Pradipta Maji
- Computational Theory and Mathematics top 0.5%
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Molecular Biology
- Information Systems top 2%
- Co-authors
- Sankar K. PalAbhirup BanerjeeSushmita PaulP.P. ChaudhuriNiloy GangulyMalay K. KunduBiplab K. SikdarChandra Das
- Topics
- Rough Sets and Fuzzy Logic (32 papers)Gene expression and cancer classification (26 papers)Medical Image Segmentation Techniques (20 papers)
- Cited by
- Computational Theory and MathematicsComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- PLoS ONEIEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image Processing
- Partner nations
- IndiaGermanyUnited Kingdom
In The Last Decade
Pradipta Maji
107 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 112
- Computational Theory and Mathematics 850
- Artificial Intelligence 746
- Computer Vision and Pattern Recognition 653
- Molecular Biology 471
- Information Systems 350
Countries citing papers authored by Pradipta Maji
This map shows the geographic impact of Pradipta Maji'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 Pradipta Maji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pradipta Maji more than expected).
Fields of papers citing papers by Pradipta Maji
This network shows the impact of papers produced by Pradipta Maji. 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 Pradipta Maji. The network helps show where Pradipta Maji may publish in the future.
Co-authorship network of co-authors of Pradipta Maji
This figure shows the co-authorship network connecting the top 25 collaborators of Pradipta Maji. A scholar is included among the top collaborators of Pradipta Maji 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 Pradipta Maji. Pradipta Maji is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 3 | |
| 5 | 10 | |
| 6 | On Synthesis of Non-Uniform Cellular Automata Having Only Point Attractors. | 3 |
| 7 | 16 | |
| 8 | 10 | |
| 9 | 8 | |
| 10 | 93 | |
| 11 | 1 | |
| 12 | 61 | |
| 13 | 65 | |
| 14 | 42 | |
| 15 | 10 | |
| 16 | 99 | |
| 17 | 30 | |
| 18 | Fuzzy Cellular Automata for Modeling Pattern Classifier(Automata and Formal Language Theory) | 4 |
| 19 | 42 | |
| 20 | Application of Fuzzy Cellular Automata (FCA) For Modeling Tree-Structured Pattern Classifier. | 1 |
About Pradipta Maji
Pradipta Maji is a scholar working on Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Media Technology, having authored 112 papers that have together received 1.9k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (32 papers), Gene expression and cancer classification (26 papers) and Medical Image Segmentation Techniques (20 papers). The work is most often cited by research in Computational Theory and Mathematics (850 citations), Computer Vision and Pattern Recognition (653 citations) and Artificial Intelligence (746 citations). Pradipta Maji has collaborated with scholars based in India, Germany and United Kingdom. Frequent co-authors include Sankar K. Pal, Abhirup Banerjee, Sushmita Paul, P.P. Chaudhuri, Niloy Ganguly, Malay K. Kundu, Biplab K. Sikdar, Chandra Das, Minakshi Banerjee and Bhabatosh Chanda. Their work appears in journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.
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.