Cor J. Veenman

3.2k total citations · 1 hit paper
45 papers, 1.7k citations indexed

About

Cor J. Veenman is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Cor J. Veenman has authored 45 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 19 papers in Computer Vision and Pattern Recognition and 6 papers in Information Systems. Recurrent topics in Cor J. Veenman's work include Advanced Image and Video Retrieval Techniques (6 papers), Digital and Cyber Forensics (5 papers) and Imbalanced Data Classification Techniques (4 papers). Cor J. Veenman is often cited by papers focused on Advanced Image and Video Retrieval Techniques (6 papers), Digital and Cyber Forensics (5 papers) and Imbalanced Data Classification Techniques (4 papers). Cor J. Veenman collaborates with scholars based in Netherlands, United States and France. Cor J. Veenman's co-authors include Marcel Reinders, E. Backer, Jan van Gemert, Jan‐Mark Geusebroek, A.W.M. Smeulders, Cees G. M. Snoek, David M. J. Tax, Laura van ‘t Veer, Lodewyk F.A. Wessels and Yudong D. He and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Remote Sensing of Environment and IEEE Transactions on Image Processing.

In The Last Decade

Cor J. Veenman

39 papers receiving 1.6k 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.

Visual Word Ambiguity

2009 512 citations Jan van Gemert, Cor J. Veenman et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers

Cor J. Veenman

CVPR

AI

MT

SP

MB

Fanhua Shang China

Hamid R. Rabiee Iran

Xinzhong Zhu China

Xianglong Tang China

Jyri Kivinen United Kingdom

Rajat Raina United States

E. Backer Netherlands

Yazhou Ren China

Linli Xu China

宏治津田 Japan

Fanhua Shang China

Cor J. Veenman

1.2k ×1.1

CVPR

741 ×1.2

AI

349 ×1.7

MT

251 ×1.5

SP

92 ×0.7

MB

Citations per year, relative to Cor J. Veenman Cor J. Veenman (= 1×) peers Fanhua Shang

Countries citing papers authored by Cor J. Veenman

Since Specialization

Citations

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

Fields of papers citing papers by Cor J. Veenman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cor J. Veenman. 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 Cor J. Veenman. The network helps show where Cor J. Veenman may publish in the future.

Co-authorship network of co-authors of Cor J. Veenman

This figure shows the co-authorship network connecting the top 25 collaborators of Cor J. Veenman. A scholar is included among the top collaborators of Cor J. Veenman 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 Cor J. Veenman. Cor J. Veenman 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

1.

Veenman, Cor J., et al.. (2024). Gender mobility in the labor market with skills-based matching models. AI and Ethics. 4(1). 163–167.

2.

Steen, Marc, Joachim de Greeff, Maaike de Boer, & Cor J. Veenman. (2024). Ethical aspects of ChatGPT: An approach to discuss and evaluate key requirements from different ethical perspectives. AI and Ethics. 5(3). 2419–2432.

3.

Takes, Frank W., et al.. (2023). Fair tree classifier using strong demographic parity. Machine Learning. 113(5). 3305–3324. 3 indexed citations

4.

Herik, H.J. van den, et al.. (2022). Fair automated assessment of noncompliance in cargo ship networks. EPJ Data Science. 11(1). 1 indexed citations

5.

Veenman, Cor J., et al.. (2021). Supervised temporal link prediction in large-scale real-world networks. Social Network Analysis and Mining. 11(1). 4 indexed citations

6.

Manintveld, Olivier C., et al.. (2021). Prediction of long-term hospitalisation and all-cause mortality in patients with chronic heart failure on Dutch claims data: a machine learning approach. BMC Medical Informatics and Decision Making. 21(1). 303–303. 5 indexed citations

7.

Vliet, Jasper van, et al.. (2021). Improving evaluation of NO2 emission from ships using spatial association on TROPOMI satellite data. Leiden Repository (Leiden University). 454–457. 4 indexed citations

8.

Veenman, Cor J., et al.. (2013). Authorship Verification with Compression Features.. CLEF (Working Notes). 8 indexed citations

9.

Veenman, Cor J., et al.. (2012). Bootstrapped Authorship Attribution in Compression Space.. 1 indexed citations

10.

Geradts, Zeno, Katrin Franke, & Cor J. Veenman. (2009). Computational Forensics : Third International Workshop, IWCF 2009, The Hague, The Netherlands, August 13-14, 2009. Proceedings. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 1 indexed citations

11.

Alles, Erwin J., Zeno Geradts, & Cor J. Veenman. (2009). Source Camera Identification for Heavily JPEG Compressed Low Resolution Still Images*. Journal of Forensic Sciences. 54(3). 628–638. 21 indexed citations

12.

Veenman, Cor J.. (2007). Statistical Disk Cluster Classification for File Carving. 393–398. 12 indexed citations

13.

Wessels, Lodewyk F.A., Marcel Reinders, A.A.M. Hart, et al.. (2005). A protocol for building and evaluating predictors of disease state based on microarray data. Computer applications in the biosciences. 21(19). 3755–3762. 106 indexed citations

14.

Snoek, Cees G. M., Jan van Gemert, Jan‐Mark Geusebroek, et al.. (2005). The MediaMill TRECVID 2005 Semantic Video Search Engine (Draft Version).. TRECVID.

15.

Veenman, Cor J. & David M. J. Tax. (2005). LESS: a model-based classifier for sparse subspaces. IEEE Transactions on Pattern Analysis and Machine Intelligence. 27(9). 1496–1500. 26 indexed citations

16.

Tax, David M. J. & Cor J. Veenman. (2005). Tuning the hyperparameter of an AUC-optimized classifier. UvA-DARE (University of Amsterdam). 224–231. 8 indexed citations

17.

Veenman, Cor J., et al.. (2005). The nearest subclass classifier: a compromise between the nearest mean and nearest neighbor classifier. IEEE Transactions on Pattern Analysis and Machine Intelligence. 27(9). 1417–1429. 107 indexed citations

18.

Veenman, Cor J., et al.. (2004). Groups of Collaborating Users and Agents in Ambient Intelligent Environments. Adaptive Agents and Multi-Agents Systems. 1320–1321. 5 indexed citations

19.

Veenman, Cor J., Marcel Reinders, & E. Backer. (2003). Establishing motion correspondence using extended temporal scope. Artificial Intelligence. 145(1-2). 227–243. 8 indexed citations

20.

Veenman, Cor J., Marcel Reinders, & E. Backer. (2003). A cellular coevolutionary algorithm for image segmentation. IEEE Transactions on Image Processing. 12(3). 304–316. 26 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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