Sandeep Kumar

3.8k citations
141 papers · 2.0k · h-index 26

Impact in

Papers in

Sandeep Kumar

124 papers receiving 1.8k citations

Peers

Sandeep Kumar
Comparison fields: 5 of 138
  • Computer Vision and Pattern Recognition 544
  • Signal Processing 186
  • Neurology 115
  • Computer Networks and Communications 298
  • Artificial Intelligence 414
Replace Fahd N. Al‐Wesabi with:
Fahd N. Al‐Wesabi Saudi Arabia
B. D. Parameshachari India
K. Venkatachalam India
Hela Elmannai Saudi Arabia
Anwer Mustafa Hilal Saudi Arabia
Sultan S. Alshamrani Saudi Arabia
Ramgopal Kashyap India
Deepak Garg India
Rajesh Kumar Dhanaraj India
Ezz El‐Din Hemdan Egypt
Sandeep Kumar relative to Fahd N. Al‐Wesabi Saudi Arabia Fahd N. Al‐Wesabi's profile →
Citations per field
00.5×2×4×6×8.8×
Fahd N. Al‐Wesabi · 1×
Citations per year

Countries citing papers authored by Sandeep Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Sandeep Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 141 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2023110
2 202199
3 202398
4 201996
5 202276
6 202266
7 202065
8 202162
9 202254
10 201753
11 202249
12 202346
13 202244
14 202239
15 202236
16 201935
17 202132
18 201731
19 201830
20 201828

About Sandeep Kumar

Sandeep Kumar is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Information Systems, Artificial Intelligence and Media Technology, having authored 141 papers that have together received 2.0k indexed citations. Recurring topics across this work include Face recognition and analysis (16 papers), Smart Agriculture and AI (12 papers), Biometric Identification and Security (12 papers), Face and Expression Recognition (10 papers), Topic Modeling (9 papers), Video Surveillance and Tracking Methods (8 papers), Advanced Neural Network Applications (7 papers) and Blockchain Technology Applications and Security (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (544 citations), Signal Processing (186 citations), Neurology (115 citations), Computer Networks and Communications (298 citations) and Artificial Intelligence (414 citations). Sandeep Kumar has collaborated with scholars based in India, Saudi Arabia and United States. Frequent co-authors include Shilpa Rani, Arpit Kumar Jain, Sukhwinder Singh, Deepika Ghai, Narendra Khatri, Shilpa Choudhary, Aarti Aarti, MVV Prasad Kantipudi, Bhupesh Kumar Lad and Rohit Singh Raja. Their work appears in journals such as Multimedia Tools and Applications, Scientific African, Computational Intelligence and Neuroscience, Wireless Personal Communications and SAE technical papers on CD-ROM/SAE technical paper series.

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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