David Macêdo

457 citations
22 papers · 254 · h-index 8

Impact in

Papers in

    • Adversarial Robustness in Machine Learning 3
    • Anomaly Detection Techniques and Applications 3
    • Domain Adaptation and Few-Shot Learning 3
    • Coding theory and cryptography 2
    • Advanced Neural Network Applications 7
    • Advanced Image and Video Retrieval Techniques 3
    • Human Pose and Action Recognition 2

David Macêdo

19 papers receiving 247 citations

Peers

David Macêdo
Comparison fields: 5 of 64
  • Signal Processing 56
  • Computer Networks and Communications 103
  • Artificial Intelligence 136
  • Computer Vision and Pattern Recognition 80
  • Occupational Therapy 5
Replace Zhongtang Zhao with:
Zhongtang Zhao China
Mohammad Nabati Iran
Manassés Ribeiro Brazil
Rafael Estepa Spain
Muhammad Usman Yaseen Pakistan
B. Perumal India
K. Deepak India
Oluwatoyin P. Popoola Nigeria
Prima Kristalina Indonesia
Fuxiang Wu China
David Macêdo relative to Zhongtang Zhao China Zhongtang Zhao's profile →
Citations per field
00.5×8.7×
Zhongtang Zhao · 1×
Citations per year

Countries citing papers authored by David Macêdo

Since Specialization
Citations

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

Fields of papers citing papers by David Macêdo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Macêdo. 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 Macêdo. The network helps show where David Macêdo may publish in the future.

Co-authors

The 17 scholars most cited alongside David Macêdo, 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 David Macêdo Line = papers co-authored together David Macêdo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020111
2 201928
3 202227
4 201818
5 202117
6 201810
7 20199
8 20228
9 20196
10 20225
11 20224
12 20242
13 19992
14 20211
15
Simple Fast Convolutional Feature Learning
20181
16 20191
17 20231
18 19961
19 20211
20 20231

About David Macêdo

David Macêdo is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Computer Networks and Communications and Safety, Risk, Reliability and Quality, having authored 22 papers that have together received 254 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (7 papers), Adversarial Robustness in Machine Learning (3 papers), Anomaly Detection Techniques and Applications (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Fire Detection and Safety Systems (2 papers), Human Pose and Action Recognition (2 papers) and Coding theory and cryptography (2 papers). The work is most often cited by research in Signal Processing (56 citations), Computer Networks and Communications (103 citations), Artificial Intelligence (136 citations), Computer Vision and Pattern Recognition (80 citations) and Occupational Therapy (5 citations). David Macêdo has collaborated with scholars based in Brazil, Canada and United States. Frequent co-authors include Cleber Zanchettin, Adriano L. I. Oliveira, Georges Kaddoum, Divanilson R. Campelo, Paulo Freitas de Araujo-Filho, Teresa B. Ludermir, Paulo S. G. de Mattos Neto, Tsang Ing Ren, Luiz Antônio de Oliveira and Byron Leite Dantas Bezerra. Their work appears in journals such as Expert Systems with Applications, Computer Communications, IEEE Transactions on Neural Networks and Learning Systems, IEEE Access and Applied Soft Computing.

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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