Improved Autoencoder Model With Memory Module for Anomaly Detection (IAEMM) is an unsupervised anomaly detection algorithm that enhances traditional autoencoders with a memory module and a hypersphere ...

Builds autoencoder model using Pytorch module. The outputs of the encoder and decoder structures are compared to demonstrate the models ability to reconstructs the input image, as well as decoder's ...

Abstract: In this paper, we propose a novel Transformer based approach, namely Cross-modal Contrastive Masked AutoEncoder (C2MAE), to Self-Supervised Learning (SSL) on compressed videos. A unified ...

The growing digitalization of Industrial Control Systems (ICSs) presents both significant benefits and security challenges, especially for small and medium-sized factories with limited resources.

Generating the periodic structure of stable materials is a long-standing challenge for the material design community. This task is difficult because stable materials only exist in a low-dimensional ...

Traditional data-driven models for predicting rare earth component content are primarily developed by relying on supervised learning methods, which suffer from limitations such as a lack of labeled ...