Sumit Kumar Basu

2.8k citations
71 papers · 1.9k · h-index 23

Impact in

Papers in

Sumit Kumar Basu

65 papers receiving 1.8k citations

Peers

Sumit Kumar Basu
Comparison fields: 5 of 138
  • Computer Science Applications 302
  • Computer Vision and Pattern Recognition 802
  • Signal Processing 369
  • Human-Computer Interaction 148
  • Artificial Intelligence 739
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Citations per year

Countries citing papers authored by Sumit Kumar Basu

Since Specialization
Citations

This map shows the geographic impact of Sumit Kumar Basu'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 Sumit Kumar Basu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumit Kumar Basu more than expected).

Fields of papers citing papers by Sumit Kumar Basu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sumit Kumar Basu. 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 Sumit Kumar Basu. The network helps show where Sumit Kumar Basu may publish in the future.

Co-authors

The 25 scholars most cited alongside Sumit Kumar Basu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sumit Kumar Basu Line = papers co-authored together Sumit Kumar Basu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Learning from the Wisdom of Crowds by Minimax Entropy
2012220
2 1996167
3 2013121
4 2008119
5 201595
6
Selective supervision: guiding supervised learning with decision-theoretic active learning
200786
7 200285
8 200475
9
Towards Measuring Human Interactions in Conversational Settings
200161
10
Learning Human Interactions with the Influence Model
200155
11 201350
12 201450
13 200349
14 201748
15 200346
16
Mind the Gap: Learning to Choose Gaps for Question Generation
201238
17 202038
18 200237
19 200236
20 201633

About Sumit Kumar Basu

Sumit Kumar Basu is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence, Radiation and Cognitive Neuroscience, having authored 71 papers that have together received 1.9k indexed citations. Recurring topics across this work include Speech and Audio Processing (15 papers), Music and Audio Processing (13 papers), Advanced Vision and Imaging (9 papers), Music Technology and Sound Studies (8 papers), Advanced Radiotherapy Techniques (6 papers), Machine Learning and Algorithms (5 papers), Topic Modeling (5 papers) and Radiation Therapy and Dosimetry (4 papers). The work is most often cited by research in Computer Science Applications (302 citations), Computer Vision and Pattern Recognition (802 citations), Signal Processing (369 citations), Human-Computer Interaction (148 citations) and Artificial Intelligence (739 citations). Sumit Kumar Basu has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Alex Pentland, Lucy Vanderwende, Irfan A. Essa, John C. Platt, Yi Mao, Dengyong Zhou, Dan Morris, Ian Simon, Tanzeem Choudhury and Brian Clarkson. Their work appears in journals such as Medical Physics, Physical review. D, The Journal of Clinical Pharmacology, Journal of Chromatography B and Optics Communications.

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.

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