Daniel Urda
Impact in
- Geology top 2%
- 3D Surveying and Cultural Heritage
- Environmental Engineering top 5%
- Remote Sensing and LiDAR Applications
Papers in
-
- Gene expression and cancer classification 7
- Machine Learning in Bioinformatics 5
- Bioinformatics and Genomic Networks 4
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- Advanced Neural Network Applications 5
- Advanced Image and Video Retrieval Techniques 5
- Co-authors
- Martial Hebert (8 shared papers)J. Andrew Bagnell (5 shared papers)Nicolas Vandapel (3 shared papers)José M. Jerez (14 shared papers)Leonardo Franco (12 shared papers)Ignacio J. Turias (10 shared papers)Juan Jesús Ruíz-Aguilar (8 shared papers)Xuehan Xiong (1 shared paper)
- Journals
- Logic Journal of IGPL (3 papers)Neural Computing and Applications (3 papers)Neurocomputing (2 papers)Applied Sciences (2 papers)Data in Brief (1 paper)
- Partner nations
- SpainUnited StatesUnited Kingdom
In The Last Decade
Daniel Urda
41 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 126
- Geology 223
- Environmental Engineering 332
- Computer Vision and Pattern Recognition 309
- Artificial Intelligence 285
- Signal Processing 88
Countries citing papers authored by Daniel Urda
This map shows the geographic impact of Daniel Urda'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 Daniel Urda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Urda more than expected).
Fields of papers citing papers by Daniel Urda
This network shows the impact of papers produced by Daniel Urda. 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 Daniel Urda. The network helps show where Daniel Urda may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Urda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 235 | |
| 2 | 2018 | 102 | |
| 3 | 2017 | 93 | |
| 4 | 2011 | 90 | |
| 5 | 2020 | 77 | |
| 6 | 2020 | 75 | |
| 7 | 2020 | 63 | |
| 8 | 2015 | 56 | |
| 9 | 2011 | 43 | |
| 10 | 2013 | 39 | |
| 11 | 2013 | 33 | |
| 12 | 2018 | 23 | |
| 13 | 2014 | 23 | |
| 14 | Analysis of Cancer Microarray Data using Constructive Neural Networks and Genetic Algorithms. | 2013 | 18 |
| 15 | 2012 | 18 | |
| 16 | 2014 | 17 | |
| 17 | 2020 | 17 | |
| 18 | 2020 | 16 | |
| 19 | 2021 | 14 | |
| 20 | 2013 | 14 |
About Daniel Urda
Daniel Urda is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Artificial Intelligence, Environmental Engineering and Computer Networks and Communications, having authored 48 papers that have together received 1.2k indexed citations. Recurring topics across this work include Gene expression and cancer classification (7 papers), Advanced Neural Network Applications (5 papers), Anomaly Detection Techniques and Applications (5 papers), Machine Learning in Bioinformatics (5 papers), Advanced Image and Video Retrieval Techniques (5 papers), Robotics and Sensor-Based Localization (4 papers), Air Quality Monitoring and Forecasting (4 papers) and Bioinformatics and Genomic Networks (4 papers). The work is most often cited by research in Geology (223 citations), Environmental Engineering (332 citations), Computer Vision and Pattern Recognition (309 citations), Artificial Intelligence (285 citations) and Signal Processing (88 citations). Daniel Urda has collaborated with scholars based in Spain, United States and United Kingdom. Frequent co-authors include Martial Hebert, J. Andrew Bagnell, Nicolas Vandapel, José M. Jerez, Leonardo Franco, Ignacio J. Turias, Juan Jesús Ruíz-Aguilar, Xuehan Xiong, Rafael Marcos Luque‐Baena and Bernabè Dorronsoro. Their work appears in journals such as Logic Journal of IGPL, Neural Computing and Applications, Neurocomputing, Applied Sciences and Data in Brief.
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.