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...

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Xehetasun bibliografikoak

Egile Nagusiak:	Emmanuel Pintelas, Ioannis E. Livieris, Panagiotis E. Pintelas
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	MDPI AG 2021-11-01
Saila:	Sensors
Gaiak:	convolutional autoencoders dimensionality reduction deep learning convolutional neural networks computer vision image classification
Sarrera elektronikoa:	https://www.mdpi.com/1424-8220/21/22/7731
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