Neerendra Kumar

31 papers receiving 190 citations

Peers

Neerendra Kumar
Comparison fields: 5 of 37
  • Computer Vision and Pattern Recognition 84
  • Computer Networks and Communications 83
  • Signal Processing 34
  • Control and Systems Engineering 46
  • Information Systems 30
Replace Pradeep B. Mane with:
Pradeep B. Mane India
Michel Kulhandjian United States
Zhemin Duan China
Dong-Wook Lee South Korea
Kazi Kutubuddin Sayyad Liyakat India
Syed Rizwan Hassan Pakistan
Steven M. Hernandez United States
Longzhe Han China
Khaled Matrouk Jordan
Jens Hagemeyer Germany
Neerendra Kumar relative to Pradeep B. Mane India Pradeep B. Mane's profile →
Citations per field
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Pradeep B. Mane · 1×
Citations per year

Countries citing papers authored by Neerendra Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Neerendra Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Neerendra 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 Neerendra Kumar Line = papers co-authored together Neerendra Kumar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202224
2 202222
3 202221
4 201716
5 202411
6 201611
7 202410
8 20239
9 20196
10 20226
11 20186
12 20166
13 20166
14 20255
15 20184
16 20214
17 20184
18 20253
19 20233
20 20222

About Neerendra Kumar

Neerendra Kumar is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Control and Systems Engineering, Artificial Intelligence and Signal Processing, having authored 35 papers that have together received 194 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (11 papers), Network Security and Intrusion Detection (8 papers), Advanced Malware Detection Techniques (8 papers), Robotics and Sensor-Based Localization (6 papers), Anomaly Detection Techniques and Applications (5 papers), Robotics and Automated Systems (5 papers), Control and Dynamics of Mobile Robots (5 papers) and IoT and Edge/Fog Computing (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (84 citations), Computer Networks and Communications (83 citations), Signal Processing (34 citations), Control and Systems Engineering (46 citations) and Information Systems (30 citations). Neerendra Kumar has collaborated with scholars based in India, Hungary and Romania. Frequent co-authors include Zoltán Vámossy, Chaman Verma, Maria Simona Raboacă, Zoltán Illés, Márta Takács, Veronika Stoffová, Arpit Jain, George Suciu, Parul Parihar and Yashwant Singh. Their work appears in journals such as Karbala International Journal of Modern Science, Alexandria Engineering Journal, IEEE Access, Journal of King Saud University - Computer and Information Sciences and International Journal of Information Security.

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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