Arpit Jain

3.5k citations
100 papers · 1.5k · h-index 22

Impact in

Papers in

Arpit Jain

96 papers receiving 1.4k citations

Peers

Arpit Jain
Comparison fields: 5 of 120
  • Computer Vision and Pattern Recognition 320
  • Computer Networks and Communications 350
  • Ophthalmology 106
  • Health Informatics 17
  • Health Information Management 50
Replace Saeed Ali Bahaj with:
Saeed Ali Bahaj Saudi Arabia
A. M. Rıad Egypt
Muhammad Muzammal Pakistan
S. K. Lakshmanaprabu India
Mukesh Soni India
Saqib Hakak Canada
Dheyaa Ahmed Ibrahim Iraq
Ali Yahyaouy Morocco
Naveed Islam Pakistan
Denis A. Pustokhin Russia
Arpit Jain relative to Saeed Ali Bahaj Saudi Arabia Saeed Ali Bahaj's profile →
Citations per field
00.5×11×
Saeed Ali Bahaj · 1×
Citations per year

Countries citing papers authored by Arpit Jain

Since Specialization
Citations

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

Fields of papers citing papers by Arpit Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 100 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009135
2 202397
3 202172
4 202256
5 202250
6 202147
7 202246
8 202145
9 202343
10 202143
11 202237
12 202237
13 202336
14 202135
15 202234
16 202132
17 202227
18 202227
19 202227
20 202227

About Arpit Jain

Arpit Jain is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering and Signal Processing, having authored 100 papers that have together received 1.5k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (10 papers), Smart Agriculture and AI (9 papers), Advanced Malware Detection Techniques (9 papers), Interconnection Networks and Systems (7 papers), Energy Efficient Wireless Sensor Networks (6 papers), IoT-based Smart Home Systems (6 papers), Advanced Steganography and Watermarking Techniques (5 papers) and IoT and Edge/Fog Computing (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (320 citations), Computer Networks and Communications (350 citations), Ophthalmology (106 citations), Health Informatics (17 citations) and Health Information Management (50 citations). Arpit Jain has collaborated with scholars based in India, United States and Saudi Arabia. Frequent co-authors include Sandeep Kumar, Shilpa Rani, Anurag Mittal, Adesh Kumar, Chaman Verma, Zoltán Illés, Hammam Alshazly, Ali Ahmadian, Shilpa Choudhary and Maria Simona Raboacă. Their work appears in journals such as Heliyon, Computers, materials & continua/Computers, materials & continua (Print), Journal of Ambient Intelligence and Humanized Computing, Sustainable Production and Consumption and Multimedia Tools and Applications.

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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