Vikram Jain

17 papers receiving 253 citations

Peers

Vikram Jain
Comparison fields: 5 of 39
  • Hardware and Architecture 70
  • Computer Vision and Pattern Recognition 83
  • Computational Mathematics 2
  • Electrical and Electronic Engineering 169
  • Computer Networks and Communications 66
Replace Linyan Mei with:
Linyan Mei Belgium
Weinan Song United States
Jon J. Pimentel United States
Joonho Song South Korea
Infall Syafalni Indonesia
Guy Boudoukh Israel
Haoran Li Hong Kong
Wenming Li China
Vikram Jain relative to Linyan Mei Belgium Linyan Mei's profile →
Citations per field
00.5×1.5×
Linyan Mei · 1×
Citations per year

Countries citing papers authored by Vikram Jain

Since Specialization
Citations

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

Fields of papers citing papers by Vikram Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202178
2 202249
3 202239
4 202326
5 202214
6
Survey on Recent Clustering Algorithms in Wireless Sensor Networks
201312
7 20219
8 20117
9 20217
10 20195
11 20074
12 20243
13 20193
14
Survey of Adaptive On Demand Distance Vector Learning Protocol (AODV)
20132
15 20232
16 20112
17 20111
18 20211
19 20240
20 20250

About Vikram Jain

Vikram Jain is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Computer Vision and Pattern Recognition, Hardware and Architecture and Media Technology, having authored 23 papers that have together received 264 indexed citations. Recurring topics across this work include CCD and CMOS Imaging Sensors (7 papers), Advanced Memory and Neural Computing (7 papers), Parallel Computing and Optimization Techniques (4 papers), Mobile Ad Hoc Networks (4 papers), Advanced Neural Network Applications (4 papers), Image Processing Techniques and Applications (3 papers), Advanced Optical Network Technologies (2 papers) and Energy Efficient Wireless Sensor Networks (2 papers). The work is most often cited by research in Hardware and Architecture (70 citations), Computer Vision and Pattern Recognition (83 citations), Computational Mathematics (2 citations), Electrical and Electronic Engineering (169 citations) and Computer Networks and Communications (66 citations). Vikram Jain has collaborated with scholars based in Belgium, United States and India. Frequent co-authors include Marian Verhelst, Juan Sebastian Piedrahita Giraldo, Linyan Mei, Ioannis A. Papistas, Debjyoti Bhattacharjee, Arindam Mallik, Diederik Verkest, Qilin Zheng, Kodai Ueyoshi and Peter Debacker. Their work appears in journals such as IEEE Journal of Solid-State Circuits, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, IEEE Transactions on Computers, IEEE Transactions on Circuits and Systems I Regular Papers and Journal of Real-Time Image Processing.

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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