PhD Researcher
Campus du Solbosch - CP 165/57
Avenue F.D. Roosevelt, 50
1050 Bruxelles
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PhD Thesis
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"Assessing Intellectual Property Relevant Similarities In Images Through Algorithmic Decision Systems" (Under supervision of Pr. Olivier Debeir and Pr. Julien Cabay)
This PhD Thesis, funded by an ARC (Action de Recherche Concertée) at ULB, is at the crossroads of Deep-Learning and Intellectual Property. This project aims at assessing Intellectual Property (IP) relevant similarities, with a focus on image recognition technologies. Current Algorithmic decisions systems are developed by private companies for the purposes of IP enforcement (monitoring infringing goods online, filtering out content) and registration by IP Offices.
We aim at exposing the biases of such systems, and propose new, unbiased and open-source algorithms for these decisions systems. -
Masaai Project
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"Assessing Intellectual Property Relevant Similarities In Images Through Algorithmic Decision Systems" (Under supervision of Pr. Olivier Debeir and Pr. Julien Cabay)
This PhD Thesis, funded by an ARC (Action de Recherche Concertée) at ULB, is at the crossroads of Deep-Learning and Intellectual Property. This project aims at assessing Intellectual Property (IP) relevant similarities, with a focus on image recognition technologies. Current Algorithmic decisions systems are developed by private companies for the purposes of IP enforcement (monitoring infringing goods online, filtering out content) and registration by IP Offices.
We aim at exposing the biases of such systems, and propose new, unbiased and open-source algorithms for these decisions systems. -
Master Thesis
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"Person Detection Using Time-Of-Flight Cameras and Machine Learning" (2019)
Some access-control gates used in public transportation stations reduce thefare evasion by counting the number of people present in an airlock, assessing that every user paid. Automatic Systems developed such a gate equipped with a Time-Of-Flight camera located above the gate, in order to evaluate its occupancy.
This thesis develops a detection algorithm meant to evaluate the occupancyof the gate using a sequence of depth-images, based on an image-segmentation neural network, followed by a labelization. The occupancy of each image is sim-ply passed through a mode to obtain the sequence’s global occupancy estimation.
A dataset acquired in Lille, in real-life settings, was split in order to train and evaluate the neural network, as well as evaluate the general performancesof the system. The neural network, based on a U-Net, achieved an Area Under Curve of the Precision/Recall curve of 0.94 with only 160k parameters, while the whole system achieved a 86% accuracy, with as little as 2.6% of sequences under-evaluated, those where fraud may occur. The training was done using 4770 depth-images, the validation of the segmentation network over 1362 images, and the system performance evaluation on 3317 sequences. -
Publications
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Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study
Martens, C., Lebrun, L., Decaestecker, C., Vandamme, T., Van Eycke, Y.-R., Rovai, A., Metens, T., Debeir, O., Goldman, S., Salmon, I., & Van Simaeys, G. (2021). Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study. Tomography, 7(4), 650-674. doi:10.3390/tomography7040055AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
Wei, P., Lu, H., Timofte, R., Lin, L., Zuo, W., Pan, Z., Li, B., Xi, T., Fan, Y., Zhang, G., Liu, J., Han, J., Ding, E., Xie, T., Cao, L., Zou, Y., Shen, Y., Zhang, J., Jia, Y., Cheng, K., Wu, C., Lin, Y., Liu, C., Peng, Y., Zou, X., Luo, Z., Yao, Y., Xu, Z., Zamir, S. W., Arora, A., Khan, S., Hayat, M., Khan, F. S., Ahn, K.-H., Kim, J.-H., Choi, J.-H., Lee, J.-S., Zhao, T., Zhao, S., Han, Y., Kim, B.-H., Baek, J., Wu, H., Xu, D., Zhou, B., Guan, W., Li, X., Ye, C., Li, H., Zhong, H., Shi, Y., Yang, Z., Yang, X., Vandamme, T., Almasri, F., & Debeir, O. (2020). AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results. arXiv.org.Initial condition assessment for reaction-diffusion glioma growth models: A translational MRI/histology (in)validation study
Martens, C., Lebrun, L., Decaestecker, C., Vandamme, T., Van Eycke, Y.-R., Rovai, A., Metens, T., Debeir, O., Goldman, S., Salmon, I., & Van Simaeys, G. (2021). Initial condition assessment for reaction-diffusion glioma growth models: A translational MRI/histology (in)validation study: Prepublication on arXiv:2102.01719. arXiv.org.AI-Powered Trademark Prior Art Search Tools: An Empirical Analysis
Cabay, J., & Vandamme, T. (2022). AI-Powered Trademark Prior Art Search Tools: An Empirical Analysis. Paper session presented at 4th Waseda Brussels Conference - New Technologies and Regulation in Japan and Europe (13 September 2022: Bip - Maison de la Région, Brussels).Le recours à la technologie pour l'analyse des similitudes en matière de propriété intellectuelle : défis et perspectives en droit des marques
Cabay, J., & Vandamme, T. (2021). Le recours à la technologie pour l'analyse des similitudes en matière de propriété intellectuelle : défis et perspectives en droit des marques. Paper session presented at Conférence du Centre de droit privé de l'ULB (8 novembre 2021: ULB).Assessing IP Similarities Through Technology: A Trademark Exploration of Challenges and Avenues
Cabay, J., & Vandamme, T. (2021). Assessing IP Similarities Through Technology: A Trademark Exploration of Challenges and Avenues. Paper session presented at Artificial Intelligence Technology & Policy Talk organisé par le Centre de droit du numérique de l'Université de Genève (4 novembre 2021: Université de Genève).