Vandaele, R., Dance, S. L.
ORCID: https://orcid.org/0000-0003-1690-3338 and Ojha, V.
ORCID: https://orcid.org/0000-0002-9256-1192
(2023)
Calibrated river-level estimation from river cameras using convolutional neural networks.
Environmental Data Science, 2.
e11.
ISSN 2634-4602
doi: 10.1017/eds.2023.6
Vandaele, R., Aceto, J., Muller, M., Péronnet, F., Debat, V., Wang, C.-W., Huang, C.-T., Jodogne, S., Martineve, P., Geurts, P. and Marée, R. (2018) Landmark detection in 2D bioimages for geometric morphometrics: a multi-resolution tree-based approach. Scientific Reports, 8 (1). 538. ISSN 2045-2322 doi: 10.1038/s41598-017-18993-5
Marée, R., Rollus, L., Stévens, B., Hoyoux, R., Louppe, G., Vandaele, R., Begon, J.-M., Kainz, P., Geurts, P. and Wehenkel, L. (2016) Collaborative analysis of multi-gigapixel imaging data using Cytomine. Bioinformatics, 32 (9). pp. 1395-1401. ISSN 1460-2059 doi: 10.1093/bioinformatics/btw013
Wang, C.-W., Huang, C.-T., Hsieh, M.-C., Li, C. H., Chang, S.-W., Li, W.-C., Vandaele, R., Marée, R., Jodogne, S., Geurts, P., Chen, C., Zheng, G., Chu, C., Mirzaalian, H., Hamarneh, G., Vrtovec, T. and Ibragimov, B. (2015) Evaluation and comparison of anatomical landmark detection methods for cephalometric X-Ray images: a grand challenge. IEEE Transactions on Medical Imaging, 34 (9). pp. 1890-1900. ISSN 1558-254X doi: 10.1109/TMI.2015.2412951
Jaikumar, P., Vandaele, R. and Ojha, V.
ORCID: https://orcid.org/0000-0002-9256-1192
(2021)
Transfer learning for instance segmentation of waste bottles using Mask R-CNN algorithm.
In: International Conference on Intelligent Systems Design and Applications, 2020-12-12 - 2020-12-15, https://link.springer.com/conference/isda, pp. 140-149.
doi: 10.1007/978-3-030-71187-0_13
(Intelligent Systems Design and Applications. ISDA 2020. Advances in Intelligent Systems and Computing, vol 1351.)
Vandaele, R., Dance, S.
ORCID: https://orcid.org/0000-0003-1690-3338 and Ojha, V.
ORCID: https://orcid.org/0000-0002-9256-1192
(2021)
Automated water segmentation and river level detection on camera images using transfer learning.
In: 42nd German Conference on Pattern Recognition (DAGM GCPR 2020), 2021-03-17, pp. 232-245.
doi: 10.1007/978-3-030-71278-5