Deep Gupta

72 papers receiving 1.6k citations

Peers

Deep Gupta
Comparison fields: 5 of 121
  • Health Informatics 65
  • Media Technology 336
  • Health Information Management 158
  • Computer Vision and Pattern Recognition 440
  • Cardiology and Cardiovascular Medicine 388
Replace Mainak Biswas with:
Mainak Biswas India
Spyretta Golemati Greece
Massimo Salvi Italy
Muthu Rama Krishnan Mookiah Singapore
Kristen M. Meiburger Italy
Marcos Ortega Hortas Spain
Chengjia Wang United Kingdom
Xiangrong Zhou Japan
Tao Tan China
Deep Gupta relative to Mainak Biswas India Mainak Biswas's profile →
Citations per field
00.5×2×3.1×
Mainak Biswas · 1×
Citations per year

Countries citing papers authored by Deep Gupta

Since Specialization
Citations

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

Fields of papers citing papers by Deep Gupta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015129
2 201978
3 201672
4 201970
5 202067
6 201866
7 202065
8 202061
9 202054
10 202150
11 202047
12 201946
13 201443
14 201941
15 202039
16 201939
17 201938
18 201936
19 201833
20 201832

About Deep Gupta

Deep Gupta is a scholar working on Media Technology, Computer Vision and Pattern Recognition, Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 75 papers that have together received 1.7k indexed citations. Recurring topics across this work include Advanced Image Fusion Techniques (25 papers), Image and Signal Denoising Methods (20 papers), Cardiovascular Health and Disease Prevention (14 papers), Cerebrovascular and Carotid Artery Diseases (10 papers), Advanced Image Processing Techniques (8 papers), Image Enhancement Techniques (6 papers), Remote-Sensing Image Classification (5 papers) and Cardiac Imaging and Diagnostics (5 papers). The work is most often cited by research in Health Informatics (65 citations), Media Technology (336 citations), Health Information Management (158 citations), Computer Vision and Pattern Recognition (440 citations) and Cardiology and Cardiovascular Medicine (388 citations). Deep Gupta has collaborated with scholars based in India, Italy and United States. Frequent co-authors include R. S. Anand, Ankush D. Jamthikar, John R. Laird, Jasjit S. Suri, Barjeev Tyagi, Narendra Nath Khanna, Sneha Singh, Luca Saba, Andrew N Nicolaides and Sophie I. Mavrogeni. Their work appears in journals such as Biomedical Signal Processing and Control, Computers in Biology and Medicine, Current Atherosclerosis Reports, IEEE Transactions on Instrumentation and Measurement and International Journal of Imaging Systems and Technology.

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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