Abhijit Sarkar

534 citations
36 papers · 306 indexed · h-index 11

Abhijit Sarkar

34 papers receiving 289 citations

Peers

Abhijit Sarkar
Comparison fields: 5 of 74
  • Building and Construction 57
  • Cognitive Neuroscience 79
  • Computer Vision and Pattern Recognition 75
  • Safety, Risk, Reliability and Quality 24
  • Cardiology and Cardiovascular Medicine 58
Replace B. Padmaja with:
B. Padmaja India
Aura Hernández-Sabaté Spain
Azlan Abd Aziz Malaysia
Hamidur Rahman Sweden
Yen-Liang Lin Taiwan
Naohisa Hashimoto Japan
Lawrence C. Barr United States
Lan Fu United States
Yihua Cheng China
Abhijit Sarkar relative to B. Padmaja India B. Padmaja's profile →
Citations per field
00.5×10×13×
B. Padmaja · 1×
Citations per year

Countries citing papers authored by Abhijit Sarkar

Since Specialization
Citations

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

Fields of papers citing papers by Abhijit Sarkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202410
2 20240
3 20234
4 20233
5 202211
6 20220
7 202119
8 202118
9
Detection of COVID-19 from Chest Computed Tomography (CT) images using Deep learning: Comparing COGNEX VisionPro Deep Learning 1.0 Software with Open Source Convolutional Neural Networks
20201
10 20172
11
Video Magnification to Detect Heart Rate for Drivers
20171
12 201633
13 201515
14 201110
15 20114
16 201013
17 201014
18 20083
19 200823
20 200623

About Abhijit Sarkar

Abhijit Sarkar is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering and Social Psychology, having authored 36 papers that have together received 306 indexed citations. Recurring topics across this work include Non-Invasive Vital Sign Monitoring (7 papers), ECG Monitoring and Analysis (6 papers), Autonomous Vehicle Technology and Safety (6 papers), Human-Automation Interaction and Safety (5 papers), Color Science and Applications (5 papers), Visual perception and processing mechanisms (4 papers), Advanced Neural Network Applications (4 papers) and Traffic and Road Safety (4 papers). The work is most often cited by research in Building and Construction (57 citations), Cognitive Neuroscience (79 citations) and Computer Vision and Pattern Recognition (75 citations). Abhijit Sarkar has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include A. Lynn Abbott, Zachary R. Doerzaph, Mark D. Fairchild, Richard G. Mistrick, Carl Salvaggio, P. Barat, Laurent Blondé, Florent Autrusseau, Patrick Le Callet and Jeffrey S. Hickman. Their work appears in journals such as LEUKOS The Journal of the Illuminating Engineering Society of North America, Fractals, The Visual Computer, International Journal of Environmental Research and Public Health and Journal of the Optical Society of America A.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026