Joan Puigcerver

1.6k total citations
19 papers, 329 citations indexed

About

Joan Puigcerver is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Joan Puigcerver has authored 19 papers receiving a total of 329 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 16 papers in Artificial Intelligence and 3 papers in Information Systems. Recurrent topics in Joan Puigcerver's work include Handwritten Text Recognition Techniques (15 papers), Natural Language Processing Techniques (13 papers) and Advanced Neural Network Applications (4 papers). Joan Puigcerver is often cited by papers focused on Handwritten Text Recognition Techniques (15 papers), Natural Language Processing Techniques (13 papers) and Advanced Neural Network Applications (4 papers). Joan Puigcerver collaborates with scholars based in Spain, Switzerland and France. Joan Puigcerver's co-authors include Enrique Vidal, Alejandro H. Toselli, Sylvain Gelly, Neil Houlsby, Xiaohua Zhai, Lucas Beyer, Alexander Kolesnikov, Jessica Yung, Konstantinos Zagoris and Ioannis Pratikakis and has published in prestigious journals such as Neural Computing and Applications, Pattern Analysis and Applications and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Joan Puigcerver

19 papers receiving 317 citations

Peers

Joan Puigcerver

CVPR

Yaqiang Wu China

Pau Riba Spain

Toni M. Rath United States

Salvador España-Boquera Spain

Vladimir Pervouchine Singapore

Yasuhisa Fujii United States

Philippe Mulhem France

Luca Piras Italy

Kartik Dutta India

Minesh Mathew India

Yaqiang Wu China

Joan Puigcerver

288 ×1.0

CVPR

116 ×0.7

96 ×2.3

23 ×0.6

23 ×1.2

Citations per year, relative to Joan Puigcerver Joan Puigcerver (= 1×) peers Yaqiang Wu

Countries citing papers authored by Joan Puigcerver

Since Specialization

Citations

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

Fields of papers citing papers by Joan Puigcerver

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joan Puigcerver

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

All Works

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19 of 19 papers shown

Toselli, Alejandro H., Joan Puigcerver, & Enrique Vidal. (2024). Probabilistic Indexing for Information Search and Retrieval in Large Collections of Handwritten Text Images. 1 indexed citations

Vidal, Enrique, Alejandro H. Toselli, & Joan Puigcerver. (2023). Lexicon-based probabilistic indexing of handwritten text images. Neural Computing and Applications. 35(24). 17501–17520. 2 indexed citations

Renggli, Cédric, et al.. (2022). Which Model to Transfer? Finding the Needle in the Growing Haystack. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 9195–9204. 6 indexed citations

Kolesnikov, Alexander, Lucas Beyer, Xiaohua Zhai, et al.. (2019). Large Scale Learning of General Visual Representations for Transfer.. arXiv (Cornell University). 26 indexed citations

Zhai, Xiaohua, Joan Puigcerver, Alexander Kolesnikov, et al.. (2019). The Visual Task Adaptation Benchmark. arXiv (Cornell University). 22 indexed citations

Puigcerver, Joan, et al.. (2018). Probabilistic Indexing and Search for Information Extraction on Handwritten German Parish Records. 33. 44–49. 12 indexed citations

Toselli, Alejandro H., et al.. (2018). Probabilistic multi-word spotting in handwritten text images. Pattern Analysis and Applications. 22(1). 23–32. 14 indexed citations

Bluche, Théodore, Christopher Kermorvant, Joan Puigcerver, et al.. (2017). Preparatory KWS Experiments for Large-Scale Indexing of a Vast Medieval Manuscript Collection in the HIMANIS Project. SPIRE - Sciences Po Institutional REpository. 311–316. 17 indexed citations

Puigcerver, Joan. (2017). Are Multidimensional Recurrent Layers Really Necessary for Handwritten Text Recognition?. 67–72. 125 indexed citations

10.

Villegas, Mauricio, Joan Puigcerver, Alejandro H. Toselli, Joan Andreu Sánchez, & Enrique Vidal. (2016). Overview of the ImageCLEF 2016 Handwritten Scanned Document Retrieval Task.. CLEF (Working Notes). 233–253. 4 indexed citations

11.

Pratikakis, Ioannis, Konstantinos Zagoris, Basilis Gatos, et al.. (2016). ICFHR2016 Handwritten Keyword Spotting Competition (H-KWS 2016). RiuNet (Politechnical University of Valencia). 613–618. 21 indexed citations

12.

Puigcerver, Joan, Alejandro H. Toselli, & Enrique Vidal. (2016). Querying out-of-vocabulary words in lexicon-based keyword spotting. Neural Computing and Applications. 28(9). 2373–2382. 10 indexed citations

13.

Toselli, Alejandro H., Joan Puigcerver, & Enrique Vidal. (2016). Two Methods to Improve Confidence Scores for Lexicon-Free Word Spotting in Handwritten Text. RiuNet (Politechnical University of Valencia). 5. 349–354. 10 indexed citations

14.

Vidal, Enrique, Alejandro H. Toselli, & Joan Puigcerver. (2015). High performance Query-by-Example keyword spotting using Query-by-String techniques. 741–745. 11 indexed citations

15.

Puigcerver, Joan, Alejandro H. Toselli, & Enrique Vidal. (2015). Probabilistic interpretation and improvements to the HMM-filler for handwritten keyword spotting. 5. 731–735. 7 indexed citations

16.

Toselli, Alejandro H., Joan Puigcerver, & Enrique Vidal. (2015). Context-aware lattice based filler approach for key word spotting in handwritten documents. 5. 736–740. 6 indexed citations

17.

Puigcerver, Joan, Alejandro H. Toselli, & Enrique Vidal. (2015). ICDAR2015 Competition on Keyword Spotting for Handwritten Documents. 1176–1180. 23 indexed citations

18.

Puigcerver, Joan, Alejandro H. Toselli, & Enrique Vidal. (2014). Word-Graph-Based Handwriting Keyword Spotting of Out-of-Vocabulary Queries. 10. 2035–2040. 4 indexed citations

19.

Puigcerver, Joan, Alejandro H. Toselli, & Enrique Vidal. (2014). Word-Graph and Character-Lattice Combination for KWS in Handwritten Documents. 77. 181–186. 8 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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