Rik Das

566 citations
56 papers · 341 · h-index 10

Impact in

    • Image Retrieval and Classification Techniques
    • Advanced Image and Video Retrieval Techniques
    • Digital Imaging for Blood Diseases
    • Video Analysis and Summarization
    • Face and Expression Recognition
    • Remote-Sensing Image Classification

Papers in

Rik Das

52 papers receiving 298 citations

Peers

Rik Das
Comparison fields: 5 of 77
  • Computer Vision and Pattern Recognition 180
  • Media Technology 70
  • Health Informatics 4
  • Artificial Intelligence 86
  • Signal Processing 21
Replace Qiyu Jin with:
Qiyu Jin China
Jiqing Wu Switzerland
Wei‐Chung Lin United States
I.A. Esquef Brazil
S. R. Bhadra Chaudhuri India
Junying Zeng China
Yukun Huang China
Célia A. Zorzo Barcelos Brazil
Yuxi Wang China
Abd El–Naser A. Mohamed Egypt
Rik Das relative to Qiyu Jin China Qiyu Jin's profile →
Citations per field
00.5×8.7×
Qiyu Jin · 1×
Citations per year

Countries citing papers authored by Rik Das

Since Specialization
Citations

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

Fields of papers citing papers by Rik Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Rik Das, 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 Rik Das Line = papers co-authored together Rik Das links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201328
2 201421
3 202218
4 198816
5 201716
6 200415
7 200514
8 201612
9 201212
10 202011
11 20149
12 20129
13 20139
14 20218
15 20158
16 20167
17 20157
18 20027
19 20237
20 20226

About Rik Das

Rik Das is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Electrical and Electronic Engineering and Atomic and Molecular Physics, and Optics, having authored 56 papers that have together received 341 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (21 papers), Advanced Image and Video Retrieval Techniques (17 papers), Remote-Sensing Image Classification (11 papers), AI in cancer detection (7 papers), Face and Expression Recognition (4 papers), Semiconductor Quantum Structures and Devices (4 papers), COVID-19 diagnosis using AI (4 papers) and Digital Imaging for Blood Diseases (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (180 citations), Media Technology (70 citations), Health Informatics (4 citations), Artificial Intelligence (86 citations) and Signal Processing (21 citations). Rik Das has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Sudeep D. Thepade, Saurav Ghosh, G. S. Tripathi, Ekta Walia, H. B. Kekre, P. K. Misra, Sanjubala Sahoo, Ajay Kumar Shrivastava, B. Ishwar and S. K. Setua. Their work appears in journals such as Journal of Physics and Chemistry of Solids, Semiconductor Science and Technology, ETRI Journal, SpringerPlus and Celestial Mechanics and Dynamical Astronomy.

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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