Joan Martı́
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Pulmonary and Respiratory Medicine
- Molecular Biology
- Co-authors
- Arnau OliverJordi FreixenetXavier LladóJosep PontElsa PérezErika DentonReyer ZwiggelaarXavier Muñoz
- Topics
- AI in cancer detection (21 papers)Image Retrieval and Classification Techniques (16 papers)Medical Image Segmentation Techniques (11 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceRadiology, Nuclear Medicine and Imaging
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Medical ImagingMedical Physics
In The Last Decade
Joan Martı́
42 papers receiving 748 citations
Peers
Comparison fields: 5 of 75
- Artificial Intelligence 533
- Computer Vision and Pattern Recognition 446
- Radiology, Nuclear Medicine and Imaging 321
- Pulmonary and Respiratory Medicine 143
- Molecular Biology 67
Countries citing papers authored by Joan Martı́
This map shows the geographic impact of Joan Martı́'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 Joan Martı́ with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joan Martı́ more than expected).
Fields of papers citing papers by Joan Martı́
This network shows the impact of papers produced by Joan Martı́. 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 Joan Martı́. The network helps show where Joan Martı́ may publish in the future.
Co-authorship network of co-authors of Joan Martı́
This figure shows the co-authorship network connecting the top 25 collaborators of Joan Martı́. A scholar is included among the top collaborators of Joan Martı́ based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Joan Martı́. Joan Martı́ is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 3 | |
| 3 | 7 | |
| 4 | 13 | |
| 5 | MamoDB:a web-based tool for training radiologists in the diagnosis of digital mammography | 2 |
| 6 | 30 | |
| 7 | 28 | |
| 8 | 278 | |
| 9 | 45 | |
| 10 | 94 | |
| 11 | Feature-based matching of underwater images | 11 |
| 12 | 19 | |
| 13 | Mass Segmentation using a Pattern Matching Approach with a Mutual Information Based Metric | 2 |
| 14 | 3 | |
| 15 | 5 | |
| 16 | 33 | |
| 17 | 3 | |
| 18 | 1 | |
| 19 | 3 | |
| 20 | 5 |
About Joan Martı́
Joan Martı́ is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 43 papers that have together received 798 indexed citations. Recurring topics across this work include AI in cancer detection (21 papers), Image Retrieval and Classification Techniques (16 papers) and Medical Image Segmentation Techniques (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (446 citations), Artificial Intelligence (533 citations) and Radiology, Nuclear Medicine and Imaging (321 citations). Joan Martı́ has collaborated with scholars based in Spain, France and Japan. Frequent co-authors include Arnau Oliver, Jordi Freixenet, Xavier Lladó, Josep Pont, Elsa Pérez, Erika Denton, Reyer Zwiggelaar, Xavier Muñoz, Yago Díez and Robert Martí. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Medical Imaging and Medical Physics.
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.