Datasets
R. Vandaele, "Trash screen blockage detection using cameras and deep learning: code and dataset", University of Reading Research Data Archive, 2023. [doi] [link]
R. Vandaele, V. Ojha and SL Dance, "Deep learning for the estimation of water-levels using river cameras: networks and datasets", University of Reading Research Data Archive, 2021. [doi][link]
Published papers
R. Vandaele, V. Ojha and SL. Dance, "Calibrated river-level estimation from river-cameras using convolutional neural networks", Environmental Data Sciences, 2, E11, 2023. [doi] [pdf]
R. Vandaele, V. Ojha and SL. Dance, "Deep learning for automated river-level monitoring through river-camera images: An approach based on water segmentation and transfer learning", Hydrology and Earth System Sciences 25 (8), 4435-4453, 2022. [doi][pdf]
P. Jaikumar, R. Vandaele and V. Ojha, "Transfer learning for instance segmentation of waste bottles using Mask R-CNN algorithm", International Conference on Intelligent Systems Design and Applications, 140-149, 2020. [doi][arXiv]
R. Vandaele, SL. Dance and V. Ojha, "Automated water segmentation and river level detection on camera images using transfer learning", DAGM German Conference on Pattern Recognition, 232-245, 2020. [doi][pdf]
U. Rubens, R. Mormont, L. Paavolainen, V. Bäcker, B. Pavie, LA. Scholz, G. Michiels, M. Maška, D. Ünay, G. Ball, R. Hoyoux, R. Vandaele, O. Golani, SG. Stanciu, N. Sladoje, P. Paul-Gilloteaux, R. Marée and S. Tosi, "BIAFLOWS: A collaborative framework to reproducibly deploy and benchmark bioimage analysis workflows", Patterns 1 (3), 100040, 2020. [doi][bioRxiv]
R. Vandaele, J. Aceto, M. Muller, F. Peronnet, V. Debat, CW. Wang, CT. Huang, S. Jodogne, P. Martinive, P. Geurts and R. Marée, "Landmark detection in 2D bioimages for geometric morphometrics: a multi-resolution tree-based approach", Scientific reports 8 (1), 1-13, 2018. [doi][pdf]
R. Vandaele, F. Lallemand, P. Martinive, A. Gulyban, S. Jodogne, P. Coucke, P. Geurts and R. Marée, "Automated multimodal volume registration based on supervised 3d anatomical landmark detection", 12th International Conference on Computer Vision Theory and Applications (VISAPP 2017), 2017. [pdf]
R. Marée, L. Rollus, B. Stévens, R. Hoyoux, G. Louppe, R. Vandaele, JM. Begon, P. Kainz, P. Geurts and L. Wehenkel, "Collaborative analysis of multi-gigapixel imaging data using Cytomine", Bioinformatics 32 (9), 1395-1401, 2016. [doi][pdf]
R. Marée, L. Rollus, B. Stévens, R. Hoyoux, G. Louppe, R. Vandaele, JM. Begon, P. Kainz, P. Geurts and L. Wehenkel, "Cytomine: An open-source software for collaborative analysis of whole-slide images", Diagnostic Pathology 1 (8), 2016. [doi]
CW. Wang, CT. Huang, MC. Hsieh, CH. Li, SW. Chang, WC. Li, R. Vandaele, R. Marée, S. Jodogne, P. Geurts, C. Chen, G. Zheng, C. Chu, H. Mirzaalian, G. Hamarneh, T. Vrtovec and B. Ibragimov, "Evaluation and comparison of anatomical landmark detection methods for cephalometric x-ray images: a grand challenge", IEEE Transactions on Medical Imaging 34 (9), 2015. [doi][pdf]
R. Vandaele, R. Marée, S. Jodogne and P. Geurts, "Automatic cephalometric x-ray landmark detection challenge 2014: a tree-based algorithm", ISBI Conference, 2014. [pdf]
PhD thesis
R. Vandaele (supervised by Pierre Geurts and Raphael Marée), "Machine Learning for Landmark Detection in Biomedical Applications", ULiège, Faculté des Sciences Appliquées, Montefiore Institute, 2018. [link][pdf]