8 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…
A geometric and deep learning reproducible pipeline for monitoring floating anthropogenic debris in urban rivers using in situ cameras
Gauthier Grimmer, Romain Wenger, Clément Flint +3
The proliferation of floating anthropogenic debris in rivers has emerged as a pressing environmental concern, exerting a detrimental influence on biodiversity, water quality, and h…
The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classification
Matthew Middlehurst, Aiden Rushbrooke, Ali Ismail-Fawaz +6
Time series machine learning (TSML) is a growing research field that spans a wide range of tasks. The popularity of established tasks such as classification, clustering, and extrin…
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…