Suman K. Ghosh
- Computer Vision and Pattern Recognition top 1%
- Media Technology top 1%
- Artificial Intelligence top 10%
- Human-Computer Interaction
- Information Systems
- Co-authors
- Ernest ValvenyDìmosthenis KaratzasLluís GómezSeiichi UchidaFaisal ShafaitVijay ChandrasekharMasakazu IwamuraShijian Lu
- Topics
- Handwritten Text Recognition Techniques (6 papers)Advanced Image and Video Retrieval Techniques (3 papers)Image Retrieval and Classification Techniques (2 papers)
- Journals
- Pattern Recognition LettersInternational Journal on Document Analysis and Recognition (IJDAR)Florence Research (University of Florence)
In The Last Decade
Suman K. Ghosh
7 papers receiving 895 citations
Hit Papers
Peers
Comparison fields: 5 of 39
- Computer Vision and Pattern Recognition 892
- Media Technology 436
- Artificial Intelligence 195
- Human-Computer Interaction 24
- Information Systems 23
Countries citing papers authored by Suman K. Ghosh
This map shows the geographic impact of Suman K. Ghosh'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 Suman K. Ghosh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suman K. Ghosh more than expected).
Fields of papers citing papers by Suman K. Ghosh
This network shows the impact of papers produced by Suman K. Ghosh. 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 Suman K. Ghosh. The network helps show where Suman K. Ghosh may publish in the future.
Co-authorship network of co-authors of Suman K. Ghosh
This figure shows the co-authorship network connecting the top 25 collaborators of Suman K. Ghosh. A scholar is included among the top collaborators of Suman K. Ghosh 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 Suman K. Ghosh. Suman K. Ghosh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 4 | |
| 3 | ICDAR 2015 competition on Robust Readingbreakdown → | 874 |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 33 | |
| 7 | 2 |
About Suman K. Ghosh
Suman K. Ghosh is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Media Technology, having authored 7 papers that have together received 937 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (6 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Image Retrieval and Classification Techniques (2 papers). The work is most often cited by research in Media Technology (436 citations), Computer Vision and Pattern Recognition (892 citations) and Artificial Intelligence (195 citations). Suman K. Ghosh has collaborated with scholars based in India, Spain and Czechia. Frequent co-authors include Ernest Valveny, Dìmosthenis Karatzas, Lluís Gómez, Seiichi Uchida, Faisal Shafait, Vijay Chandrasekhar, Masakazu Iwamura, Shijian Lu, Anguelos Nicolaou and Andrew D. Bagdanov. Their work appears in journals such as Pattern Recognition Letters, International Journal on Document Analysis and Recognition (IJDAR) and Florence Research (University of Florence).
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.