4 papers
Detection of Thermal Events by Semi-Supervised Learning for Tokamak First Wall Safety
Christian Staron, Hervé Le Borgne, Raphaël Mitteau +2
This paper explores a semi-supervised object detection approach to detect hot spots on the internal wall of Tokamaks. A huge amount of data is produced during an experimental campa…
Semantic Generative Augmentations for Few-Shot Counting
Perla Doubinsky, Nicolas Audebert, Michel Crucianu +1
With the availability of powerful text-to-image diffusion models, recent works have explored the use of synthetic data to improve image classification performances. These works sho…
Wasserstein Loss for Semantic Editing in the Latent Space of GANs
Perla Doubinsky, Nicolas Audebert, Michel Crucianu +1
The latent space of GANs contains rich semantics reflecting the training data. Different methods propose to learn edits in latent space corresponding to semantic attributes, thus a…
Zero-shot Learning with Deep Neural Networks for Object Recognition
Yannick Le Cacheux, Hervé Le Borgne, Michel Crucianu
Zero-shot learning deals with the ability to recognize objects without any visual training sample. To counterbalance this lack of visual data, each class to recognize is associated…