Pierre Geurts
Impact in
- Artificial Intelligence top 0.5%
- Biophysics top 0.5%
- Cell Image Analysis Techniques
Papers in
-
- Cell Image Analysis Techniques 9
-
- Image Retrieval and Classification Techniques 11
- Advanced Image and Video Retrieval Techniques 8
Pierre Geurts
102 papers receiving 13.3k citations
Hit Papers
Peers
Comparison fields: 5 of 228
- Artificial Intelligence 2.5k
- Biophysics 409
- Molecular Biology 4.6k
- Immunology 1.3k
- Cancer Research 879
Countries citing papers authored by Pierre Geurts
This map shows the geographic impact of Pierre Geurts'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 Pierre Geurts with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pierre Geurts more than expected).
Fields of papers citing papers by Pierre Geurts
This network shows the impact of papers produced by Pierre Geurts. 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 Pierre Geurts. The network helps show where Pierre Geurts may publish in the future.
Co-authors
The 25 scholars most cited alongside Pierre Geurts, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Improving the Training of Deep Convolutional Neural Networks for Art Classification: from Transfer Learning to Multi-Task Learning | 2019 | 1 |
| 2 | 2018 | 14 | |
| 3 | 2018 | 31 | |
| 4 | 2017 | 1 | |
| 5 | Globally Induced Forest: A Prepruning Compression Scheme | 2017 | 5 |
| 6 | 2015 | 9 | |
| 7 | 2015 | 49 | |
| 8 | Automatic Cephalometric X-Ray Landmark Detection Challenge 2014: A tree-based algorithm | 2014 | 9 |
| 9 | Data normalization and supervised learning to assess the condition of patients with multiple sclerosis based on gait analysis | 2014 | 1 |
| 10 | Understanding variable importances in forests of randomized trees Hit paper breakdown → | 2013 | 554 |
| 11 | Inferring gene regulatory networks from expression data using tree-based methods | 2011 | 3 |
| 12 | Learning from positive and unlabeled examples by enforcing statistical signicance | 2011 | 5 |
| 13 | Regulatory network inference with GENIE3: application to the DREAM5 challenge | 2010 | 2 |
| 14 | Inferring Regulatory Networks from Expression Data Using Tree-Based Methods Hit paper breakdown → | 2010 | 1257 |
| 15 | 2009 | 164 | |
| 16 | Random Subwindows and Randomized Trees for Image Retrieval, Classification, and Annotation | 2007 | 4 |
| 17 | 2005 | 28 | |
| 18 | Tree-Based Batch Mode Reinforcement Learning Hit paper breakdown → | 2005 | 478 |
| 19 | 2001 | 6 | |
| 20 | Data mining tools and application in power system engineering | 1999 | 5 |
About Pierre Geurts
Pierre Geurts is a scholar working on Biophysics, Computer Vision and Pattern Recognition, Artificial Intelligence, Music and Media Technology, having authored 104 papers that have together received 13.7k indexed citations. Recurring topics across this work include Gene expression and cancer classification (17 papers), Image Retrieval and Classification Techniques (11 papers), Bioinformatics and Genomic Networks (10 papers), Cell Image Analysis Techniques (9 papers), Neural Networks and Applications (8 papers), Advanced Image and Video Retrieval Techniques (8 papers), Machine Learning and Data Classification (7 papers) and Gene Regulatory Network Analysis (7 papers). The work is most often cited by research in Artificial Intelligence (2.5k citations), Biophysics (409 citations), Molecular Biology (4.6k citations), Immunology (1.3k citations) and Cancer Research (879 citations). Pierre Geurts has collaborated with scholars based in Belgium, France and Germany. Frequent co-authors include Louis Wehenkel, Damien Ernst, Vân Anh Huynh‐Thu, Alexandre Irrthum, Gert Hulselmans, Stein Aerts, Joost van den Oord, Hana Imrichová, Jasper Wouters and Florian Rambow. Their work appears in journals such as PLoS ONE, Machine Learning, Scientific Reports, Bioinformatics and Frontiers in Genetics.
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.