17 citations · 35 across the 15 of their papers we have counts for
15 papers
The 2nd International StepUP Competition for Biometric Footstep Recognition: From Steps to Strides
Robyn Larracy, Anant Gupta, Gourav Gupta +8
The International StepUP Competition Series was launched to advance research in pressure-based footstep biometrics through a standardized and challenging evaluation framework. Usin…
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…
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…
Failure Risk Prediction in a MOOC: A Multivariate Time Series Analysis Approach
Anass El Ayady, Maxime Devanne, Germain Forestier +1
MOOCs offer free and open access to a wide audience, but completion rates remain low, often due to a lack of personalized content. To address this issue, it is essential to predict…
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…
A Medical Low-Back Pain Physical Rehabilitation Dataset for Human Body Movement Analysis
Sao Mai Nguyen, Maxime Devanne, Olivier Remy-Neris +2
While automatic monitoring and coaching of exercises are showing encouraging results in non-medical applications, they still have limitations such as errors and limited use context…
Establishing a Unified Evaluation Framework for Human Motion Generation: A Comparative Analysis of Metrics
Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti +2
The development of generative artificial intelligence for human motion generation has expanded rapidly, necessitating a unified evaluation framework. This paper presents a detailed…
Finding Foundation Models for Time Series Classification with a PreText Task
Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti +2
Over the past decade, Time Series Classification (TSC) has gained an increasing attention. While various methods were explored, deep learning - particularly through Convolutional N…
ShapeDBA: Generating Effective Time Series Prototypes using ShapeDTW Barycenter Averaging
Ali Ismail-Fawaz, Hassan Ismail Fawaz, François Petitjean +5
Time series data can be found in almost every domain, ranging from the medical field to manufacturing and wireless communication. Generating realistic and useful exemplars and prot…
An Approach to Multiple Comparison Benchmark Evaluations that is Stable Under Manipulation of the Comparate Set
Ali Ismail-Fawaz, Angus Dempster, Chang Wei Tan +8
The measurement of progress using benchmarks evaluations is ubiquitous in computer science and machine learning. However, common approaches to analyzing and presenting the results…
A co-design approach for a rehabilitation robot coach for physical rehabilitation based on the error classification of motion errors
Maxime Devanne, Sao Mai Nguyen, Olivier Rémy-Néris +3
The rising number of the elderly incurs growing concern about healthcare, and in particular rehabilitation healthcare. Assistive technology and assistive robotics in particular may…
Generating Shared Latent Variables for Robots to Imitate Human Movements and Understand their Physical Limitations
Maxime Devanne, Sao Mai Nguyen
Assistive robotics and particularly robot coaches may be very helpful for rehabilitation healthcare. In this context, we propose a method based on Gaussian Process Latent Variable…