Minesh Mathew
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Media Technology top 5%
- Human-Computer Interaction top 10%
- Information Systems
- Co-authors
- C. V. JawaharDìmosthenis KaratzasKartik DuttaPraveen KrishnanMohit JainAjeet Kumar SinghErnest ValvenyMarçal Rusiñol
- Topics
- Handwritten Text Recognition Techniques (10 papers)Natural Language Processing Techniques (8 papers)Vehicle License Plate Recognition (4 papers)
- Journals
- 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
- Partner nations
- India
In The Last Decade
Minesh Mathew
13 papers receiving 415 citations
Peers
Comparison fields: 5 of 39
- Computer Vision and Pattern Recognition 372
- Artificial Intelligence 219
- Media Technology 110
- Human-Computer Interaction 30
- Information Systems 19
Countries citing papers authored by Minesh Mathew
This map shows the geographic impact of Minesh Mathew'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 Minesh Mathew with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minesh Mathew more than expected).
Fields of papers citing papers by Minesh Mathew
This network shows the impact of papers produced by Minesh Mathew. 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 Minesh Mathew. The network helps show where Minesh Mathew may publish in the future.
Co-authorship network of co-authors of Minesh Mathew
This figure shows the co-authorship network connecting the top 25 collaborators of Minesh Mathew. A scholar is included among the top collaborators of Minesh Mathew 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 Minesh Mathew. Minesh Mathew 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 | 43 | |
| 3 | 136 | |
| 4 | 20 | |
| 5 | 31 | |
| 6 | 13 | |
| 7 | 87 | |
| 8 | 12 | |
| 9 | 22 | |
| 10 | 2 | |
| 11 | 16 | |
| 12 | 30 | |
| 13 | 25 |
About Minesh Mathew
Minesh Mathew is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Media Technology, having authored 13 papers that have together received 440 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (10 papers), Natural Language Processing Techniques (8 papers) and Vehicle License Plate Recognition (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (372 citations), Media Technology (110 citations) and Artificial Intelligence (219 citations). Minesh Mathew has collaborated with scholars based in India. Frequent co-authors include C. V. Jawahar, Dìmosthenis Karatzas, Kartik Dutta, Praveen Krishnan, Mohit Jain, Ajeet Kumar Singh, Ernest Valveny, Marçal Rusiñol and Lluís Gómez. Their work appears in journals such as 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) and 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
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.