IEEE

ConUAD: Combating Noisy Data through Selective Contrastive Learning for Unsupervised Acoustic Anomaly Detection

Abstract: Acoustic Anomaly Detection (AAD) has gained significant attention as a method for identifying faults or malicious activities. Previous state-of-the-art (SOTA) unsupervised AAD algorithms, ...
IEEE

Enhancing Semi-Supervised Brain Tumor Segmentation via Dual-Uncertainty Guided 2.5-D CNN–Transformer and Voxel-Wise Contrastive Learning

Abstract: Data annotation in medical image segmentation is time-consuming and expensive. Semi-supervised learning (SSL) presents a viable solution. However, unlike organ segmentation, current ...