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Arnout Van Messem
Arnout Van Messem
University of Liège
Verified email at uliege.be
Title
Cited by
Cited by
Year
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
712019
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
642008
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
532016
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
532009
How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques
N Harandi, B Vandenberghe, J Vankerschaver, S Depuydt, ...
Plant Methods 19 (1), 60, 2023
22*2023
Know your self-supervised learning: A survey on image-based generative and discriminative training
U Ozbulak, HJ Lee, B Boga, ET Anzaku, H Park, A Van Messem, ...
arXiv preprint arXiv:2305.13689, 2023
172023
Rethinking protein drug design with highly accurate structure prediction of anti-CRISPR proteins
H Park, Y Park, J Vankerschaver, A Van Messem, W De Neve, H Shim
Pharmaceuticals 15 (3), 310, 2022
142022
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
142021
Support vector machines: A robust prediction method with applications in bioinformatics
A Van Messem
Handbook of Statistics 43, 391-466, 2020
142020
An automated model reduction method for biochemical reaction networks
M Gasparyan, A Van Messem, S Rao
Symmetry 12 (8), 1321, 2020
132020
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
122019
MP-Net: Deep learning-based segmentation for fluorescence microscopy images of microplastics isolated from clams
H Park, S Park, MK de Guzman, JY Baek, T Cirkovic Velickovic, ...
Plos one 17 (6), e0269449, 2022
112022
Perturbation analysis of gradient-based adversarial attacks
U Ozbulak, M Gasparyan, W De Neve, A Van Messem
Pattern Recognition Letters 135, 313-320, 2020
112020
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
102021
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
92020
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
92010
In silico optimization of RNA–protein interactions for CRISPR-Cas13-based antimicrobials
H Park, Y Park, U Berani, E Bang, J Vankerschaver, A Van Messem, ...
Biology Direct 17 (1), 27, 2022
82022
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
82018
A novel technique for model reduction of biochemical reaction networks
M Gasparyan, A Van Messem, S Rao
IFAC-PapersOnLine 51 (19), 28-31, 2018
62018
Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation. arXiv 2019
U Ozbulak, A Van Messem, W De Neve
arXiv preprint arXiv:1907.13124, 0
6
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