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Toon Van Craenendonck
Toon Van Craenendonck
Verified email at cs.kuleuven.be - Homepage
Title
Cited by
Cited by
Year
Using internal validity measures to compare clustering algorithms
T Van Craenendonck, H Blockeel
Benelearn 2015 Poster presentations (online), 1-8, 2015
1012015
Combination of snapshot hyperspectral retinal imaging and optical coherence tomography to identify Alzheimer’s disease patients
S Lemmens, T Van Craenendonck, J Van Eijgen, L De Groef, R Bruffaerts, ...
Alzheimer's research & therapy 12 (1), 144, 2020
752020
Age and sex affect deep learning prediction of cardiometabolic risk factors from retinal images
N Gerrits, B Elen, TV Craenendonck, D Triantafyllidou, IN Petropoulos, ...
Scientific reports 10 (1), 9432, 2020
712020
Constraint-based Clustering Selection
T Van Craenendonck, H Blockeel
Machine Learning, 2018
462018
COBRA: A fast and simple method for active clustering with pairwise constraints
T Van Craenendonck, S Dumancic, H Blockeel
International Joint Conference on Artificial Intelligence (IJCAI) 2017, 2017
452017
wannesm/dtaidistance v2. 0.0
W Meert, K Hendrickx, T Van Craenendonck
Zenodo, 2020
432020
Hyperspectral imaging and the retina: worth the wave?
S Lemmens, J Van Eijgen, K Van Keer, J Jacob, S Moylett, L De Groef, ...
Translational vision science & technology 9 (9), 9-9, 2020
422020
Systematic comparison of heatmapping techniques in deep learning in the context of diabetic retinopathy lesion detection
T Van Craenendonck, B Elen, N Gerrits, P De Boever
Translational vision science & technology 9 (2), 64-64, 2020
342020
COBRASTS: A New Approach to Semi-supervised Clustering of Time Series
T Van Craenendonck, W Meert, S Dumančić, H Blockeel
International conference on discovery science, 179-193, 2018
282018
Cobras: Interactive clustering with pairwise queries
T Van Craenendonck, S Dumančić, E Van Wolputte, H Blockeel
International Symposium on Intelligent Data Analysis, 353-366, 2018
282018
COBRAS: fast, iterative, active clustering with pairwise constraints
T Van Craenendonck, S Dumančić, E Van Wolputte, H Blockeel
arXiv preprint arXiv:1803.11060, 2018
142018
wannesm/dtaidistance: v2. 3.5
K Wannesm, A Yurtman, P Robberechts, D Vohl, E Ma, G Verbruggen, ...
Zenodo: Genève, Switzerland, 2022
132022
Dtaidistance (version v2)
W Meert, K Hendrickx, T Van Craenendonck, P Robberechts, H Blockeel, ...
last Accessed, 04-14, 2023
122023
Retinal microvascular complexity comparing mono‐and multifractal dimensions in relation to cardiometabolic risk factors in a Middle Eastern population
T Van Craenendonck, N Gerrits, B Buelens, IN Petropoulos, A Shuaib, ...
Acta Ophthalmologica, 2020
122020
Tackling noise in active semi-supervised clustering
J Soenen, S Dumančić, T Van Craenendonck, H Blockeel
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020
72020
DTAIDistance (Version v2). Zenodo
W Meert, K Hendrickx, T Van Craenendonck, P Robberechts
62022
DTAIDistance. Zenodo
W Meert, K Hendrickx, T Van Craenendonck, P Robberechts, H Blockeel, ...
62020
DTAIDistance (2022)
W Meert, K Hendrickx, T Van Craenendonck, P Robberechts, H Blockeel, ...
URL https://github. com/wannesm/dtaidistance, 0
6
System and method for evaluating a performance of explainability methods used with artificial neural networks
E Bart, N GERRITS, T VAN CRAENENDONCK, P de Boever
US Patent App. 17/342,228, 2021
52021
wannesm/dtaidistance: v2. 3.5
A Yurtman, P Robberechts, D Vohl, E Ma, G Verbruggen, M Rossi, ...
Zenodo, 2021
52021
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