IEEE

MMEVAE: A Time-Varying Rolling Bearing Data Enhancement Method Based on a Multimodal Mechanism Enhanced Variational Autoencoder and Self-Attention Module

Abstract: Variational autoencoder (VAE) is widely used as a data enhancement technique. However, it faces challenges with inaccurate potential spatial distribution and poor reconstruction quality when ...
IEEE

CLIP-FSQAE: Clip-Guided Finite Scalar Quantized Autoencoder for Few-Shot Anomaly Detection

Abstract: Industrial anomaly detection is hindered by data inefficiency and dependence on large-scale training sets. We introduce CLIP-FSQAE, a novel framework for few-shot anomaly detection that ...
GitHub

Multimodal Masked Autoencoder Pre-training for 3D MRI-based Brain Tumor Analysis with Missing Modalities

This is a Python repository for recovering weights or re-training a multimodal masked autoencoder on anatomical brain MRIs. It naturally handles missing modalities and processes any combination of ...