Nature

Autoencoder Techniques in Anomaly Detection and Feature Learning

Autoencoders are a class of unsupervised neural networks designed to learn efficient data representations by encoding inputs into a compact latent space and then reconstructing them. Their versatility ...
EurekAlert!

An approach for unsupervised domain adaptation based on integrated autoencoder

Unsupervised domain adaptation has provoked vast amount of attention and research in past decades. Among all the deep-based methods, the autoencoder-based approach have achieved sound performance for ...
Nature

Secure Elliptic Galois Cryptography Framework for robust real-time vehicle image classification using convolutional sparse autoencoder in intelligent transportation systems

Intelligent transportation systems (ITS) have experienced an important development in the past decade because of developments in communication, control, and information technology deployed to roads, ...