Rolf Ingold

3.1k total citations
146 papers, 1.6k citations indexed

About

Rolf Ingold is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Rolf Ingold has authored 146 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 114 papers in Computer Vision and Pattern Recognition, 42 papers in Artificial Intelligence and 17 papers in Information Systems. Recurrent topics in Rolf Ingold's work include Handwritten Text Recognition Techniques (99 papers), Image Retrieval and Classification Techniques (46 papers) and Image Processing and 3D Reconstruction (36 papers). Rolf Ingold is often cited by papers focused on Handwritten Text Recognition Techniques (99 papers), Image Retrieval and Classification Techniques (46 papers) and Image Processing and 3D Reconstruction (36 papers). Rolf Ingold collaborates with scholars based in Switzerland, Tunisia and Germany. Rolf Ingold's co-authors include Jean Hennebert, Marcus Liwicki, Fouad Slimane, Mathias Seuret, Adel M. Alimi, Slim Kanoun, Denis Lalanne, Najoua Essoukri Ben Amara, Andreas Fischer and Kai Chen and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition Letters and Computers in Biology and Medicine.

In The Last Decade

Rolf Ingold

138 papers receiving 1.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Rolf Ingold Switzerland	22	1.4k	446	374	124	118	146	1.6k
Junfeng He United States	21	1.8k 1.3×	419 0.9×	300 0.8×	80 0.6×	101 0.9×	33	2.1k
Dzulkifli Mohamad Malaysia	17	672 0.5×	249 0.6×	172 0.5×	54 0.4×	111 0.9×	79	939
Toru Wakahara Japan	14	985 0.7×	310 0.7×	239 0.6×	49 0.4×	66 0.6×	54	1.1k
Srirangaraj Setlur United States	17	732 0.5×	205 0.5×	190 0.5×	36 0.3×	119 1.0×	81	948
Simone Marinai Italy	17	659 0.5×	247 0.6×	100 0.3×	85 0.7×	77 0.7×	61	903
Jonathan J. Hull United States	19	599 0.4×	269 0.6×	82 0.2×	73 0.6×	50 0.4×	71	854
M.C. Fairhurst United Kingdom	20	829 0.6×	579 1.3×	205 0.5×	200 1.6×	267 2.3×	145	1.4k
Pınar Duygulu Türkiye	21	1.3k 1.0×	488 1.1×	129 0.3×	138 1.1×	144 1.2×	73	1.7k
Hung-Hsu Tsai Taiwan	17	702 0.5×	136 0.3×	117 0.3×	57 0.5×	92 0.8×	51	951
M. Ortega United States	8	1.3k 1.0×	253 0.6×	163 0.4×	44 0.4×	169 1.4×	12	1.5k

Countries citing papers authored by Rolf Ingold

Since Specialization

Citations

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

Fields of papers citing papers by Rolf Ingold

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rolf Ingold

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

All Works

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20 of 20 papers shown

Fischer, Andreas, et al.. (2023). DIVA-DAF: A Deep Learning Framework for Historical Document Image Analysis. ArODES (HES-SO (https://www.hes-so.ch/)). 61–66. 1 indexed citations

Ingold, Rolf, et al.. (2023). Historical document image analysis using controlled data for pre-training. International Journal on Document Analysis and Recognition (IJDAR). 26(3). 241–254. 3 indexed citations

Hennebert, Jean, et al.. (2018). Multi‐dimensional long short‐term memory networks for artificial Arabic text recognition in news video. IET Computer Vision. 12(5). 710–719. 20 indexed citations

Hennebert, Jean, et al.. (2018). Open Datasets and Tools for Arabic Text Detection and Recognition in News Video Frames. Journal of Imaging. 4(2). 32–32. 12 indexed citations

Seuret, Mathias, et al.. (2017). ICDAR2017 Competition on Layout Analysis for Challenging Medieval Manuscripts. 1361–1370. 26 indexed citations

Ingold, Rolf, et al.. (2016). DIVAServices-Spotlight - Experimenting with Document Image Analysis Methods in the Web.. DH. 414–417. 1 indexed citations

Ingold, Rolf, et al.. (2016). DivaServices—A RESTful web service for Document Image Analysis methods. Digital Scholarship in the Humanities. fqw051–fqw051. 7 indexed citations

Seuret, Mathias, et al.. (2016). DIVA-HisDB: A Precisely Annotated Large Dataset of Challenging Medieval Manuscripts. 471–476. 51 indexed citations

Zufferey, Damien, Thomas Höfer, Jean Hennebert, et al.. (2015). Performance comparison of multi-label learning algorithms on clinical data for chronic diseases. Computers in Biology and Medicine. 65. 34–43. 51 indexed citations

10.

Hao, Wei, Kai Chen, Anguelos Nicolaou, Marcus Liwicki, & Rolf Ingold. (2014). Investigation of feature selection for historical document layout analysis. 1. 1–6. 7 indexed citations

11.

Fischer, Andreas, et al.. (2012). HisDoc: Historical Document Analysis, Recognition, and Retrieval.. DH. 94–96. 3 indexed citations

12.

Carrino, Francesco, Antonio Ridi, Elena Mugellini, Omar Abou Khaled, & Rolf Ingold. (2012). Gesture Segmentation and Recognition with an EMG-Based Intimate Approach - An Accuracy and Usability Study. 33. 544–551. 2 indexed citations

13.

Ingold, Rolf, et al.. (2008). Recognition of Ultra Low Resolution Word Images Using HMMs.. 429–436. 1 indexed citations

14.

Behera, Ardhendu, Denis Lalanne, & Rolf Ingold. (2005). Enhancement of layout-based identification of low-resolution documents using geometrical color distribution. Edge Hill University Research Information Repository (Edge Hill University). 468–472 Vol. 1. 1 indexed citations

15.

Lalanne, Denis, et al.. (2004). Thematic segmentation of meetings through document/speech alignment. 804–811. 5 indexed citations

16.

Lalanne, Denis, et al.. (2003). A research agenda for assessing the utility of document annotations in multimedia databases of meeting recordings.. Edge Hill University Research Information Repository (Edge Hill University). 47–55. 8 indexed citations

17.

Ingold, Rolf, et al.. (1999). Using XML in Document Recognition. 2 indexed citations

18.

Ingold, Rolf, et al.. (1999). Analysis of synthetic document images. 374–377. 5 indexed citations

19.

Ingold, Rolf. (1989). Text structure recognition in optical reading. Cambridge University Press eBooks. 133–142. 2 indexed citations

20.

Ingold, Rolf, et al.. (1988). Structure recognition of printed documents. International Conference on Electronic Publishing. 59–70. 4 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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