David Mota
Impact in
- Media Technology top 1%
- Vehicle License Plate Recognition
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- Handwritten Text Recognition Techniques
- Image Processing and 3D Reconstruction
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Video Analysis and Summarization
Papers in
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- Bipolar Disorder and Treatment 1
- Electroconvulsive Therapy Studies 1
- Co-authors
- Joan Mas (1 shared paper)Lluís Gómez (1 shared paper)Jon Almazán (1 shared paper)Lluís-Pere de las Heras (1 shared paper)Dìmosthenis Karatzas (1 shared paper)Faisal Shafait (1 shared paper)Masakazu Iwamura (1 shared paper)Seiichi Uchida (1 shared paper)
- Journals
- Integration (1 paper)BMJ Case Reports (1 paper)Estudo Geral (Universidade de Coimbra) (1 paper)UWA Profiles and Research Repository (UWA) (1 paper)
In The Last Decade
David Mota
5 papers receiving 790 citations
David Mota's Hit Papers
Peers
Comparison fields: 5 of 32
- Media Technology 339
- Computer Vision and Pattern Recognition 783
- Artificial Intelligence 151
- Human-Computer Interaction 19
- Signal Processing 19
Countries citing papers authored by David Mota
This map shows the geographic impact of David Mota'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 David Mota with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Mota more than expected).
Fields of papers citing papers by David Mota
This network shows the impact of papers produced by David Mota. 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 David Mota. The network helps show where David Mota may publish in the future.
Co-authors
The 14 scholars most cited alongside David Mota, 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 | ICDAR 2013 Robust Reading Competition Hit paper breakdown → | 2013 | 800 |
| 2 | 2020 | 8 | |
| 3 | 2017 | 3 | |
| 4 | 2017 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 0 |
About David Mota
David Mota is a scholar working on Neurology, Psychiatry and Mental health, Computer Networks and Communications, Cardiology and Cardiovascular Medicine and Management Information Systems, having authored 6 papers that have together received 813 indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (1 paper), Mental Health and Psychiatry (1 paper), Distributed systems and fault tolerance (1 paper), Handwritten Text Recognition Techniques (1 paper), Bipolar Disorder and Treatment (1 paper), Big Data and Business Intelligence (1 paper), Radiation Effects in Electronics (1 paper) and Electroconvulsive Therapy Studies (1 paper). The work is most often cited by research in Media Technology (339 citations), Computer Vision and Pattern Recognition (783 citations), Artificial Intelligence (151 citations), Human-Computer Interaction (19 citations) and Signal Processing (19 citations). David Mota has collaborated with scholars based in Portugal, Australia and Japan. Frequent co-authors include Joan Mas, Lluís Gómez, Jon Almazán, Lluís-Pere de las Heras, Dìmosthenis Karatzas, Faisal Shafait, Masakazu Iwamura, Seiichi Uchida, Fabian Vargas and João Mota. Their work appears in journals such as Integration, BMJ Case Reports, Estudo Geral (Universidade de Coimbra) and UWA Profiles and Research Repository (UWA).
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.