Raghu Krishnapuram
- Artificial Intelligence top 0.2%
- Computer Vision and Pattern Recognition top 0.2%
- Signal Processing top 0.5%
- Information Systems top 0.5%
- Media Technology top 0.5%
- Co-authors
- James M. KellerHichem FriguiOlfa NasraouiRajesh N. DavéAnupam JoshiSwarup MedasaniJaeseok KimJoonwhoan Lee
- Topics
- Data Management and Algorithms (30 papers)Image Retrieval and Classification Techniques (24 papers)Advanced Clustering Algorithms Research (21 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingPattern Recognition
- Partner nations
- United StatesIndiaSouth Korea
In The Last Decade
Raghu Krishnapuram
114 papers receiving 6.0k citations
Hit Papers
Peers
Comparison fields: 5 of 161
- Artificial Intelligence 3.9k
- Computer Vision and Pattern Recognition 2.7k
- Signal Processing 1.2k
- Information Systems 860
- Media Technology 830
Countries citing papers authored by Raghu Krishnapuram
This map shows the geographic impact of Raghu Krishnapuram'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 Raghu Krishnapuram with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raghu Krishnapuram more than expected).
Fields of papers citing papers by Raghu Krishnapuram
This network shows the impact of papers produced by Raghu Krishnapuram. 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 Raghu Krishnapuram. The network helps show where Raghu Krishnapuram may publish in the future.
Co-authorship network of co-authors of Raghu Krishnapuram
This figure shows the co-authorship network connecting the top 25 collaborators of Raghu Krishnapuram. A scholar is included among the top collaborators of Raghu Krishnapuram 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 Raghu Krishnapuram. Raghu Krishnapuram is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 105 | |
| 6 | 1 | |
| 7 | 26 | |
| 8 | 1 | |
| 9 | 13 | |
| 10 | A comparison of Gaussian and Pearson mixture modeling for pattern recognition and computer vision applications | 2 |
| 11 | 351 | |
| 12 | 13 | |
| 13 | 238 | |
| 14 | 159 | |
| 15 | 1 | |
| 16 | 46 | |
| 17 | 18 | |
| 18 | A possibilistic approach to clusteringbreakdown → | 1720 |
| 19 | 131 | |
| 20 | 60 |
About Raghu Krishnapuram
Raghu Krishnapuram is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Media Technology, having authored 117 papers that have together received 6.6k indexed citations. Recurring topics across this work include Data Management and Algorithms (30 papers), Image Retrieval and Classification Techniques (24 papers) and Advanced Clustering Algorithms Research (21 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.7k citations), Artificial Intelligence (3.9k citations) and Signal Processing (1.2k citations). Raghu Krishnapuram has collaborated with scholars based in United States, India and South Korea. Frequent co-authors include James M. Keller, Hichem Frigui, Olfa Nasraoui, Rajesh N. Davé, Anupam Joshi, Swarup Medasani, Jaeseok Kim, Joonwhoan Lee, Jong Woo Kim and Krishna Kummamuru. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.
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.