John Gideon
Impact in
-
- Digital Mental Health Interventions
-
- Emotion and Mood Recognition
- Mental Health Research Topics
Papers in
-
- Sleep and Work-Related Fatigue 2
- Emotion and Mood Recognition 2
-
- Domain Adaptation and Few-Shot Learning 1
- Co-authors
- Simon Stent (6 shared papers)Emily Mower Provost (5 shared papers)Melvin G. McInnis (4 shared papers)Heather T. Schatten (1 shared paper)Duc Le (1 shared paper)Luke Fletcher (1 shared paper)Song Han (1 shared paper)Zakaria Aldeneh (1 shared paper)
- Journals
- European Neuropsychopharmacology (1 paper)PubMed (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2 papers)
- Partner nations
- United States
In The Last Decade
John Gideon
10 papers receiving 230 citations
Peers
Comparison fields: 5 of 40
- Applied Psychology 32
- Experimental and Cognitive Psychology 57
- Cardiology and Cardiovascular Medicine 61
- Biomedical Engineering 93
- Human-Computer Interaction 12
Countries citing papers authored by John Gideon
This map shows the geographic impact of John Gideon'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 John Gideon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Gideon more than expected).
Fields of papers citing papers by John Gideon
This network shows the impact of papers produced by John Gideon. 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 John Gideon. The network helps show where John Gideon may publish in the future.
Co-authors
The 12 scholars most cited alongside John Gideon, 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 | 2021 | 88 | |
| 2 | 2016 | 65 | |
| 3 | 2019 | 22 | |
| 4 | 2016 | 17 | |
| 5 | 2021 | 15 | |
| 6 | 2021 | 7 | |
| 7 | 2022 | 7 | |
| 8 | 2017 | 5 | |
| 9 | 2016 | 5 | |
| 10 | 2018 | 4 | |
| 11 | 2024 | 0 |
About John Gideon
John Gideon is a scholar working on Experimental and Cognitive Psychology, Artificial Intelligence, Social Psychology, Cardiology and Cardiovascular Medicine and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 235 indexed citations. Recurring topics across this work include Sleep and Work-Related Fatigue (2 papers), Human-Automation Interaction and Safety (2 papers), Non-Invasive Vital Sign Monitoring (2 papers), Emotion and Mood Recognition (2 papers), Speech and Audio Processing (2 papers), Multimodal Machine Learning Applications (1 paper), Domain Adaptation and Few-Shot Learning (1 paper) and Retinal Imaging and Analysis (1 paper). The work is most often cited by research in Applied Psychology (32 citations), Experimental and Cognitive Psychology (57 citations), Cardiology and Cardiovascular Medicine (61 citations), Biomedical Engineering (93 citations) and Human-Computer Interaction (12 citations). John Gideon has collaborated with scholars based in United States. Frequent co-authors include Simon Stent, Emily Mower Provost, Melvin G. McInnis, Heather T. Schatten, Duc Le, Luke Fletcher, Song Han, Zakaria Aldeneh, Zhijian Liu and Yelin Kim. Their work appears in journals such as European Neuropsychopharmacology, PubMed, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.