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pro vyhledávání: '"Kechris, Christodoulos"'
Deep learning time-series processing often relies on convolutional neural networks with overlapping windows. This overlap allows the network to produce an output faster than the window length. However, it introduces additional computations. This work
Externí odkaz:
http://arxiv.org/abs/2408.03223
Non-linear activation functions are crucial in Convolutional Neural Networks. However, until now they have not been well described in the frequency domain. In this work, we study the spectral behavior of ReLU, a popular activation function. We use th
Externí odkaz:
http://arxiv.org/abs/2407.16556
Autor:
Kechris, Christodoulos, Thevenot, Jerome, Teijeiro, Tomas, Stadelmann, Vincent A., Maffiuletti, Nicola A., Atienza, David
Acoustical knee health assessment has long promised an alternative to clinically available medical imaging tools, but this modality has yet to be adopted in medical practice. The field is currently led by machine learning models processing acoustical
Externí odkaz:
http://arxiv.org/abs/2405.15085
Accurate extraction of heart rate from photoplethysmography (PPG) signals remains challenging due to motion artifacts and signal degradation. Although deep learning methods trained as a data-driven inference problem offer promising solutions, they of
Externí odkaz:
http://arxiv.org/abs/2405.09559
Removing Noise from Extracellular Neural Recordings Using Fully Convolutional Denoising Autoencoders
Autor:
Kechris, Christodoulos, Delitzas, Alexandros, Matsoukas, Vasileios, Petrantonakis, Panagiotis C.
Extracellular recordings are severely contaminated by a considerable amount of noise sources, rendering the denoising process an extremely challenging task that should be tackled for efficient spike sorting. To this end, we propose an end-to-end deep
Externí odkaz:
http://arxiv.org/abs/2109.08945
Autor:
Kechris C; Embedded Systems Laboratory (ESL), Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland. Electronic address: christodoulos.kechris@epfl.ch., Thevenot J; Embedded Systems Laboratory (ESL), Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland., Teijeiro T; Embedded Systems Laboratory (ESL), Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland; Basque Center for Applied Mathematics (BCAM), Spain., Stadelmann VA; Department of Research and Development, Schulthess Klinik, Zürich, Switzerland., Maffiuletti NA; Human Performance Lab, Schulthess Klinik, Zürich, Switzerland., Atienza D; Embedded Systems Laboratory (ESL), Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland.
Publikováno v:
Artificial intelligence in medicine [Artif Intell Med] 2024 Nov 10; Vol. 158, pp. 103013. Date of Electronic Publication: 2024 Nov 10.
Autor:
Kechris C, Delopoulos A
Publikováno v:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2021 Nov; Vol. 2021, pp. 228-231.