T.M. Rath
Impact in
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- Handwritten Text Recognition Techniques
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Image Processing and 3D Reconstruction
- Signal Processing top 5%
- Time Series Analysis and Forecasting
- Music and Audio Processing
Papers in
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- Handwritten Text Recognition Techniques 5
- Advanced Image and Video Retrieval Techniques 2
- Video Analysis and Summarization 2
- Image Processing and 3D Reconstruction 1
- Advanced Vision and Imaging 1
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- Natural Language Processing Techniques 4
- Co-authors
- R. Manmatha (6 shared papers)Victor Lavrenko (1 shared paper)Fan Feng (1 shared paper)Eric Partridge (1 shared paper)Hans-Hellmut Nagel (1 shared paper)Surya Narayan Panda (1 shared paper)
- Journals
- International Journal on Document Analysis and Recognition (IJDAR) (1 paper)Acta Horticulturae (1 paper)International Journal of Science and Research (IJSR) (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
T.M. Rath
8 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 87
- Computer Vision and Pattern Recognition 827
- Signal Processing 205
- Artificial Intelligence 448
- Media Technology 89
- Human-Computer Interaction 26
Countries citing papers authored by T.M. Rath
This map shows the geographic impact of T.M. Rath'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 T.M. Rath with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T.M. Rath more than expected).
Fields of papers citing papers by T.M. Rath
This network shows the impact of papers produced by T.M. Rath. 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 T.M. Rath. The network helps show where T.M. Rath may publish in the future.
Co-authors
The 6 scholars most cited alongside T.M. Rath, 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 | 2003 | 401 | |
| 2 | 2006 | 221 | |
| 3 | 2004 | 153 | |
| 4 | 2004 | 133 | |
| 5 | 2001 | 126 | |
| 6 | Indexing for a Digital Library of George Washington’s Manuscripts: A Study of Word Matching Techniques | 2002 | 24 |
| 7 | 2005 | 15 | |
| 8 | 2003 | 11 | |
| 9 | 2025 | 2 |
About T.M. Rath
T.M. Rath is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Automotive Engineering and Computational Theory and Mathematics, having authored 9 papers that have together received 1.1k indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (5 papers), Natural Language Processing Techniques (4 papers), Advanced Image and Video Retrieval Techniques (2 papers), Video Analysis and Summarization (2 papers), Image Processing and 3D Reconstruction (1 paper), Data Management and Algorithms (1 paper), Autonomous Vehicle Technology and Safety (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (827 citations), Signal Processing (205 citations), Artificial Intelligence (448 citations), Media Technology (89 citations) and Human-Computer Interaction (26 citations). T.M. Rath has collaborated with scholars based in United States and Germany. Frequent co-authors include R. Manmatha, Victor Lavrenko, Fan Feng, Eric Partridge, Hans-Hellmut Nagel and Surya Narayan Panda. Their work appears in journals such as International Journal on Document Analysis and Recognition (IJDAR), Acta Horticulturae and International Journal of Science and Research (IJSR).
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.