1.6k citations · 2.2k across the 9 of their papers we have counts for
7 papers · 1 filter
Match-And-Deform: Time Series Domain Adaptation through Optimal Transport and Temporal Alignment
François Painblanc, Laetitia Chapel, Nicolas Courty +3
While large volumes of unlabeled data are usually available, associated labels are often scarce. The unsupervised domain adaptation problem aims at exploiting labels from a source…
Elastic Similarity and Distance Measures for Multivariate Time Series
Ahmed Shifaz, Charlotte Pelletier, Francois Petitjean +1
This paper contributes multivariate versions of seven commonly used elastic similarity and distance measures for time series data analytics. Elastic similarity and distance measure…
A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping
Benjamin Lucas, Charlotte Pelletier, Daniel Schmidt +2
Land cover maps are a vital input variable to many types of environmental research and management. While they can be produced automatically by machine learning techniques, these te…
InceptionTime: Finding AlexNet for Time Series Classification
Hassan Ismail Fawaz, Benjamin Lucas, Germain Forestier +7
This paper brings deep learning at the forefront of research into Time Series Classification (TSC). TSC is the area of machine learning tasked with the categorization (or labelling…
TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification
Ahmed Shifaz, Charlotte Pelletier, Francois Petitjean +1
Time Series Classification (TSC) has seen enormous progress over the last two decades. HIVE-COTE (Hierarchical Vote Collective of Transformation-based Ensembles) is the current sta…
BreizhCrops: A Time Series Dataset for Crop Type Mapping
Marc Rußwurm, Charlotte Pelletier, Maximilian Zollner +2
We present Breizhcrops, a novel benchmark dataset for the supervised classification of field crops from satellite time series. We aggregated label data and Sentinel-2 top-of-atmosp…
Proximity Forest: An effective and scalable distance-based classifier for time series
Benjamin Lucas, Ahmed Shifaz, Charlotte Pelletier +5
Research into the classification of time series has made enormous progress in the last decade. The UCR time series archive has played a significant role in challenging and guiding…