40 citations · 60 across the 8 of their papers we have counts for
9 papers
CAD-feature enhanced machine learning for manufacturing effort estimation on sheet metal bending parts
Matteo Ballegeer, Toon Van Camp, Willem Jaspers +6
Graph-based machine learning has emerged as a promising approach for manufacturability analysis by learning directly from CAD models represented as Boundary Representations (B-reps…
BenDFM: A taxonomy and synthetic CAD dataset for manufacturability assessment in sheet metal bending
Matteo Ballegeer, Dries F. Benoit
Predicting the manufacturability of CAD designs early, in terms of both feasibility and required effort, is a key goal of Design for Manufacturing (DFM). Despite advances in deep l…
FoV-Net: Rotation-Invariant CAD B-rep Learning via Field-of-View Ray Casting
Matteo Ballegeer, Dries F. Benoit
Learning directly from boundary representations (B-reps) has significantly advanced 3D CAD analysis. However, state-of-the-art B-rep learning methods rely on absolute coordinates a…
Ordinality in Discrete-level Question Difficulty Estimation: Introducing Balanced DRPS and OrderedLogitNN
Arthur Thuy, Ekaterina Loginova, Dries F. Benoit
Recent years have seen growing interest in Question Difficulty Estimation (QDE) using natural language processing techniques. Question difficulty is often represented using discret…
Active Learning to Guide Labeling Efforts for Question Difficulty Estimation
Arthur Thuy, Ekaterina Loginova, Dries F. Benoit
In recent years, there has been a surge in research on Question Difficulty Estimation (QDE) using natural language processing techniques. Transformer-based neural networks achieve…
Explainability through uncertainty: Trustworthy decision-making with neural networks
Arthur Thuy, Dries F. Benoit
Uncertainty is a key feature of any machine learning model and is particularly important in neural networks, which tend to be overconfident. This overconfidence is worrying under d…
Fast and reliable uncertainty quantification with neural network ensembles for industrial image classification
Arthur Thuy, Dries F. Benoit
Image classification with neural networks (NNs) is widely used in industrial processes, situations where the model likely encounters unknown objects during deployment, i.e., out-of…
Using Machine Learning Methods for Automation of Size Grid Building and Management
Salim Yunus, Dries Benoit, Filipa Peleja
Fashion apparel companies require planning for the next season, a year in advance for supply chain management. This study focuses on size selection decision making for Levi Strauss…
Defining a synthetic data generator for realistic electric vehicle charging sessions
Manu Lahariya, Dries Benoit, Chris Develder
Electric vehicle (EV) charging stations have become prominent in electricity grids in the past years. Analysis of EV charging sessions is useful for flexibility analysis, load bala…