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Beaini, D., Achiche, S., Duperre, A., & Raison, M. (2021). Deep green function convolution for improving saliency in convolutional neural networks. Visual Computer, 37(2), 227-244. Lien externe
Beaini, D. (2019). Green Function and Electromagnetic Potential for Computer Vision and Convolutional Neural Network Applications [Thèse de doctorat, Polytechnique Montréal]. Disponible
Beaini, D., Achiche, S., & Raison, M. (2019). Object analysis in images using electric potentials and electric fields. (Demande de brevet no US20190277618). Lien externe
Gamache, J.-F., Vadean, A., Noirot-Nérin, É., Beaini, D., & Achiche, S. (2018). Image-based truss recognition for density-based topology optimization approach. Structural and Multidisciplinary Optimization, 58(6), 2697-2709. Lien externe
Beaini, D., Achiche, S., Law-Kam Cio, Y.-S., & Raison, M. (2018). Novel convolution kernels for computer vision and shape analysis based on electromagnetism. (Rapport). Disponible
Beaini, D. (2018). Object analysis in images using electric potentials and electric fields. (Demande de brevet no WO2018045472). Lien externe
Leroux, M., Beaini, D., Achiche, S., & Raison, M. (mai 2016). Revisiting the Agile eye using Euler-Lagrange Formalism and Torque Control [Communication écrite]. Joint International Conference on Multibody System Dynamics (IMSD 2016), Montréal, Québec. Non disponible
