Marcelo Keese Albertini
- Media Technology top 10%
- Remote-Sensing Image Classification 3
- Image Processing Techniques and Applications 3
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- Advanced Image Processing Techniques 5
- Advanced Vision and Imaging 4
- Image and Signal Denoising Methods 3
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- Advanced Clustering Algorithms Research 5
- Data Stream Mining Techniques 4
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- Time Series Analysis and Forecasting 3
- Co-authors
- Rodrigo Fernandes de MelloRicardo BatistaLouise BouchardGwanggil JeonXiaomin YangGeraldo Caixeta GuimarãesTurgay ÇelikHenrique Fernandes
- Partner nations
- BrazilChinaSouth Korea
In The Last Decade
Marcelo Keese Albertini
29 papers receiving 294 citations
Peers
Comparison fields: 5 of 102
- Media Technology 55
- Computer Vision and Pattern Recognition 77
- Health 24
- Artificial Intelligence 88
- Energy Engineering and Power Technology 5
Countries citing papers authored by Marcelo Keese Albertini
This map shows the geographic impact of Marcelo Keese Albertini'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 Marcelo Keese Albertini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcelo Keese Albertini more than expected).
Fields of papers citing papers by Marcelo Keese Albertini
This network shows the impact of papers produced by Marcelo Keese Albertini. 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 Marcelo Keese Albertini. The network helps show where Marcelo Keese Albertini may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Marcelo Keese Albertini, 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 | 2023 | 12 | |
| 2 | 2023 | 1 | |
| 3 | 2022 | 1 | |
| 4 | 2022 | 5 | |
| 5 | 2022 | 2 | |
| 6 | 2021 | 1 | |
| 7 | 2020 | 5 | |
| 8 | 2020 | 5 | |
| 9 | 2020 | 24 | |
| 10 | 2020 | 13 | |
| 11 | 2020 | 30 | |
| 12 | 2020 | 3 | |
| 13 | 2019 | 0 | |
| 14 | 2017 | 3 | |
| 15 | 2017 | 3 | |
| 16 | 2015 | 62 | |
| 17 | 2015 | 1 | |
| 18 | 2015 | 4 | |
| 19 | 2013 | 1 | |
| 20 | 2007 | 23 |
About Marcelo Keese Albertini
Marcelo Keese Albertini is a scholar working on Media Technology, Signal Processing and Computer Vision and Pattern Recognition, having authored 31 papers that have together received 303 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (5 papers), Advanced Image Processing Techniques (5 papers), Data Stream Mining Techniques (4 papers), Advanced Vision and Imaging (4 papers), Image and Signal Denoising Methods (3 papers), Time Series Analysis and Forecasting (3 papers), Remote-Sensing Image Classification (3 papers) and Image Processing Techniques and Applications (3 papers). The work is most often cited by research in Media Technology (55 citations), Computer Vision and Pattern Recognition (77 citations) and Health (24 citations). Marcelo Keese Albertini has collaborated with scholars based in Brazil, China and South Korea. Frequent co-authors include Rodrigo Fernandes de Mello, Ricardo Batista, Louise Bouchard, Gwanggil Jeon, Xiaomin Yang, Geraldo Caixeta Guimarães, Turgay Çelik, Henrique Fernandes, André Ricardo Backes and João B. Florindo. Their work appears in journals such as Social Science & Medicine, IEEE Access and Information Sciences.
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.