David Raba

913 citations
17 papers · 733 · h-index 9

Impact in

Papers in

David Raba

17 papers receiving 694 citations

Peers

David Raba
Comparison fields: 5 of 89
  • Computer Vision and Pattern Recognition 502
  • Media Technology 136
  • Artificial Intelligence 287
  • Radiology, Nuclear Medicine and Imaging 123
  • Industrial and Manufacturing Engineering 47
Replace He Cheng with:
He Cheng United States
Yuefeng Chen China
Shengdong Zhang China
Suneeta Agarwal India
Sheng Ren China
Chenxi Xu China
Ashutosh Aggarwal India
Zhiqiang He China
Roman Solovyev Russia
David Raba relative to He Cheng United States He Cheng's profile →
Citations per field
00.5×3.9×
He Cheng · 1×
Citations per year

Countries citing papers authored by David Raba

Since Specialization
Citations

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

Fields of papers citing papers by David Raba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside David Raba, 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 Raba Line = papers co-authored together David Raba links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2002414
2 2005141
3 202334
4 200530
5 200728
6 202022
7 202120
8 200313
9 20068
10 20196
11 20205
12 20213
13 20053
14
Monitoring the lead contamination of food products of non-animal origin in different regions from Romania in 2019.
20202
15 20222
16 20051
17
Texture segmentation in mammograms
20031

About David Raba

David Raba is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Industrial and Manufacturing Engineering, having authored 17 papers that have together received 733 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Medical Image Segmentation Techniques (4 papers), Digital Radiography and Breast Imaging (4 papers), Advanced Manufacturing and Logistics Optimization (3 papers), Image and Object Detection Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Vehicle Routing Optimization Methods (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (502 citations), Media Technology (136 citations), Artificial Intelligence (287 citations), Radiology, Nuclear Medicine and Imaging (123 citations) and Industrial and Manufacturing Engineering (47 citations). David Raba has collaborated with scholars based in Spain, United Kingdom and Germany. Frequent co-authors include Jordi Freixenet, Xavier Cufí, Xavier Muñoz, J. Martı́, Arnau Oliver, Joan Martı́, M. Peracaula, Reyer Zwiggelaar, Ángel A. Juan and Robert Martí. Their work appears in journals such as IEEE Robotics and Automation Letters, International Transactions in Operational Research, Sensors, Lecture notes in computer science and 2022 IEEE Intelligent Vehicles Symposium (IV).

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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