Amitabha Chakrabarty
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Plant Science
- Information Systems top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Md. Jalil PiranMamoun AlazabThippa Reddy GadekalluSamiul IslamMartin CollierSumit DuttaAmitabha DeyYong Ju Jung
- Topics
- Smart Agriculture and AI (10 papers)Caching and Content Delivery (10 papers)IoT and Edge/Fog Computing (9 papers)
- Journals
- Scientific ReportsIEEE AccessSensors
- Partner nations
- BangladeshSouth KoreaIreland
In The Last Decade
Amitabha Chakrabarty
80 papers receiving 724 citations
Hit Papers
Peers
Comparison fields: 5 of 123
- Artificial Intelligence 203
- Computer Vision and Pattern Recognition 132
- Plant Science 118
- Information Systems 117
- Computer Networks and Communications 99
Countries citing papers authored by Amitabha Chakrabarty
This map shows the geographic impact of Amitabha Chakrabarty'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 Amitabha Chakrabarty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amitabha Chakrabarty more than expected).
Fields of papers citing papers by Amitabha Chakrabarty
This network shows the impact of papers produced by Amitabha Chakrabarty. 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 Amitabha Chakrabarty. The network helps show where Amitabha Chakrabarty may publish in the future.
Co-authorship network of co-authors of Amitabha Chakrabarty
This figure shows the co-authorship network connecting the top 25 collaborators of Amitabha Chakrabarty. A scholar is included among the top collaborators of Amitabha Chakrabarty 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 Amitabha Chakrabarty. Amitabha Chakrabarty 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 | 7 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 9 | |
| 7 | Vision Transformers, Ensemble Model, and Transfer Learning Leveraging Explainable AI for Brain Tumor Detection and Classificationbreakdown → | 122 |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 22 | |
| 11 | 1 | |
| 12 | 8 | |
| 13 | 3 | |
| 14 | 1 | |
| 15 | 11 | |
| 16 | 16 | |
| 17 | 39 | |
| 18 | 42 | |
| 19 | 31 | |
| 20 | 15 |
About Amitabha Chakrabarty
Amitabha Chakrabarty is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Health Informatics, having authored 85 papers that have together received 760 indexed citations. Recurring topics across this work include Smart Agriculture and AI (10 papers), Caching and Content Delivery (10 papers) and IoT and Edge/Fog Computing (9 papers). The work is most often cited by research in Neurology (95 citations), Signal Processing (73 citations) and Computer Vision and Pattern Recognition (132 citations). Amitabha Chakrabarty has collaborated with scholars based in Bangladesh, South Korea and Ireland. Frequent co-authors include Md. Jalil Piran, Mamoun Alazab, Thippa Reddy Gadekallu, Samiul Islam, Martin Collier, Sumit Dutta, Amitabha Dey, Yong Ju Jung, Md Tanzim Reza and Syed Mahfuzul Aziz. 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.