works on

From the 1 of 9 linked papers with an AI index.

collaborators

9 papers

cs.CV2026

The 2nd International StepUP Competition for Biometric Footstep Recognition: From Steps to Strides

Robyn Larracy, Anant Gupta, Gourav Gupta +8

The paper describes the second International StepUP Competition, which evaluated methods for recognizing individuals from pressure‑based footstep data under challenging conditions…

cs.LG2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.CV2025

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…