Moumita Roy

507 citations
37 papers · 329 · h-index 11

Impact in

Papers in

    • Remote-Sensing Image Classification 21
    • Domain Adaptation and Few-Shot Learning 4
    • Text and Document Classification Technologies 3
    • Neural Networks and Applications 2
    • Imbalanced Data Classification Techniques 2

Moumita Roy

34 papers receiving 312 citations

Peers

Moumita Roy
Comparison fields: 5 of 68
  • Media Technology 169
  • Atmospheric Science 112
  • Artificial Intelligence 119
  • Ecology 76
  • Computer Vision and Pattern Recognition 60
Replace Mohamed Farah with:
Mohamed Farah Tunisia
Xiangming Jiang China
Xiang Tan China
Noureddine Ghoggali Italy
Junzheng Wu China
Fenlong Jiang China
Yufei Yang China
Hüseyin Fırat Türkiye
Moumita Roy relative to Mohamed Farah Tunisia Mohamed Farah's profile →
Citations per field
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Mohamed Farah · 1×
Citations per year

Countries citing papers authored by Moumita Roy

Since Specialization
Citations

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

Fields of papers citing papers by Moumita Roy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Moumita Roy. 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 Moumita Roy. The network helps show where Moumita Roy may publish in the future.

Co-authors

The 14 scholars most cited alongside Moumita Roy, 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 Moumita Roy Line = papers co-authored together Moumita Roy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201456
2 201354
3 202331
4 201525
5 202021
6 201418
7 201717
8 201517
9 202112
10 201312
11 202210
12 20197
13 20227
14 20124
15
Empirical Study of Different Classifiers for Sentiment Analysis
20143
16 20223
17 20193
18 20133
19 20203
20 20252

About Moumita Roy

Moumita Roy is a scholar working on Media Technology, Artificial Intelligence, Atmospheric Science, Ecology and Analytical Chemistry, having authored 37 papers that have together received 329 indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (21 papers), Remote Sensing and Land Use (14 papers), Spectroscopy and Chemometric Analyses (7 papers), Remote Sensing in Agriculture (7 papers), Domain Adaptation and Few-Shot Learning (4 papers), Text and Document Classification Technologies (3 papers), Neural Networks and Applications (2 papers) and Imbalanced Data Classification Techniques (2 papers). The work is most often cited by research in Media Technology (169 citations), Atmospheric Science (112 citations), Artificial Intelligence (119 citations), Ecology (76 citations) and Computer Vision and Pattern Recognition (60 citations). Moumita Roy has collaborated with scholars based in India, United States and Italy. Frequent co-authors include Susmita Ghosh, Ashish Ghosh, Anindya Halder, Utpal Biswas, Asit Kumar Das, Soumi Dutta, Saptarshi Ghosh, Farid Melgani, Enrico Blanzieri and B.B. Chaudhuri. Their work appears in journals such as IEEE Geoscience and Remote Sensing Letters, Applied Soft Computing, Information Sciences, Engineering Applications of Artificial Intelligence and IEEE Journal of Selected Topics in Applied Earth Observations 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.

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