Abstract: Deep learning (DL) has received a lot of attention in hyperspectral anomaly detection (HAD) in recent years. While some progress has been made in boosting the generalization of DL-based HAD ...

Abstract: We propose a self-supervised feature learning assisted reconstruction (SSFL-Recon) framework for MRI reconstruction to address the limitation of existing supervised learning methods.

then we select the top five most uncertain points to label. Next, we train with 15 labeled points (original 10 + 5 new ones). We repeat this process four times to have a model trained with 30 labeled ...