15 citations · 16 across the 10 of their papers we have counts for
10 papers
VersaPants: A Loose-Fitting Textile Capacitive Sensing System for Lower-Body Motion Capture
Deniz Kasap, Taraneh Aminosharieh Najafi, Jérôme Paul Rémy Thevenot +3
We present VersaPants, the first loose-fitting, textile-based capacitive sensing system for lower-body motion capture, built on the open-hardware VersaSens platform. By integrating…
Personalization on a Budget: Minimally-Labeled Continual Learning for Resource-Efficient Seizure Detection
Amirhossein Shahbazinia, Jonathan Dan, Jose A. Miranda +2
Objective: Epilepsy, a prevalent neurological disease, demands careful diagnosis and continuous care. Seizure detection remains challenging, as current clinical practice relies on…
MEDEA: A Design-Time Multi-Objective Manager for Energy-Efficient DNN Inference on Heterogeneous Ultra-Low Power Platforms
Hossein Taji, José Miranda, Miguel Peón-Quirós +1
The growing demand for on-device AI necessitates energy-efficient execution of DNN based applications on resource-constrained ultra-low power (ULP) platforms. Heterogeneous archite…
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…
FADE: Forecasting for Anomaly Detection on ECG
Paula Ruiz-Barroso, Francisco M. Castro, José Miranda +3
Cardiovascular diseases, a leading cause of noncommunicable disease-related deaths, require early and accurate detection to improve patient outcomes. Taking advantage of advances i…
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…
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…
STRELA: STReaming ELAstic CGRA Accelerator for Embedded Systems
Daniel Vazquez, Jose Miranda, Alfonso Rodriguez +3
Reconfigurable computing offers a good balance between flexibility and energy efficiency. When combined with software-programmable devices such as CPUs, it is possible to obtain hi…