Javier Marín

1.1k total citations
11 papers, 635 citations indexed

About

Javier Marín is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Automotive Engineering. According to data from OpenAlex, Javier Marín has authored 11 papers receiving a total of 635 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Automotive Engineering. Recurrent topics in Javier Marín's work include Video Surveillance and Tracking Methods (8 papers), Advanced Neural Network Applications (6 papers) and Advanced Image and Video Retrieval Techniques (3 papers). Javier Marín is often cited by papers focused on Video Surveillance and Tracking Methods (8 papers), Advanced Neural Network Applications (6 papers) and Advanced Image and Video Retrieval Techniques (3 papers). Javier Marín collaborates with scholars based in Spain, United States and Germany. Javier Marín's co-authors include Antonio M. López, David Vázquez, David Gerónimo, Yusuf Aytar, Amaia Salvador, Antonio Torralba, Ingmar Weber, Ferda Ofli, Daniel Ponsa and Jaume Amores and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Intelligent Transportation Systems and IEEE Transactions on Cybernetics.

In The Last Decade

Javier Marín

11 papers receiving 611 citations

Peers

Javier Marín

CVPR

AI

BE

PHEOH

AE

Antonino Furnari Italy

Hengde Zhu United Kingdom

Huailin Zhao China

Jinxia Yu China

Mouazma Batool Pakistan

M. Saeed Darweesh Egypt

Yoong Choon Chang Malaysia

Marco A. Moreno-Armendáriz Mexico

Yeon-Ho Kim South Korea

Antonino Furnari Italy

Javier Marín

671 ×1.4

CVPR

252 ×1.4

AI

46 ×0.7

BE

15 ×0.3

PHEOH

31 ×0.7

AE

Citations per year, relative to Javier Marín Javier Marín (= 1×) peers Antonino Furnari

Countries citing papers authored by Javier Marín

Since Specialization

Citations

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

Fields of papers citing papers by Javier Marín

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Javier Marín

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

All Works

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11 of 11 papers shown

1.

Takáts, K., et al.. (2023). A New Framework for Evaluating Image Quality Including Deep Learning Task Performances as a Proxy. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 3285–3296. 1 indexed citations

2.

Salvador, Amaia, Yusuf Aytar, Javier Marín, et al.. (2017). Learning Cross-Modal Embeddings for Cooking Recipes and Food Images. 3068–3076. 229 indexed citations

3.

López, Antonio M., et al.. (2017). Training my car to see using virtual worlds. Image and Vision Computing. 68. 102–118. 6 indexed citations

4.

Xu, Jiaolong, David Vázquez, Antonio M. López, Javier Marín, & Daniel Ponsa. (2014). Learning a Part-Based Pedestrian Detector in a Virtual World. IEEE Transactions on Intelligent Transportation Systems. 15(5). 2121–2131. 33 indexed citations

5.

Vázquez, David, Antonio M. López, Javier Marín, Daniel Ponsa, & David Gerónimo. (2013). Virtual and Real World Adaptation for Pedestrian Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36(4). 797–809. 107 indexed citations

6.

Xu, Jiaolong, David Vázquez, Antonio M. López, Javier Marín, & Daniel Ponsa. (2013). Learning a multiview part-based model in virtual world for pedestrian detection. 467–472. 2 indexed citations

7.

Marín, Javier, David Vázquez, Antonio M. López, Jaume Amores, & Ludmila I. Kuncheva. (2013). Occlusion Handling via Random Subspace Classifiers for Human Detection. IEEE Transactions on Cybernetics. 44(3). 342–354. 41 indexed citations

8.

Marín, Javier, David Vázquez, Antonio M. López, Jaume Amores, & Bastian Leibe. (2013). Random Forests of Local Experts for Pedestrian Detection. 2592–2599. 90 indexed citations

9.

Vázquez, David, Antonio M. López, Daniel Ponsa, & Javier Marín. (2011). Virtual worlds and active learning for human detection. 393–400. 8 indexed citations

10.

Marín, Javier, David Vázquez, David Gerónimo, & Antonio M. López. (2010). Learning appearance in virtual scenarios for pedestrian detection. 137–144. 107 indexed citations

11.

Schoenwald, J.S., et al.. (1982). Acoustic Scanning for Robotic Range Sensing and Object Pattern Recognition. 945–949. 11 indexed citations

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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