-authors
- Xinggang WangXiaowei HuYun LiuMing‐Ming ChengWenyu LiuPeng TangWei ShenKai Wang
- Topics
- Advanced Image and Video Retrieval Techniques (9 papers)Advanced Neural Network Applications (6 papers)Medical Image Segmentation Techniques (5 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyIndustrial and Manufacturing Engineering
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingFuel
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Xiang Bai
25 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Computer Vision and Pattern Recognition 1.7k
- Media Technology 478
- Artificial Intelligence 445
- Aerospace Engineering 175
- Industrial and Manufacturing Engineering 172
Countries citing papers authored by Xiang Bai
This map shows the geographic impact of Xiang Bai'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 Xiang Bai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiang Bai more than expected).
Fields of papers citing papers by Xiang Bai
This network shows the impact of papers produced by Xiang Bai. 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 Xiang Bai. The network helps show where Xiang Bai may publish in the future.
Co-authorship network of co-authors of Xiang Bai
This figure shows the co-authorship network connecting the top 25 collaborators of Xiang Bai. A scholar is included among the top collaborators of Xiang Bai 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 Xiang Bai. Xiang Bai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 8 | |
| 5 | 12 | |
| 6 | 8 | |
| 7 | Richer Convolutional Features for Edge Detectionbreakdown → | 498 |
| 8 | 289 | |
| 9 | 113 | |
| 10 | 2 | |
| 11 | 308 | |
| 12 | 29 | |
| 13 | 9 | |
| 14 | Richer Convolutional Features for Edge Detectionbreakdown → | 543 |
| 15 | DeepContour: A deep convolutional feature learned by positive-sharing loss for contour detectionbreakdown → | 351 |
| 16 | 8 | |
| 17 | 1 | |
| 18 | 1 | |
| 19 | 3 | |
| 20 | 1 |
About Xiang Bai
Xiang Bai is a scholar working on Fuel Technology, Computer Vision and Pattern Recognition and Media Technology, having authored 26 papers that have together received 2.3k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (9 papers), Advanced Neural Network Applications (6 papers) and Medical Image Segmentation Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.7k citations), Media Technology (478 citations) and Industrial and Manufacturing Engineering (172 citations). Xiang Bai has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Xinggang Wang, Xiaowei Hu, Yun Liu, Ming‐Ming Cheng, Wenyu Liu, Peng Tang, Wei Shen, Kai Wang, Jia-Wang Bian and Jinhui Tang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Fuel.
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.