Alceu Ferraz Costa

496 citations
11 papers · 321 indexed · h-index 6
Journals
Computer Methods and Programs in Biomedicine (1 paper)ACM Transactions on Knowledge Discovery from Data (1 paper)Scientific Electronic Library Online (São Paulo Research Foundation, Latin American and Caribbean Center on Health Sciences Information, Conselho Nacional de Desenvolvimento Científico e Tecnológico) (3 papers)

In The Last Decade

Alceu Ferraz Costa

11 papers receiving 306 citations

Peers

Alceu Ferraz Costa
Comparison fields: 5 of 95
  • Computer Vision and Pattern Recognition 150
  • Signal Processing 34
  • Artificial Intelligence 95
  • Media Technology 23
  • Statistical and Nonlinear Physics 32
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Feng Shao China
Haiwei Pan China
Sheng Zhou China
Paulo S. Rodrigues Brazil
Grigory Begelman Israel
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Citations per field
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Citations per year

Countries citing papers authored by Alceu Ferraz Costa

Since Specialization
Citations

This map shows the geographic impact of Alceu Ferraz Costa'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 Alceu Ferraz Costa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alceu Ferraz Costa more than expected).

Fields of papers citing papers by Alceu Ferraz Costa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alceu Ferraz Costa. 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 Alceu Ferraz Costa. The network helps show where Alceu Ferraz Costa may publish in the future.

Co-authorship network

The 10 scholars most cited alongside Alceu Ferraz Costa, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Alceu Ferraz Costa Line = papers co-authored together Alceu Ferraz Costa links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 20193
2 201715
3 20172
4 20171
5 20165
6 20165
7 201557
8 20157
9 20144
10 2012209
11 201113

About Alceu Ferraz Costa

Alceu Ferraz Costa is a scholar working on Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality and Statistical and Nonlinear Physics, having authored 11 papers that have together received 321 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (5 papers), Advanced Image and Video Retrieval Techniques (2 papers), Complex Network Analysis Techniques (2 papers), Fire Detection and Safety Systems (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Image Enhancement Techniques (1 paper), Spam and Phishing Detection (1 paper) and Game Theory and Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (150 citations), Signal Processing (34 citations) and Artificial Intelligence (95 citations). Alceu Ferraz Costa has collaborated with scholars based in Brazil, Moldova and United States. Frequent co-authors include Agma J. M. Traina, Gabriel Efrain Humpire Mamani, Caetano Traina, Christos Faloutsos, Yuto Yamaguchi, Joe Tekli, José F. Rodrigues, Mirela T. Cazzolato, Paulo Mazzoncini de Azevedo‐Marques and Marcel Koenigkam Santos. Their work appears in journals such as Computer Methods and Programs in Biomedicine, ACM Transactions on Knowledge Discovery from Data and Scientific Electronic Library Online (São Paulo Research Foundation, Latin American and Caribbean Center on Health Sciences Information, Conselho Nacional de Desenvolvimento Científico e Tecnológico).

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.

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