Vikas Tripathi

1.8k citations
141 papers · 826 · h-index 15

Impact in

Papers in

Vikas Tripathi

113 papers receiving 782 citations

Peers

Vikas Tripathi
Comparison fields: 5 of 137
  • Computer Vision and Pattern Recognition 198
  • Artificial Intelligence 189
  • Human-Computer Interaction 29
  • Health Informatics 7
  • Computer Networks and Communications 114
Replace Avinash Sharma with:
Avinash Sharma India
Meshal Alharbi Saudi Arabia
Georgios Tsaramirsis Saudi Arabia
Zeashan Hameed Khan Pakistan
Faisal Mehmood Pakistan
Anton Satria Prabuwono Malaysia
Hiram Pönce Mexico
Muhammad Islam Saudi Arabia
Hani Alquhayz Saudi Arabia
Vikas Tripathi relative to Avinash Sharma India Avinash Sharma's profile →
Citations per field
00.5×12×
Avinash Sharma · 1×
Citations per year

Countries citing papers authored by Vikas Tripathi

Since Specialization
Citations

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

Fields of papers citing papers by Vikas Tripathi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Vikas Tripathi, 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 Vikas Tripathi Line = papers co-authored together Vikas Tripathi 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 202060
2 202251
3 202042
4 202235
5 201633
6 202131
7 202230
8 202226
9 202322
10 202122
11 202322
12 202222
13 202222
14 202319
15 202117
16 202314
17 201514
18 202213
19 202211
20 202211

About Vikas Tripathi

Vikas Tripathi is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Information Systems, Artificial Intelligence and Electrical and Electronic Engineering, having authored 141 papers that have together received 826 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (18 papers), Internet of Things and AI (13 papers), Video Surveillance and Tracking Methods (12 papers), Anomaly Detection Techniques and Applications (11 papers), Blockchain Technology Applications and Security (10 papers), Network Security and Intrusion Detection (9 papers), COVID-19 diagnosis using AI (8 papers) and Human Pose and Action Recognition (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (198 citations), Artificial Intelligence (189 citations), Human-Computer Interaction (29 citations), Health Informatics (7 citations) and Computer Networks and Communications (114 citations). Vikas Tripathi has collaborated with scholars based in India, Saudi Arabia and Singapore. Frequent co-authors include Durgaprasad Gangodkar, Prabhdeep Singh, Ankush Mittal, Manoj Diwakar, Prabhishek Singh, Bhaskar Pant, Devvret Verma, Kumud Pant, Ashish Thapliyal and Rajneesh Sharma. Their work appears in journals such as Computational Intelligence and Neuroscience, Ecological Informatics, Energy Reports, Alexandria Engineering Journal and IEEE Transactions on Consumer Electronics.

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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