Subhankar Roy

1.3k citations
14 papers · 339 · h-index 9

Impact in

    • Advanced Image and Video Retrieval Techniques
    • Multimodal Machine Learning Applications
    • Image Retrieval and Classification Techniques
    • Advanced Neural Network Applications
    • Video Surveillance and Tracking Methods
    • Remote-Sensing Image Classification

Papers in

    • Multimodal Machine Learning Applications 7
    • Advanced Image and Video Retrieval Techniques 4
    • Advanced Neural Network Applications 4
    • Human Pose and Action Recognition 2
    • Image Retrieval and Classification Techniques 2
    • Domain Adaptation and Few-Shot Learning 10

Subhankar Roy

14 papers receiving 334 citations

Peers

Subhankar Roy
Comparison fields: 5 of 47
  • Computer Vision and Pattern Recognition 231
  • Media Technology 98
  • Artificial Intelligence 190
  • Atmospheric Science 23
  • Radiology, Nuclear Medicine and Imaging 28
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Citations per field
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Citations per year

Countries citing papers authored by Subhankar Roy

Since Specialization
Citations

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

Fields of papers citing papers by Subhankar Roy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Subhankar 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 Subhankar Roy Line = papers co-authored together Subhankar Roy links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 201989
2 202174
3 202061
4 201824
5 201822
6 202320
7 20249
8 20188
9 20238
10 20238
11 20237
12 20236
13 20242
14 20171

About Subhankar Roy

Subhankar Roy is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Cancer Research and Computer Networks and Communications, having authored 14 papers that have together received 339 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (10 papers), Multimodal Machine Learning Applications (7 papers), Remote-Sensing Image Classification (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Advanced Neural Network Applications (4 papers), Human Pose and Action Recognition (2 papers), Image Retrieval and Classification Techniques (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (231 citations), Media Technology (98 citations), Artificial Intelligence (190 citations), Atmospheric Science (23 citations) and Radiology, Nuclear Medicine and Imaging (28 citations). Subhankar Roy has collaborated with scholars based in Italy, France and Germany. Frequent co-authors include Nicu Sebe, Enver Sangineto, Elisa Ricci, Begüm Demir, Aliaksandr Siarohin, Samuel Rota Bulò, Zhun Zhong, Zhiming Luo, Enrico Fini and Stéphane Lathuilière. Their work appears in journals such as IEEE Geoscience and Remote Sensing Letters, Computer Vision and Image Understanding, International Journal of Grid and Distributed Computing, Aisberg (University of Bergamo) and SPIRE - Sciences Po Institutional REpository.

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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