A method for anomaly detection in hyperspectral images, using deep convolutional autoencoders

A method for anomaly detection in hyperspectral images, using deep convolutional autoencoders

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Bibliographic Details
Main Author: Penttilä, Jeremias
Other Authors: Informaatioteknologian tiedekunta, Faculty of Information Technology, Informaatioteknologia, University of Jyväskylä, Jyväskylän yliopisto, Tietotekniikka, Mathematical Information Technology, 602
Format: Master's thesis
Language:eng
Published: 2017
Subjects:
hyperspektrikuvat
konvoluutio
autoenkooderit
machine learning
anomaly detection
hyperspectral images
hdbscan
convolutional neural network
autoencoder
convolutional autoencoder
CAE
SCAE
deep learning
autoenkooderi
älytekniikka
poikkeavuus
havaitseminen
neuroverkot
koneoppiminen
Online Access: https://jyx.jyu.fi/handle/123456789/55868
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