5 papers
Enhancing deep learning models for time series classification via knowledge distillation
Javidan Abdullayev, Maxime Devanne, Jonathan Weber +1
Deep learning has achieved remarkable success in various domains including time series analysis, computer vision and natural language processing. However, high computational and me…
Adaptive Structured Pruning of Convolutional Neural Networks for Time Series Classification
Javidan Abdullayev, Maxime Devanne, Cyril Meyer +3
Deep learning models for Time Series Classification (TSC) have achieved strong predictive performance but their high computational and memory requirements often limit deployment on…
Enhancing Time Series Classification with Diversity-Driven Neural Network Ensembles
Javidan Abdullayev, Maxime Devanne, Cyril Meyer +3
Ensemble methods have played a crucial role in achieving state-of-the-art (SOTA) performance across various machine learning tasks by leveraging the diversity of features learned b…
A Standardized Benchmark for Skeleton-Based Rehabilitation Assessment Using Deep Learning
Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti +2
Automated assessment of human motion plays a vital role in rehabilitation, enabling objective evaluation of patient performance and progress. Unlike general human activity recognit…
Look Into the LITE in Deep Learning for Time Series Classification
Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti +2
Deep learning models have been shown to be a powerful solution for Time Series Classification (TSC). State-of-the-art architectures, while producing promising results on the UCR an…