14 citations · 31 across the 10 of their papers we have counts for
10 papers
When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregate
Florent Forest, Amaury Wei, Olga Fink
Time series extrinsic regression (TSER) refers to the task of predicting a continuous target variable from an input time series. It appears in many domains, including healthcare, f…
Explainable AI guided unsupervised fault diagnostics for high-voltage circuit breakers
Chi-Ching Hsu, Gaëtan Frusque, Florent Forest +3
Commercial high-voltage circuit breaker (CB) condition monitoring systems rely on directly observable physical parameters such as gas filling pressure with pre-defined thresholds.…
Thermoxels: a voxel-based method to generate simulation-ready 3D thermal models
Etienne Chassaing, Florent Forest, Olga Fink +1
In the European Union, buildings account for 42% of energy use and 35% of greenhouse gas emissions. Since most existing buildings will still be in use by 2050, retrofitting is cruc…
Exploiting Semantic Scene Reconstruction for Estimating Building Envelope Characteristics
Chenghao Xu, Malcolm Mielle, Antoine Laborde +3
Achieving the EU's climate neutrality goal requires retrofitting existing buildings to reduce energy use and emissions. A critical step in this process is the precise assessment of…
Simplifying Source-Free Domain Adaptation for Object Detection: Effective Self-Training Strategies and Performance Insights
Yan Hao, Florent Forest, Olga Fink
This paper focuses on source-free domain adaptation for object detection in computer vision. This task is challenging and of great practical interest, due to the cost of obtaining…
Cut-and-Paste with Precision: a Content and Perspective-aware Data Augmentation for Road Damage Detection
Punnawat Siripathitti, Florent Forest, Olga Fink
Damage to road pavement can develop into cracks, potholes, spallings, and other issues posing significant challenges to the integrity, safety, and durability of the road structure.…
Interpretable Prognostics with Concept Bottleneck Models
Florent Forest, Katharina Rombach, Olga Fink
Deep learning approaches have recently been extensively explored for the prognostics of industrial assets. However, they still suffer from a lack of interpretability, which hinders…
Uncertainty-Guided Alignment for Unsupervised Domain Adaptation in Regression
Ismail Nejjar, Gaetan Frusque, Florent Forest +1
Unsupervised Domain Adaptation for Regression (UDAR) aims to adapt models from a labeled source domain to an unlabeled target domain for regression tasks. Traditional feature align…
Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault Diagnosis
Florent Forest, Olga Fink
Intelligent Fault Diagnosis (IFD) based on deep learning has proven to be an effective and flexible solution, attracting extensive research. Deep neural networks can learn rich rep…
From Classification to Segmentation with Explainable AI: A Study on Crack Detection and Growth Monitoring
Florent Forest, Hugo Porta, Devis Tuia +1
Monitoring surface cracks in infrastructure is crucial for structural health monitoring. Automatic visual inspection offers an effective solution, especially in hard-to-reach areas…