Benoît Miramond

GPU-based Self-Organizing Maps for Post-Labeled Few-Shot Unsupervised\n Learning

2020 · arXiv (Cornell University)

Few-shot classification is a challenge in machine learning where the goal is\nto train a classifier using a very limited number of labeled examples. This\nscenario is likely to occur frequently in real life, for example when …

Unsupervised Anomaly Detection for Cars CAN Sensors Time Series Using Small Recurrent and Convolutional Neural Networks

2023 · Sensors

Predictive maintenance in the car industry is an active field of research for machine learning and anomaly detection. The capability of cars to produce time series data from sensors is growing as the car industry …