Tsang Ing Ren
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 2%
- Radiology, Nuclear Medicine and Imaging top 10%
- Media Technology top 2%
- Signal Processing top 5%
- Co-authors
- George D. C. CavalcantiRafael M. O. CruzRobert SabourinM. A. F. GomesJan SijbersVinícius M. MelloViviane M. de OliveiraBruno Fernandes
- Topics
- Face and Expression Recognition (23 papers)Image Retrieval and Classification Techniques (16 papers)Neural Networks and Applications (13 papers)
- Partner nations
- BrazilBelgiumUnited States
In The Last Decade
Tsang Ing Ren
114 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 166
- Computer Vision and Pattern Recognition 588
- Artificial Intelligence 518
- Radiology, Nuclear Medicine and Imaging 164
- Media Technology 140
- Signal Processing 135
Countries citing papers authored by Tsang Ing Ren
This map shows the geographic impact of Tsang Ing Ren'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 Tsang Ing Ren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tsang Ing Ren more than expected).
Fields of papers citing papers by Tsang Ing Ren
This network shows the impact of papers produced by Tsang Ing Ren. 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 Tsang Ing Ren. The network helps show where Tsang Ing Ren may publish in the future.
Co-authorship network of co-authors of Tsang Ing Ren
This figure shows the co-authorship network connecting the top 25 collaborators of Tsang Ing Ren. A scholar is included among the top collaborators of Tsang Ing Ren 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 Tsang Ing Ren. Tsang Ing Ren is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 17 | |
| 3 | J Regularization Improves Imbalanced Multiclass Segmentation | 12 |
| 4 | Isotropy Maximization Loss and Entropic Score: Accurate, Fast, Efficient, Scalable, and Turnkey Neural Networks Out-of-Distribution Detection Based on The Principle of Maximum Entropy | 0 |
| 5 | 12 | |
| 6 | 4 | |
| 7 | 20 | |
| 8 | Principal Component Analysis for Supervised Learning: a minimum classification error approach | 3 |
| 9 | 6 | |
| 10 | 3 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | 17 | |
| 14 | 20 | |
| 15 | 15 | |
| 16 | 4 | |
| 17 | 4 | |
| 18 | 14 | |
| 19 | 0 | |
| 20 | 4 |
About Tsang Ing Ren
Tsang Ing Ren is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology, having authored 122 papers that have together received 1.5k indexed citations. Recurring topics across this work include Face and Expression Recognition (23 papers), Image Retrieval and Classification Techniques (16 papers) and Neural Networks and Applications (13 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (588 citations), Artificial Intelligence (518 citations) and Media Technology (140 citations). Tsang Ing Ren has collaborated with scholars based in Brazil, Belgium and United States. Frequent co-authors include George D. C. Cavalcanti, Rafael M. O. Cruz, Robert Sabourin, M. A. F. Gomes, Jan Sijbers, Vinícius M. Mello, Viviane M. de Oliveira, Bruno Fernandes, Fidel A. Guerrero Peña and Giovani L. Vasconcelos. Their work appears in journals such as PLoS ONE, IEEE Transactions on Image Processing and Expert Systems with Applications.
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.