Roshan Fernandes
- Artificial Intelligence top 10%
- Oncology
- Computer Vision and Pattern Recognition top 10%
- Epidemiology
- Information Systems
- Co-authors
- Anisha P RodriguesSweta BhattacharyaRajeswari ChengodenKuruva LakshmannaP. VijayaMufti MahmudM. Shamim KaiserNiranjan N. Chiplunkar
- Topics
- Sentiment Analysis and Opinion Mining (4 papers)Handwritten Text Recognition Techniques (4 papers)Vehicle License Plate Recognition (3 papers)
- Journals
- Scientific ReportsIEEE AccessSensors
In The Last Decade
Roshan Fernandes
28 papers receiving 239 citations
Hit Papers
Peers
Comparison fields: 5 of 76
- Artificial Intelligence 117
- Oncology 103
- Computer Vision and Pattern Recognition 70
- Epidemiology 41
- Information Systems 27
Countries citing papers authored by Roshan Fernandes
This map shows the geographic impact of Roshan Fernandes'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 Roshan Fernandes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roshan Fernandes more than expected).
Fields of papers citing papers by Roshan Fernandes
This network shows the impact of papers produced by Roshan Fernandes. 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 Roshan Fernandes. The network helps show where Roshan Fernandes may publish in the future.
Co-authorship network of co-authors of Roshan Fernandes
This figure shows the co-authorship network connecting the top 25 collaborators of Roshan Fernandes. A scholar is included among the top collaborators of Roshan Fernandes 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 Roshan Fernandes. Roshan Fernandes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 5 | |
| 11 | Skin lesion classification of dermoscopic images using machine learning and convolutional neural networkbreakdown → | 126 |
| 12 | 3 | |
| 13 | 2 | |
| 14 | 6 | |
| 15 | 2 | |
| 16 | 10 | |
| 17 | 4 | |
| 18 | 3 | |
| 19 | 12 | |
| 20 | 1 |
About Roshan Fernandes
Roshan Fernandes is a scholar working on Computer Vision and Pattern Recognition, Transportation and Artificial Intelligence, having authored 33 papers that have together received 267 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (4 papers), Handwritten Text Recognition Techniques (4 papers) and Vehicle License Plate Recognition (3 papers). The work is most often cited by research in Oncology (103 citations), Artificial Intelligence (117 citations) and Computer Vision and Pattern Recognition (70 citations). Roshan Fernandes has collaborated with scholars based in India, Oman and Lebanon. Frequent co-authors include Anisha P Rodrigues, Sweta Bhattacharya, Rajeswari Chengoden, Kuruva Lakshmanna, P. Vijaya, Mufti Mahmud, M. Shamim Kaiser, Niranjan N. Chiplunkar, Thippa Reddy Gadekallu and Maheswari Raja. Their work appears in journals such as Scientific Reports, IEEE Access and Sensors.
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.