Robinson Piramuthu
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 5%
- Media Technology top 5%
- Radiology, Nuclear Medicine and Imaging
- Computational Mechanics top 10%
- Co-authors
- Di WeiVignesh JagadeeshDennis DeCosteHao ZhangZhicheng YanYizhou YuQiaosong WangAnurag Bhardwaj
- Topics
- Advanced Image and Video Retrieval Techniques (10 papers)Image Retrieval and Classification Techniques (6 papers)Multimodal Machine Learning Applications (6 papers)
- Journals
- IEEE Transactions on Information TheoryComputer Vision and Image UnderstandingThe HKU Scholars Hub (University of Hong Kong)
- Partner nations
- United StatesIrelandGermany
In The Last Decade
Robinson Piramuthu
26 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 124
- Computer Vision and Pattern Recognition 907
- Artificial Intelligence 424
- Media Technology 115
- Radiology, Nuclear Medicine and Imaging 86
- Computational Mechanics 65
Countries citing papers authored by Robinson Piramuthu
This map shows the geographic impact of Robinson Piramuthu'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 Robinson Piramuthu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robinson Piramuthu more than expected).
Fields of papers citing papers by Robinson Piramuthu
This network shows the impact of papers produced by Robinson Piramuthu. 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 Robinson Piramuthu. The network helps show where Robinson Piramuthu may publish in the future.
Co-authorship network of co-authors of Robinson Piramuthu
This figure shows the co-authorship network connecting the top 25 collaborators of Robinson Piramuthu. A scholar is included among the top collaborators of Robinson Piramuthu 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 Robinson Piramuthu. Robinson Piramuthu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 6 | |
| 6 | 7 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 7 | |
| 10 | 63 | |
| 11 | 80 | |
| 12 | 3 | |
| 13 | HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognitionbreakdown → | 482 |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 22 | |
| 17 | 13 | |
| 18 | 89 | |
| 19 | 11 | |
| 20 | 4 |
About Robinson Piramuthu
Robinson Piramuthu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Sensory Systems, having authored 26 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (10 papers), Image Retrieval and Classification Techniques (6 papers) and Multimodal Machine Learning Applications (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (907 citations), Artificial Intelligence (424 citations) and Media Technology (115 citations). Robinson Piramuthu has collaborated with scholars based in United States, Ireland and Germany. Frequent co-authors include Di Wei, Vignesh Jagadeesh, Dennis DeCoste, Hao Zhang, Zhicheng Yan, Yizhou Yu, Qiaosong Wang, Anurag Bhardwaj, Neel Sundaresan and Ming–Hsuan Yang. Their work appears in journals such as IEEE Transactions on Information Theory, Computer Vision and Image Understanding and The HKU Scholars Hub (University of Hong Kong).
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.