Arnav Jain

11 papers receiving 136 citations

Peers

Arnav Jain
Comparison fields: 5 of 43
  • Computer Vision and Pattern Recognition 68
  • Computer Graphics and Computer-Aided Design 9
  • Automotive Engineering 28
  • Artificial Intelligence 23
  • Media Technology 6
Replace Jinsoo Choi with:
Jinsoo Choi South Korea
Yunzhong Hou Australia
Stefano Pellegrini Italy
Tian Yang China
Chaitanya K. Joshi Singapore
Khushboo Tripathi India
Jinrong Yang China
Bao Xin Chen Canada
Junjie Huang China
Míriam Bellver Spain
Arnav Jain relative to Jinsoo Choi South Korea Jinsoo Choi's profile →
Citations per field
00.5×2.8×
Jinsoo Choi · 1×
Citations per year

Countries citing papers authored by Arnav Jain

Since Specialization
Citations

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

Fields of papers citing papers by Arnav Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Arnav 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 Arnav Jain Line = papers co-authored together Arnav Jain links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 202066
2 202232
3 202115
4 20228
5 20224
6
A Study of ECG Steganography for Securing Patient's Confidential Data based on Wavelet Transformation
20143
7 20203
8 20252
9 20242
10 20252
11 20211
12 20230
13 20230
14 20230
15 20220

About Arnav Jain

Arnav Jain is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Control and Systems Engineering, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 15 papers that have together received 138 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (2 papers), COVID-19 diagnosis using AI (1 paper), Neuroscience and Neural Engineering (1 paper), Glaucoma and retinal disorders (1 paper), IoT-based Smart Home Systems (1 paper), Biometric Identification and Security (1 paper), Robot Manipulation and Learning (1 paper) and Hydrological Forecasting Using AI (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (68 citations), Computer Graphics and Computer-Aided Design (9 citations), Automotive Engineering (28 citations), Artificial Intelligence (23 citations) and Media Technology (6 citations). Arnav Jain has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Pabitra Mitra, Prabir Kumar Biswas, Darsh Patel, K. Chidambaram, B. Ashok, Baljeet Singh, Rajesh Bhatia, Jian Jiao, Ruofei Zhang and Kushal Dave. Their work appears in journals such as Energies, Scientific Reports, Sustainable Cities and Society, Cybernetics and Information Technologies and Cluster Computing.

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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