Zobrazeno 1 - 10
of 368
pro vyhledávání: '"Sahli, Hichem"'
Autor:
Boulogne, Luuk H., Lorenz, Julian, Kienzle, Daniel, Schon, Robin, Ludwig, Katja, Lienhart, Rainer, Jegou, Simon, Li, Guang, Chen, Cong, Wang, Qi, Shi, Derik, Maniparambil, Mayug, Muller, Dominik, Mertes, Silvan, Schroter, Niklas, Hellmann, Fabio, Elia, Miriam, Dirks, Ine, Bossa, Matias Nicolas, Berenguer, Abel Diaz, Mukherjee, Tanmoy, Vandemeulebroucke, Jef, Sahli, Hichem, Deligiannis, Nikos, Gonidakis, Panagiotis, Huynh, Ngoc Dung, Razzak, Imran, Bouadjenek, Reda, Verdicchio, Mario, Borrelli, Pasquale, Aiello, Marco, Meakin, James A., Lemm, Alexander, Russ, Christoph, Ionasec, Razvan, Paragios, Nikos, van Ginneken, Bram, Dubois, Marie-Pierre Revel
Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Public access to the training methodology for these solutions remains abse
Externí odkaz:
http://arxiv.org/abs/2306.10484
Autor:
Safa, Ali, Verbelen, Tim, Ocket, Ilja, Bourdoux, André, Sahli, Hichem, Catthoor, Francky, Gielen, Georges
This work proposes a first-of-its-kind SLAM architecture fusing an event-based camera and a Frequency Modulated Continuous Wave (FMCW) radar for drone navigation. Each sensor is processed by a bio-inspired Spiking Neural Network (SNN) with continual
Externí odkaz:
http://arxiv.org/abs/2210.04236
Autor:
Safa, Ali, Verbelen, Tim, Ocket, Ilja, Bourdoux, André, Sahli, Hichem, Catthoor, Francky, Gielen, Georges
Learning to safely navigate in unknown environments is an important task for autonomous drones used in surveillance and rescue operations. In recent years, a number of learning-based Simultaneous Localisation and Mapping (SLAM) systems relying on dee
Externí odkaz:
http://arxiv.org/abs/2208.12997
Successful data representation is a fundamental factor in machine learning based medical imaging analysis. Deep Learning (DL) has taken an essential role in robust representation learning. However, the inability of deep models to generalize to unseen
Externí odkaz:
http://arxiv.org/abs/2207.01437
Autor:
Boulogne, Luuk H., Lorenz, Julian, Kienzle, Daniel, Schön, Robin, Ludwig, Katja, Lienhart, Rainer, Jégou, Simon, Li, Guang, Chen, Cong, Wang, Qi, Shi, Derik, Maniparambil, Mayug, Müller, Dominik, Mertes, Silvan, Schröter, Niklas, Hellmann, Fabio, Elia, Miriam, Dirks, Ine, Bossa, Matías Nicolás, Berenguer, Abel Díaz, Mukherjee, Tanmoy, Vandemeulebroucke, Jef, Sahli, Hichem, Deligiannis, Nikos, Gonidakis, Panagiotis, Huynh, Ngoc Dung, Razzak, Imran, Bouadjenek, Reda, Verdicchio, Mario, Borrelli, Pasquale, Aiello, Marco, Meakin, James A., Lemm, Alexander, Russ, Christoph, Ionasec, Razvan, Paragios, Nikos, van Ginneken, Bram, Revel, Marie-Pierre
Publikováno v:
In Medical Image Analysis October 2024 97
This paper demonstrates for the first time that a biologically-plausible spiking neural network (SNN) equipped with Spike-Timing-Dependent Plasticity (STDP) can continuously learn to detect walking people on the fly using retina-inspired, event-based
Externí odkaz:
http://arxiv.org/abs/2202.08023
We present new theoretical foundations for unsupervised Spike-Timing-Dependent Plasticity (STDP) learning in spiking neural networks (SNNs). In contrast to empirical parameter search used in most previous works, we provide novel theoretical grounds f
Externí odkaz:
http://arxiv.org/abs/2111.00791
Autor:
Berenguer, Abel Díaz, Kvasnytsia, Maryna, Bossa, Matías Nicolás, Mukherjee, Tanmoy, Deligiannis, Nikos, Sahli, Hichem
Publikováno v:
In Medical Image Analysis May 2024 94
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging
Autor:
Berenguer, Abel Díaz, Sahli, Hichem, Joukovsky, Boris, Kvasnytsia, Maryna, Dirks, Ine, Alioscha-Perez, Mitchel, Deligiannis, Nikos, Gonidakis, Panagiotis, Sánchez, Sebastián Amador, Brahimetaj, Redona, Papavasileiou, Evgenia, Chana, Jonathan Cheung-Wai, Li, Fei, Song, Shangzhen, Yang, Yixin, Tilborghs, Sofie, Willems, Siri, Eelbode, Tom, Bertels, Jeroen, Vandermeulen, Dirk, Maes, Frederik, Suetens, Paul, Fidon, Lucas, Vercauteren, Tom, Robben, David, Brys, Arne, Smeets, Dirk, Ilsen, Bart, Buls, Nico, Watté, Nina, de Mey, Johan, Snoeckx, Annemiek, Parizel, Paul M., Guiot, Julien, Deprez, Louis, Meunier, Paul, Gryspeerdt, Stefaan, De Smet, Kristof, Jansen, Bart, Vandemeulebroucke, Jef
Our motivating application is a real-world problem: COVID-19 classification from CT imaging, for which we present an explainable Deep Learning approach based on a semi-supervised classification pipeline that employs variational autoencoders to extrac
Externí odkaz:
http://arxiv.org/abs/2011.11719
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