Dimas Lima
Impact in
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- Emotion and Mood Recognition
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- Brain Tumor Detection and Classification
Papers in
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- Brain Tumor Detection and Classification 8
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- Face and Expression Recognition 2
- Digital Imaging for Blood Diseases 1
- Co-authors
- Bin Li (2 shared papers)Shuangshuang Gao (1 shared paper)Jian Wang (1 shared paper)Mengxia Wang (1 shared paper)Xue Han (1 shared paper)Yan Yan (1 shared paper)William Yang Wang (1 shared paper)Zuojin Hu (1 shared paper)
- Journals
- Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (1 paper)AIP conference proceedings (1 paper)DOAJ (DOAJ: Directory of Open Access Journals) (5 papers)
- Partner nations
- BrazilChinaUnited Kingdom
In The Last Decade
Dimas Lima
10 papers receiving 286 citations
Peers
Comparison fields: 5 of 81
- Experimental and Cognitive Psychology 78
- Neurology 45
- Computer Vision and Pattern Recognition 124
- Health Informatics 5
- Health Information Management 16
Countries citing papers authored by Dimas Lima
This map shows the geographic impact of Dimas Lima'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 Dimas Lima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dimas Lima more than expected).
Fields of papers citing papers by Dimas Lima
This network shows the impact of papers produced by Dimas Lima. 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 Dimas Lima. The network helps show where Dimas Lima may publish in the future.
Co-authors
The 9 scholars most cited alongside Dimas Lima, 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 | 175 | |
| 2 | 2021 | 57 | |
| 3 | 2021 | 23 | |
| 4 | 2017 | 16 | |
| 5 | 2021 | 11 | |
| 6 | 2021 | 9 | |
| 7 | 2018 | 5 | |
| 8 | 2022 | 2 | |
| 9 | 2022 | 1 | |
| 10 | 2021 | 1 |
About Dimas Lima
Dimas Lima is a scholar working on Neurology, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Analytical Chemistry and Artificial Intelligence, having authored 10 papers that have together received 300 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (8 papers), Spectroscopy and Chemometric Analyses (3 papers), COVID-19 diagnosis using AI (3 papers), Face and Expression Recognition (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Digital Imaging for Blood Diseases (1 paper), Dementia and Cognitive Impairment Research (1 paper) and Spectroscopy Techniques in Biomedical and Chemical Research (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (78 citations), Neurology (45 citations), Computer Vision and Pattern Recognition (124 citations), Health Informatics (5 citations) and Health Information Management (16 citations). Dimas Lima has collaborated with scholars based in Brazil, China and United Kingdom. Frequent co-authors include Bin Li, Shuangshuang Gao, Jian Wang, Mengxia Wang, Xue Han, Yan Yan, William Yang Wang, Zuojin Hu and Lin Yang. Their work appears in journals such as Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, AIP conference proceedings and DOAJ (DOAJ: Directory of Open Access Journals).
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.