Deep Gupta

57 papers receiving 1.2k citations

Peers

Deep Gupta
Comparison fields: 5 of 114
  • Health Informatics 58
  • Media Technology 308
  • Health Information Management 100
  • Computer Vision and Pattern Recognition 397
  • Cardiology and Cardiovascular Medicine 378
Replace Timothy J. W. Dawes with:
Timothy J. W. Dawes United Kingdom
Mainak Biswas India
Spyretta Golemati Greece
Kristen M. Meiburger Italy
Xiangrong Zhou Japan
Muthu Rama Krishnan Mookiah Singapore
Luca Saba Italy
Tomasz Markiewicz Poland
Marcos Ortega Spain
Deep Gupta relative to Timothy J. W. Dawes United Kingdom Timothy J. W. Dawes's profile →
Citations per field
00.5×2.7×
Timothy J. W. Dawes · 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 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015120
2 201665
3 201957
4 201957
5 201849
6 202044
7 202144
8 202042
9 201440
10 202039
11 202035
12 201930
13 201930
14 202030
15 201930
16 202029
17 201829
18 201928
19 201928
20 201427

About Deep Gupta

Deep Gupta is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging, having authored 59 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Image Fusion Techniques (23 papers), Cardiovascular Health and Disease Prevention (19 papers), Image and Signal Denoising Methods (19 papers), Cerebrovascular and Carotid Artery Diseases (18 papers), Cardiac Imaging and Diagnostics (9 papers), Advanced Image Processing Techniques (8 papers), Image Enhancement Techniques (6 papers) and Medical Image Segmentation Techniques (4 papers). The work is most often cited by research in Health Informatics (58 citations), Media Technology (308 citations), Health Information Management (100 citations), Computer Vision and Pattern Recognition (397 citations) and Cardiology and Cardiovascular Medicine (378 citations). Deep Gupta has collaborated with scholars based in India, Italy and United States. Frequent co-authors include R. S. Anand, Barjeev Tyagi, Ankush D. Jamthikar, Sneha Singh, John R. Laird, Jasjit S. Suri, Narendra N. Khanna, Luca Saba, Vinod Kumar and Andrew Nicolaides. Their work appears in journals such as Biomedical Signal Processing and Control, Computers in Biology and Medicine, IEEE Transactions on Instrumentation and Measurement, Current Atherosclerosis Reports 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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