most citedData refinement for fully unsupervised visual inspection using pre-trained networks

8 citations · 8 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2022

Improving generalization with synthetic training data for deep learning based quality inspection

Antoine Cordier, Pierre Gutierrez, Victoire Plessis

Automating quality inspection with computer vision techniques is often a very data-demanding task. Specifically, supervised deep learning requires a large amount of annotated image…

cs.CV20228 cited

Data refinement for fully unsupervised visual inspection using pre-trained networks

Antoine Cordier, Benjamin Missaoui, Pierre Gutierrez

Anomaly detection has recently seen great progress in the field of visual inspection. More specifically, the use of classical outlier detection techniques on features extracted by…

cs.CV2021

Data augmentation and pre-trained networks for extremely low data regimes unsupervised visual inspection

Pierre Gutierrez, Antoine Cordier, Thaïs Caldeira +1

The use of deep features coming from pre-trained neural networks for unsupervised anomaly detection purposes has recently gathered momentum in the computer vision field. In particu…

cs.CV2021

Synthetic training data generation for deep learning based quality inspection

Pierre Gutierrez, Maria Luschkova, Antoine Cordier +3

Deep learning is now the gold standard in computer vision-based quality inspection systems. In order to detect defects, supervised learning is often utilized, but necessitates a la…

cs.CV2021

Active learning using weakly supervised signals for quality inspection

Antoine Cordier, Deepan Das, Pierre Gutierrez

Because manufacturing processes evolve fast, and since production visual aspect can vary significantly on a daily basis, the ability to rapidly update machine vision based inspecti…