Manosij Ghosh
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Electrical and Electronic Engineering
- Co-authors
- Ram SarkarRitam GuhaSeyedali MirjaliliMita NasipuriShemim BegumAjith AbrahamSamir MalakarShowmik Bhowmik
- Topics
- Evolutionary Algorithms and Applications (8 papers)Handwritten Text Recognition Techniques (7 papers)Metaheuristic Optimization Algorithms Research (7 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionComputational Theory and Mathematics
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsApplied Soft Computing
- Partner nations
- IndiaUnited StatesAustralia
In The Last Decade
Manosij Ghosh
21 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 121
- Artificial Intelligence 727
- Computer Vision and Pattern Recognition 368
- Molecular Biology 169
- Computational Theory and Mathematics 164
- Electrical and Electronic Engineering 76
Countries citing papers authored by Manosij Ghosh
This map shows the geographic impact of Manosij 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 Manosij Ghosh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manosij Ghosh more than expected).
Fields of papers citing papers by Manosij Ghosh
This network shows the impact of papers produced by Manosij 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 Manosij Ghosh. The network helps show where Manosij Ghosh may publish in the future.
Co-authorship network of co-authors of Manosij Ghosh
This figure shows the co-authorship network connecting the top 25 collaborators of Manosij Ghosh. A scholar is included among the top collaborators of Manosij 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 Manosij Ghosh. Manosij 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 | 8 | |
| 2 | 42 | |
| 3 | 17 | |
| 4 | 227 | |
| 5 | 59 | |
| 6 | 39 | |
| 7 | 3 | |
| 8 | 11 | |
| 9 | 45 | |
| 10 | 13 | |
| 11 | 43 | |
| 12 | 69 | |
| 13 | 13 | |
| 14 | 136 | |
| 15 | 20 | |
| 16 | 163 | |
| 17 | 35 | |
| 18 | 93 | |
| 19 | 103 | |
| 20 | 9 |
About Manosij Ghosh
Manosij Ghosh is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics, having authored 21 papers that have together received 1.2k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (8 papers), Handwritten Text Recognition Techniques (7 papers) and Metaheuristic Optimization Algorithms Research (7 papers). The work is most often cited by research in Artificial Intelligence (727 citations), Computer Vision and Pattern Recognition (368 citations) and Computational Theory and Mathematics (164 citations). Manosij Ghosh has collaborated with scholars based in India, United States and Australia. Frequent co-authors include Ram Sarkar, Ritam Guha, Seyedali Mirjalili, Mita Nasipuri, Shemim Begum, Ajith Abraham, Samir Malakar, Showmik Bhowmik, Kushal Kanti Ghosh and Ujjwal Maulik. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Applied Soft Computing.
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.