A Convolutional Autoencoder Topology for Classification in High-Dimensional Noisy Image Datasets

Deep convolutional neural networks have shown remarkable performance in the image classification domain. However, Deep Learning models are vulnerable to noise and redundant information encapsulated into the high-dimensional raw input images, leading to unstable and unreliable predictions. Autoencode...

Celý popis

Podrobná bibliografia

Vydané v:	Sensors (Basel, Switzerland) Ročník 21; číslo 22; s. 7731
Hlavní autori:	Pintelas, Emmanuel, Livieris, Ioannis E., Pintelas, Panagiotis E.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 20.11.2021 MDPI
Predmet:	Classification computer vision convolutional autoencoders convolutional neural networks Datasets Deep learning dimensionality reduction image classification Machine learning Noise Parameter estimation
ISSN:	1424-8220, 1424-8220
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!