José Ignacio Orlando

27 papers receiving 882 citations

Hit Papers

A Discriminatively Trained Fully Connected Conditional Ra...20162026201920222016100200300

Peers

José Ignacio Orlando
Comparison fields: 5 of 73
  • Radiology, Nuclear Medicine and Imaging 768
  • Ophthalmology 552
  • Computer Vision and Pattern Recognition 466
  • Artificial Intelligence 98
  • Biomedical Engineering 76
Replace Behdad Dashtbozorg with:
Behdad Dashtbozorg Netherlands
Sandra Morales Spain
Rongchang Zhao China
Andres Diaz‐Pinto United Kingdom
Erik J. Bekkers Netherlands
Paweł Liskowski Poland
Ahmed J. Afifi Germany
Soochahn Lee South Korea
Zaiwang Gu China
Pedro Costa Portugal
José Ignacio Orlando relative to Behdad Dashtbozorg Netherlands Behdad Dashtbozorg's profile →
Citations per field
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Behdad Dashtbozorg · 1×
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Countries citing papers authored by José Ignacio Orlando

Since Specialization
Citations

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

Fields of papers citing papers by José Ignacio Orlando

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José Ignacio Orlando. 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 José Ignacio Orlando. The network helps show where José Ignacio Orlando may publish in the future.

Co-authorship network of co-authors of José Ignacio Orlando

This figure shows the co-authorship network connecting the top 25 collaborators of José Ignacio Orlando. A scholar is included among the top collaborators of José Ignacio Orlando 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 José Ignacio Orlando. José Ignacio Orlando is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 12
4 8
5 0
6 3
7 1
8 18
9 14
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SketchZooms: Deep Multi-view Descriptors for Matching Line Drawings
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Linking Function and Structure: Prediction of Retinal Sensitivity in AMD from OCT using Deep Learning
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14 41
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16 100
17 26
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Acaros acuáticos (Acari: Hydrachnidiae) de Colombia
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Acondicionadores y mejoradores del suelo
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About José Ignacio Orlando

José Ignacio Orlando is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging and Health Informatics, having authored 32 papers that have together received 914 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (18 papers), Glaucoma and retinal disorders (8 papers) and Digital Imaging for Blood Diseases (7 papers). The work is most often cited by research in Ophthalmology (552 citations), Radiology, Nuclear Medicine and Imaging (768 citations) and Computer Vision and Pattern Recognition (466 citations). José Ignacio Orlando has collaborated with scholars based in Argentina, Austria and United States. Frequent co-authors include Matthew B. Blaschko, Elena Prokofyeva, Mariana del Fresno, Hrvoje Bogunović, Ursula Schmidt‐Erfurth, Sebastian M. Waldstein, Philipp Seeböck, Ignacio Larrabide, Georg Langs and Thomas Schlegl. Their work appears in journals such as Scientific Reports, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.

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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