Rick’s Webpage

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I am now officially a doctor!

I acquired my PhD in Computer Vision & Mathematical Morphology at the Computer Vision Lab at the University of Amsterdam. I was supervised by dr. Leo Dorst and Prof. dr. Theo Gevers. My research interest is mathematical morphology in the context of deep learning, specifically how morphological operators can be integrated in contemporary neural networks.

Thesis

My thesis is titled “Going into Depth: Large Learning Morphological Aspects in Data Modalities using Neural Networks”. I successfully defended my thesis on October 23rd, 2023. It is available for reading at the UvA’s thesis repository.

Publications

Groenendijk, R., Dorst, L., Gevers, T. (2023). Geometric Back-Propagation in Morphological Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). [paper][github]

Groenendijk, R., Dorst, L., Gevers, T. (2023). HaarNet: Large-scale Linear-Morphological Hybrid Network for RGB-D Semantic Segmentation. arXiv preprint arXiv:2310.07669. [paper]

Groenendijk, R., Dorst, L., Gevers, T. (2022). MorphPool: Efficient Non-linear Pooling & Unpooling in CNNs. 33rd British Machine Vision Conference 2022. [paper][github]

Groenendijk, R., Karaoglu, S., Gevers, T., & Mensink, T. (2021). Multi-loss weighting with coefficient of variations. In Proceedings of the IEEE/CVF winter conference on applications of computer vision (pp. 1469-1478). [paper][github]

Knott, M., & Groenendijk, R. (2021). Towards Mesh-Based Deep Learning for Semantic Segmentation in Photogrammetry. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2, 59-66. [paper]

Groenendijk, R., Karaoglu, S., Gevers, T., & Mensink, T. (2020). On the benefit of adversarial training for monocular depth estimation. Computer Vision and Image Understanding, 190, 102848. [paper][github]

Heinerman, J., Bussmann, B., Groenendijk, R., Van Krieken, E., Slik, J., Tezza, A., & Eiben, A. E. (2018, November). Benefits of social learning in physical robots. In 2018 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 851-858). IEEE. [paper]

^{Thanks to Wei Wang for the template!}