Mausumi Acharyya
- Cognitive Neuroscience top 10%
- Computer Vision and Pattern Recognition top 5%
- Social Psychology top 10%
- Media Technology top 5%
- Artificial Intelligence
- Co-authors
- Malay K. KunduDinggang ShenYong FanJames LougheadChristos DavatzikosDaniel D. LanglebenRuben C. GurKosha Ruparel
- Topics
- Image and Signal Denoising Methods (10 papers)Image Retrieval and Classification Techniques (5 papers)Medical Image Segmentation Techniques (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceNeuroImageIEEE Transactions on Geoscience and Remote Sensing
- Partner nations
- IndiaUnited States
In The Last Decade
Mausumi Acharyya
17 papers receiving 517 citations
Peers
Comparison fields: 5 of 79
- Cognitive Neuroscience 230
- Computer Vision and Pattern Recognition 204
- Social Psychology 102
- Media Technology 93
- Artificial Intelligence 84
Countries citing papers authored by Mausumi Acharyya
This map shows the geographic impact of Mausumi Acharyya'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 Mausumi Acharyya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mausumi Acharyya more than expected).
Fields of papers citing papers by Mausumi Acharyya
This network shows the impact of papers produced by Mausumi Acharyya. 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 Mausumi Acharyya. The network helps show where Mausumi Acharyya may publish in the future.
Co-authorship network of co-authors of Mausumi Acharyya
This figure shows the co-authorship network connecting the top 25 collaborators of Mausumi Acharyya. A scholar is included among the top collaborators of Mausumi Acharyya 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 Mausumi Acharyya. Mausumi Acharyya 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 | 13 | |
| 3 | 12 | |
| 4 | 10 | |
| 5 | 13 | |
| 6 | 1 | |
| 7 | Image Segmentation Using Wavelet Packet Frames and Neuro-fuzzy Tools | 16 |
| 8 | 305 | |
| 9 | 39 | |
| 10 | 31 | |
| 11 | 24 | |
| 12 | 2 | |
| 13 | 14 | |
| 14 | 13 | |
| 15 | 43 | |
| 16 | 31 | |
| 17 | 1 |
About Mausumi Acharyya
Mausumi Acharyya is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Analytical Chemistry, having authored 17 papers that have together received 569 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (10 papers), Image Retrieval and Classification Techniques (5 papers) and Medical Image Segmentation Techniques (4 papers). The work is most often cited by research in Cognitive Neuroscience (230 citations), Media Technology (93 citations) and Computer Vision and Pattern Recognition (204 citations). Mausumi Acharyya has collaborated with scholars based in India and United States. Frequent co-authors include Malay K. Kundu, Dinggang Shen, Yong Fan, James Loughead, Christos Davatzikos, Daniel D. Langleben, Ruben C. Gur, Kosha Ruparel, Rajat K. De and Pragnya Maduskar. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, NeuroImage and IEEE Transactions on Geoscience and Remote Sensing.
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.