Jochen Maydt

3.3k total citations · 1 hit paper
6 papers, 2.2k citations indexed

About

Jochen Maydt is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Infectious Diseases. According to data from OpenAlex, Jochen Maydt has authored 6 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Molecular Biology, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Infectious Diseases. Recurrent topics in Jochen Maydt's work include Face and Expression Recognition (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and HIV Research and Treatment (1 paper). Jochen Maydt is often cited by papers focused on Face and Expression Recognition (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and HIV Research and Treatment (1 paper). Jochen Maydt collaborates with scholars based in Germany, United States and Sweden. Jochen Maydt's co-authors include Rainer Lienhart, Thomas Lengauer, Francisco S. Domingues, Jörg Rahnenführer, Christoph Welsch, Martin Welker, Stefan Zeuzem, Mario Albrecht, Axel J. Scheidig and Eva Herrmann and has published in prestigious journals such as Bioinformatics, Retrovirology and Journal of Molecular Graphics and Modelling.

In The Last Decade

Jochen Maydt

6 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

An extended set of Haar-like features for rapid object detection

2003 2.0k citations Rainer Lienhart, Jochen Maydt Proceedings - International Conference on Image Processing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jochen Maydt Germany	5	1.5k	262	214	200	185	6	2.2k
Jordi Gonzàlez Spain	26	1.6k 1.1×	257 1.0×	526 2.5×	111 0.6×	108 0.6×	117	2.4k
Narciso Garcı́a Spain	26	1.9k 1.2×	323 1.2×	241 1.1×	444 2.2×	234 1.3×	273	2.7k
Dah-Jye Lee United States	27	985 0.6×	57 0.2×	295 1.4×	120 0.6×	279 1.5×	147	2.2k
Douglas Chai Australia	20	1.7k 1.1×	415 1.6×	243 1.1×	235 1.2×	96 0.5×	87	2.7k
Alex Zelinsky Australia	18	1.2k 0.8×	349 1.3×	208 1.0×	53 0.3×	336 1.8×	50	1.8k
Ming Ouhyoung Taiwan	25	2.2k 1.4×	1.1k 4.1×	179 0.8×	112 0.6×	220 1.2×	113	4.0k
Giovanni Maria Farinella Italy	24	1.5k 1.0×	135 0.5×	452 2.1×	85 0.4×	135 0.7×	185	2.3k
Niels da Vitoria Lobo United States	18	1.3k 0.8×	291 1.1×	244 1.1×	183 0.9×	54 0.3×	61	1.9k
Neill Campbell United Kingdom	18	1000 0.7×	61 0.2×	162 0.8×	123 0.6×	104 0.6×	73	1.4k
Takayoshi Yamashita Japan	20	1.0k 0.7×	82 0.3×	508 2.4×	67 0.3×	121 0.7×	139	2.5k

Countries citing papers authored by Jochen Maydt

Since Specialization

Citations

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

Fields of papers citing papers by Jochen Maydt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jochen Maydt

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

All Works

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6 of 6 papers shown

1.

Maydt, Jochen, Oliver Frank, Alessia Ruggieri, et al.. (2007). Expression pattern analysis of transcribed HERV sequences is complicated by ex vivorecombination. Retrovirology. 4(1). 39–39. 20 indexed citations

2.

Welsch, Christoph, Mario Albrecht, Jochen Maydt, et al.. (2007). Structural and functional comparison of the non-structural protein 4B in flaviviridae. Journal of Molecular Graphics and Modelling. 26(2). 546–557. 29 indexed citations

3.

Maydt, Jochen & Thomas Lengauer. (2006). Recco: recombination analysis using cost optimization. Bioinformatics. 22(9). 1064–1071. 92 indexed citations

4.

Rahnenführer, Jörg, Francisco S. Domingues, Jochen Maydt, & Thomas Lengauer. (2004). Calculating the Statistical Significance of Changes in Pathway Activity From Gene Expression Data. Statistical Applications in Genetics and Molecular Biology. 3(1). 1–29. 91 indexed citations

5.

Maydt, Jochen & Rainer Lienhart. (2003). A fast method for training support vector machines with a very large set of linear features. 309–312. 4 indexed citations

6.

Lienhart, Rainer & Jochen Maydt. (2003). An extended set of Haar-like features for rapid object detection. Proceedings - International Conference on Image Processing. 1. I–900. 1965 indexed citations breakdown →

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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