Sanjay Kumar

1.6k citations
66 papers · 1.1k · 1 hit paper · h-index 16

Impact in

Papers in

Sanjay Kumar

59 papers receiving 935 citations

Sanjay Kumar's Hit Papers

Generative artificial intelligence: a systematic review and applications 2024 · 155 citations
1550+1Years since publication50100150

Peers

Sanjay Kumar
Comparison fields: 5 of 123
  • Health Informatics 27
  • Computer Vision and Pattern Recognition 408
  • Media Technology 85
  • Artificial Intelligence 215
  • Ocean Engineering 82
Replace Mona Jamjoom with:
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Kamil Dimililer Cyprus
Rafael M. Martins Sweden
Lei Huang China
Ciro Castiello Italy
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Sanjay Kumar relative to Mona Jamjoom Saudi Arabia Mona Jamjoom's profile →
Citations per field
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Countries citing papers authored by Sanjay Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Sanjay Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Generative artificial intelligence: a systematic review and applications
Hit paper breakdown →
2024155
2 200797
3 202189
4 202072
5 202069
6 200766
7 201649
8 202145
9 202038
10 201133
11 200929
12 202129
13 201624
14 201721
15 202119
16 201617
17 202414
18 202014
19 202413
20 202312

About Sanjay Kumar

Sanjay Kumar is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 66 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (15 papers), Chaos-based Image/Signal Encryption (12 papers), Digital Media Forensic Detection (9 papers), IoT-based Smart Home Systems (4 papers), User Authentication and Security Systems (4 papers), Digital Imaging for Blood Diseases (3 papers), Biometric Identification and Security (3 papers) and Artificial Intelligence in Healthcare (3 papers). The work is most often cited by research in Health Informatics (27 citations), Computer Vision and Pattern Recognition (408 citations), Media Technology (85 citations), Artificial Intelligence (215 citations) and Ocean Engineering (82 citations). Sanjay Kumar has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Binod Kumar Singh, Sandeep Singh Sengar, Fiona Carroll, S.K. Chaulya, Vinay Kumar, Mohit Yadav, B. Ishwar, Shashank Joshi, Rahul Gupta and Nitin Khanna. Their work appears in journals such as Multimedia Tools and Applications, Microelectronic Engineering, IEEE Transactions on Computational Social Systems, Analytical Methods and Biofuels.

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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