Ram Sarkar
Impact in
-
- Handwritten Text Recognition Techniques
- Media Technology top 0.2%
- Vehicle License Plate Recognition
Papers in
-
- Handwritten Text Recognition Techniques 118
- Image Retrieval and Classification Techniques 45
- Image Processing and 3D Reconstruction 30
-
- Vehicle License Plate Recognition 78
- Co-authors
- Pawan Kumar SinghMita NasipuriManosij GhoshSamir MalakarRohit KunduSeyedali MirjaliliSubhadip BasuZong Woo Geem
- Journals
- Multimedia Tools and Applications (41 papers)Neural Computing and Applications (22 papers)Expert Systems with Applications (19 papers)IEEE Access (14 papers)Scientific Reports (13 papers)
- Partner nations
- IndiaSouth KoreaMexico
In The Last Decade
Ram Sarkar
319 papers receiving 7.8k citations
Hit Papers
Peers
Comparison fields: 5 of 180
- Computer Vision and Pattern Recognition 3.9k
- Media Technology 1.3k
- Artificial Intelligence 3.8k
- Health Informatics 99
- Radiology, Nuclear Medicine and Imaging 1.4k
Countries citing papers authored by Ram Sarkar
This map shows the geographic impact of Ram Sarkar'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 Ram Sarkar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ram Sarkar more than expected).
Fields of papers citing papers by Ram Sarkar
This network shows the impact of papers produced by Ram Sarkar. 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 Ram Sarkar. The network helps show where Ram Sarkar may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ram Sarkar, 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 | 2024 | 11 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 4 | |
| 6 | 2023 | 15 | |
| 7 | 2023 | 22 | |
| 8 | 2023 | 18 | |
| 9 | 2022 | 9 | |
| 10 | 2021 | 33 | |
| 11 | 2021 | 8 | |
| 12 | 2021 | 83 | |
| 13 | 2020 | 42 | |
| 14 | 2020 | 17 | |
| 15 | 2019 | 13 | |
| 16 | 2019 | 43 | |
| 17 | 2019 | 69 | |
| 18 | 2018 | 93 | |
| 19 | Word extraction from unconstrained handwritten Bangla document images using Spiral Run Length Smearing Algorithm. | 2011 | 3 |
| 20 | Handwritten Bangla Compound character recognition: Potential challenges and probable solution. | 2009 | 12 |
About Ram Sarkar
Ram Sarkar is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Artificial Intelligence, Human-Computer Interaction and Health Informatics, having authored 330 papers that have together received 8.2k indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (118 papers), Vehicle License Plate Recognition (78 papers), Image Retrieval and Classification Techniques (45 papers), AI in cancer detection (40 papers), Metaheuristic Optimization Algorithms Research (31 papers), Image Processing and 3D Reconstruction (30 papers), COVID-19 diagnosis using AI (29 papers) and Anomaly Detection Techniques and Applications (27 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (3.9k citations), Media Technology (1.3k citations), Artificial Intelligence (3.8k citations), Health Informatics (99 citations) and Radiology, Nuclear Medicine and Imaging (1.4k citations). Ram Sarkar has collaborated with scholars based in India, South Korea and Mexico. Frequent co-authors include Pawan Kumar Singh, Mita Nasipuri, Manosij Ghosh, Samir Malakar, Rohit Kundu, Seyedali Mirjalili, Subhadip Basu, Zong Woo Geem, Kushal Kanti Ghosh and Nibaran Das. Their work appears in journals such as Multimedia Tools and Applications, Neural Computing and Applications, Expert Systems with Applications, IEEE Access and Scientific Reports.
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.