Devdiscourse

Fast and Accurate Water Leak Detection in Distribution Networks Using Deep Anomaly Models

Researchers from Politecnico di Milano propose a data-driven water leak detection method that treats leaks as anomalies in ...
GitHub

Deep Autoencoders model for Anomaly Detection

"Objective: This project focuses on the application of Autoencoders in Deep Learning, particularly for learning compressed representations of data. Autoencoders consist of two main components: an ...
C&EN

Variational Autoencoder for Generation of Antimicrobial Peptides

Over millennia, natural evolution has allowed for the emergence of countless biomolecules with highly specific roles within natural systems. As seen with peptides and proteins, often evolution ...
Frontiers

Loop closure detection of visual SLAM based on variational autoencoder

1 Department of College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China 2 Yantai Tulan Electronic Technology Co., Ltd, Yantai, China Loop ...
GitHub

mdhabibi/Neural-Compression-with-Autoencoders

The primary objective of this project is to develop an efficient model for data compression. The focus is on leveraging complex autoencoder architectures to achieve significant dimensionality ...
IEEE

Dual-Constraint Autoencoder and Adaptive Weighted Similarity Spatial Attention for Unsupervised Anomaly Detection

Abstract: Image reconstruction-based methods with autoencoder have been widely used for unsupervised anomaly detection. By training the reconstruction on normal ...
IEEE

Improved Autoencoder Model With Memory Module for Anomaly Detection

Abstract: As a commonly used model for anomaly detection, the autoencoder model for anomaly detection does not train the objective for extracted features, which is a downside of autoencoder model. In ...