Matthew R. Scott
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- Advanced Image and Video Retrieval Techniques 6
- Generative Adversarial Networks and Image Synthesis 5
- Human Pose and Action Recognition 4
- Human-Computer Interaction top 5%
- Artificial Intelligence top 2%
- Domain Adaptation and Few-Shot Learning 6
- Media Technology top 2%
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- Alzheimer's disease research and treatments 10
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- Dementia and Cognitive Impairment Research 8
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- Functional Brain Connectivity Studies 8
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- Advanced Neuroimaging Techniques and Applications 8
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Matthew R. Scott
45 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 138
- Computer Vision and Pattern Recognition 1.5k
- Human-Computer Interaction 114
- Artificial Intelligence 576
- Media Technology 140
- Computer Graphics and Computer-Aided Design 55
Countries citing papers authored by Matthew R. Scott
This map shows the geographic impact of Matthew R. Scott'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 Matthew R. Scott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew R. Scott more than expected).
Fields of papers citing papers by Matthew R. Scott
This network shows the impact of papers produced by Matthew R. Scott. 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 Matthew R. Scott. The network helps show where Matthew R. Scott may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Matthew R. Scott, 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 5 | |
| 4 | 2023 | 1 | |
| 5 | 2022 | 34 | |
| 6 | 2022 | 79 | |
| 7 | 2021 | 4 | |
| 8 | Deformable Siamese Attention Networks for Visual Object Trackingbreakdown → | 2020 | 312 |
| 9 | V4D: 4D Covolutional Neural Networks for Video-level Representations Learning | 2020 | 5 |
| 10 | 2020 | 34 | |
| 11 | 2020 | 36 | |
| 12 | 2020 | 29 | |
| 13 | 2020 | 168 | |
| 14 | 2019 | 155 | |
| 15 | 2019 | 40 | |
| 16 | Multi-Similarity Loss With General Pair Weighting for Deep Metric Learningbreakdown → | 2019 | 493 |
| 17 | 2019 | 39 | |
| 18 | 2017 | 59 | |
| 19 | Engkoo: Mining the Web for Language Learning | 2011 | 1 |
| 20 | A case study of strategic infarct dementia investigated with the cognitive assessment system. | 2002 | 3 |
About Matthew R. Scott
Matthew R. Scott is a scholar working on Computer Vision and Pattern Recognition, Psychiatry and Mental health and Human-Computer Interaction, having authored 47 papers that have together received 2.2k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (10 papers), Dementia and Cognitive Impairment Research (8 papers), Functional Brain Connectivity Studies (8 papers), Advanced Neuroimaging Techniques and Applications (8 papers), Domain Adaptation and Few-Shot Learning (6 papers), Advanced Image and Video Retrieval Techniques (6 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Human Pose and Action Recognition (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Human-Computer Interaction (114 citations) and Artificial Intelligence (576 citations). Matthew R. Scott has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Weilin Huang, Xun Wang, Xintong Han, Yilei Xiong, Xiaojun Hu, Xintong Han, Haozhi Zhang, Zhi Tian, Linjie Xing and Yu Gao. Their work appears in journals such as Circulation, Nature Communications and NeuroImage.
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.