IEEE

Contrastive Self-Supervised Learning-Based Background Reconstruction for Hyperspectral Anomaly Detection

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 ...
Frontiers

Generative AI in Education: Cognitive Mechanisms, Learning Outcomes, and Evidence-Based Practice

The rapid adoption of generative AI tools — including large language models such as ChatGPT, DeepSeek, and domain-specific tutoring systems — has outpaced ...
IEEE

Self-Supervised Feature Learning for Cardiac Cine MR Image Reconstruction

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.
GitHub

plot_label_propagation_structure.py

# We generate a dataset with two concentric circles. In addition, a label # is associated with each sample of the dataset that is: 0 (belonging to # the outer circle), 1 (belonging to the inner circle ...
GitHub

Label Propagation digits: Active learning

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 ...