A comparison of classical and variational autoencoders for anomaly detection

Autor:	Patuzzo, Fabrizio
Rok vydání:	2020
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	This paper analyzes and compares a classical and a variational autoencoder in the context of anomaly detection. To better understand their architecture and functioning, describe their properties and compare their performance, it explores how they address a simple problem: reconstructing a line with a slope.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2009.13793 Zobrazit plný text záznamu View this record from Arxiv