| Multi-loss weighting with coefficient of variations R Groenendijk, S Karaoglu, T Gevers, T Mensink Proceedings of the IEEE/CVF winter conference on applications of computer …, 2021 | 48 | 2021 |
| On the benefit of adversarial training for monocular depth estimation R Groenendijk, S Karaoglu, T Gevers, T Mensink Computer Vision and Image Understanding 190, 102848, 2020 | 32 | 2020 |
| Geometric back-propagation in morphological neural networks R Groenendijk, L Dorst, T Gevers IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 7 | 2023 |
| Towards Mesh-based Deep Learning for Semantic Segmentation in Photogrammetry M Knott, R Groenendijk ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2021 | 7 | 2021 |
| MorphPool: Efficient Non-linear Pooling & Unpooling in CNNs R Groenendijk, L Dorst, T Gevers 33rd British Machine Vision Conference 2022, 2022 | 3 | 2022 |
| Benefits of social learning in physical robots J Heinerman, B Bussmann, R Groenendijk, E Van Krieken, J Slik, A Tezza, ... 2018 IEEE Symposium Series on Computational Intelligence (SSCI), 851-858, 2018 | 2 | 2018 |
| Progress on climate action: a multilingual machine learning analysis of the global stocktake AJ Sietsma, RW Groenendijk, R Biesbroek Climatic Change 176 (12), 173, 2023 | 1 | 2023 |
| HaarNet: Large-scale Linear-Morphological Hybrid Network for RGB-D Semantic Segmentation R Groenendijk, L Dorst, T Gevers arXiv preprint arXiv:2310.07669, 2023 | | 2023 |
| Going into depth: Learning morphological aspects in data modalities using neural networks RW Groenendijk | | 2023 |
| A Deep Learning Approach to Landmark Detection in Facial Images R Groenendijk University of Twente Students Journal of Biometrics and Computer Vision, 2016 | | 2016 |
Theo GeversComputer Vision Research Group, University of Amsterdam (UvA); 3DUniversumVerified email at uva.nl
