Keshav Kumar

641 citations
46 papers · 277 · h-index 10

Impact in

Papers in

Keshav Kumar

39 papers receiving 262 citations

Peers

Keshav Kumar
Comparison fields: 5 of 64
  • Hardware and Architecture 70
  • Computer Vision and Pattern Recognition 79
  • Artificial Intelligence 88
  • Signal Processing 24
  • Information Systems 38
Replace Husheng Zhou with:
Husheng Zhou United States
Henry Selvaraj United States
Weijia Wang China
Yujing Feng China
Sharad Sinha India
Vicent Sanz Marco United Kingdom
Christoph Ruland Germany
E. M. Saad Egypt
Keshav Kumar relative to Husheng Zhou United States Husheng Zhou's profile →
Citations per field
00.5×1.5×1.8×
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Citations per year

Countries citing papers authored by Keshav Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Keshav Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202242
2 202235
3 202023
4 202020
5 202219
6 201814
7 202112
8 202012
9 201911
10 20209
11 20219
12 20188
13 20236
14 20206
15 20194
16 20194
17 20193
18
IDENTIFICATION OF AYURVEDIC MEDICINAL LEAVES USING DEEP LEARNING
20213
19 20223
20 20193

About Keshav Kumar

Keshav Kumar is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture, Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 46 papers that have together received 277 indexed citations. Recurring topics across this work include Cryptographic Implementations and Security (9 papers), Physical Unclonable Functions (PUFs) and Hardware Security (9 papers), Embedded Systems and FPGA Applications (8 papers), Chaos-based Image/Signal Encryption (8 papers), Embedded Systems Design Techniques (7 papers), Low-power high-performance VLSI design (6 papers), Embedded Systems and FPGA Design (5 papers) and Energy Harvesting in Wireless Networks (5 papers). The work is most often cited by research in Hardware and Architecture (70 citations), Computer Vision and Pattern Recognition (79 citations), Artificial Intelligence (88 citations), Signal Processing (24 citations) and Information Systems (38 citations). Keshav Kumar has collaborated with scholars based in India, Denmark and Malaysia. Frequent co-authors include Amanpreet Kaur, K. R. Ramkumar, Bishwajeet Pandey, Anurag Shrivastava, Hamza Mohammed Ridha Al‐Khafaji, Smita Sharma, Surya Narayan Panda, Vikas Tripathi, Deepika Arora and Poonam Jindal. Their work appears in journals such as Electronics, Vacuum, Journal of King Saud University - Computer and Information Sciences, Wireless Communications and Mobile Computing and International Journal of Information Technology.

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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