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Arnout Van Messem
Arnout Van Messem
University of Liège
Verifierad e-postadress på uliege.be
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Bouligand derivatives and robustness of support vector machines for regression
A Christmann, A Van Messem
Journal of Machine Learning Research 9 (May), 915-936, 2008
622008
On consistency and robustness properties of support vector machines for heavy-tailed distributions
A Christmann, I Steinwart, A van Messem
Statistics and Its Interface 2 (3), 311-327, 2009
482009
On consistency and robustness properties of support vector machines for heavy-tailed distributions
A Christmann, I Steinwart, A Van Messem
Statistics and Its Interface 2 (3), 311-327, 2009
482009
State of affairs of osteopathy in the Benelux: Benelux Osteosurvey 2013
PLS Van Dun, MA Nicolaie, A Van Messem
International Journal of Osteopathic Medicine 20, 3-17, 2016
412016
Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation
U Ozbulak, A Van Messem, W De Neve
International Conference on Medical Image Computing and Computer-Assisted …, 2019
252019
A review on consistency and robustness properties of support vector machines for heavy-tailed distributions
A Van Messem, A Christmann
Advances in data analysis and classification 4 (2), 199-220, 2010
72010
An automated model reduction method for biochemical reaction networks
M Gasparyan, A Van Messem, S Rao
Symmetry 12 (8), 1321, 2020
52020
Support vector machines: A robust prediction method with applications in bioinformatics
A Van Messem
Handbook of Statistics 43, 391-466, 2020
52020
Box-Scan: An efficient and effective algorithm for box dimension measurement in conveyor systems using a single RGB-D camera
HM Park, A Van Messem, W De Neve
Proceedings of the 7th IIAE International Conference on Industrial …, 2019
42019
How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques
B Vandenberghe, S Depuydt, A Van Messem
OSF Preprints, 2018
42018
How the softmax output is misleading for evaluating the strength of adversarial examples
U Ozbulak, W De Neve, A Van Messem
NeurIPS 2018: 32nd Conference on Neural Information Processing Systems …, 2018
42018
A novel technique for model reduction of biochemical reaction networks
M Gasparyan, A Van Messem, S Rao
IFAC-PapersOnLine 51 (19), 28-31, 2018
42018
Towards a quantitative analysis of class activation mapping for deep learning-based computer-aided diagnosis
H Kang, H Park, Y Ahn, A Van Messem, W De Neve
Medical Imaging 2021: Image Perception, Observer Performance, and Technology …, 2021
32021
Investigating the significance of adversarial attacks and their relation to interpretability for radar-based human activity recognition systems
U Ozbulak, B Vandersmissen, A Jalalvand, I Couckuyt, A Van Messem, ...
Computer Vision and Image Understanding 202, 103111, 2021
32021
Perturbation analysis of gradient-based adversarial attacks
U Ozbulak, M Gasparyan, W De Neve, A Van Messem
Pattern Recognition Letters 135, 313-320, 2020
32020
Bouligand derivatives and robustness of support vector machines
A Christmann, A Van Messem
Technical Report, 2007
32007
Automatic Detection of Trypanosomosis in Thick Blood Smears Using Image Pre-processing and Deep Learning
T Jung, ET Anzaku, U Özbulak, S Magez, AV Messem, WD Neve
International Conference on Intelligent Human Computer Interaction, 254-266, 2020
22020
Selection of Source Images Heavily Influences the Effectiveness of Adversarial Attacks
U Ozbulak, ET Anzaku, W De Neve, A Van Messem
arXiv preprint arXiv:2106.07141, 2021
12021
Item measurement for logistics-oriented belt conveyor systems using a scenario-driven approach and automata-based control design
H Park, A Van Messem, W De Neve
2020 IEEE 7th International Conference on Industrial Engineering and …, 2020
12020
Not All Adversarial Examples Require a Complex Defense: Identifying Over-optimized Adversarial Examples with IQR-based Logit Thresholding
U Ozbulak, A Van Messem, W De Neve
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
12019
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Artiklar 1–20