Paramjit Sehdev
Impact in
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- Emotion and Mood Recognition
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- Face and Expression Recognition
- Face recognition and analysis
Papers in
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- Face and Expression Recognition 2
- Face recognition and analysis 2
- Video Surveillance and Tracking Methods 2
- Digital Imaging for Blood Diseases 1
- Co-authors
- Pourya Shamsolmoali (1 shared paper)Deepak Kumar Jain (1 shared paper)Satnam Kaur (2 shared papers)Sandeep Verma (2 shared papers)Mohammad Ayoub Khan (1 shared paper)Varun G. Menon (3 shared papers)Fadi Al‐Turjman (1 shared paper)Sunil Jacob (2 shared papers)
- Journals
- Pattern Recognition Letters (4 papers)Big Data (1 paper)Computer Communications (1 paper)IEEE Communications Standards Magazine (1 paper)IEEE Internet of Things Journal (1 paper)
- Partner nations
- United StatesChinaIndia
In The Last Decade
Paramjit Sehdev
10 papers receiving 526 citations
Paramjit Sehdev's Hit Papers
Peers
Comparison fields: 5 of 75
- Experimental and Cognitive Psychology 233
- Computer Vision and Pattern Recognition 241
- Health Informatics 5
- Computer Networks and Communications 88
- Cognitive Neuroscience 59
Countries citing papers authored by Paramjit Sehdev
This map shows the geographic impact of Paramjit Sehdev'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 Paramjit Sehdev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paramjit Sehdev more than expected).
Fields of papers citing papers by Paramjit Sehdev
This network shows the impact of papers produced by Paramjit Sehdev. 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 Paramjit Sehdev. The network helps show where Paramjit Sehdev may publish in the future.
Co-authors
The 25 scholars most cited alongside Paramjit Sehdev, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Extended deep neural network for facial emotion recognition Hit paper breakdown → | 2019 | 299 |
| 2 | 2020 | 102 | |
| 3 | 2020 | 58 | |
| 4 | 2021 | 17 | |
| 5 | 2018 | 16 | |
| 6 | 2020 | 15 | |
| 7 | 2021 | 10 | |
| 8 | 2018 | 10 | |
| 9 | 2018 | 9 | |
| 10 | 2021 | 8 | |
| 11 | 2020 | 0 | |
| 12 | 2003 | 0 |
About Paramjit Sehdev
Paramjit Sehdev is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Computer Networks and Communications and Automotive Engineering, having authored 12 papers that have together received 544 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (2 papers), Face and Expression Recognition (2 papers), Face recognition and analysis (2 papers), Video Surveillance and Tracking Methods (2 papers), CCD and CMOS Imaging Sensors (2 papers), Fire Detection and Safety Systems (1 paper), Digital Imaging for Blood Diseases (1 paper) and Advanced MIMO Systems Optimization (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (233 citations), Computer Vision and Pattern Recognition (241 citations), Health Informatics (5 citations), Computer Networks and Communications (88 citations) and Cognitive Neuroscience (59 citations). Paramjit Sehdev has collaborated with scholars based in United States, China and India. Frequent co-authors include Pourya Shamsolmoali, Deepak Kumar Jain, Satnam Kaur, Sandeep Verma, Mohammad Ayoub Khan, Varun G. Menon, Fadi Al‐Turjman, Sunil Jacob, Mohammad R. Khosravi and Shuren Zhou. Their work appears in journals such as Pattern Recognition Letters, Big Data, Computer Communications, IEEE Communications Standards Magazine and IEEE Internet of Things Journal.
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.