Search Results for author:
Found 2 papers, 2 papers with code
Self-supervised vision-langage alignment of deep learning representations for bone X-rays analysis
This paper proposes leveraging vision-language pretraining on bone X-rays paired with French reports to address downstream tasks of interest on bone radiography.
Improved anomaly detection by training an autoencoder with skip connections on images corrupted with Stain-shaped noise
In industrial vision, the anomaly detection problem can be addressed with an autoencoder trained to map an arbitrary image, i. e. with or without any defect, to a clean image, i. e. without any defect.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
