15 citations · 25 across the 7 of their papers we have counts for
7 papers
Quantifying the Generalization Gap in Seizure Detection: A Large-Scale Empirical Benchmark via the SzCORE Challenge
Jonathan Dan, Amirhossein Shahbazinia, Christodoulos Kechris +1
Reliable automatic seizure detection from long-term electroencephalography (EEG) remains an unsolved challenge, as current models often fail to generalize across patients or clinic…
Time series saliency maps: explaining models across multiple domains
Christodoulos Kechris, Jonathan Dan, David Atienza
Traditional saliency map methods, popularized in computer vision, highlight individual points (pixels) of the input that contribute the most to the model's output. However, in time…
Don't Think It Twice: Exploit Shift Invariance for Efficient Online Streaming Inference of CNNs
Christodoulos Kechris, Jonathan Dan, Jose Miranda +1
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 wi…
DC is all you need: describing ReLU from a signal processing standpoint
Christodoulos Kechris, Jonathan Dan, Jose Miranda +1
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 t…
Acoustical Features as Knee Health Biomarkers: A Critical Analysis
Christodoulos Kechris, Jerome Thevenot, Tomas Teijeiro +3
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 f…
KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch
Christodoulos Kechris, Jonathan Dan, Jose Miranda +1
Accurate extraction of heart rate from photoplethysmography (PPG) signals remains challenging due to motion artifacts and signal degradation. Although deep learning methods trained…
Removing Noise from Extracellular Neural Recordings Using Fully Convolutional Denoising Autoencoders
Christodoulos Kechris, Alexandros Delitzas, Vasileios Matsoukas +1
Extracellular recordings are severely contaminated by a considerable amount of noise sources, rendering the denoising process an extremely challenging task that should be tackled f…