Skip to content
University of Jyväskylä | Thesis search
  • Language
    • Suomi
    • English
University of Jyväskylä | Thesis search
Language
  • Suomi
  • English
Advanced
  • A method for anomaly detection...
  • Cite this
  • Print
  • Export Record
    • Export to RefWorks
    • Export to EndNoteWeb
    • Export to EndNote
A method for anomaly detection in hyperspectral images, using deep convolutional autoencoders

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

Show other versions (1)
Bibliographic Details
Main Author: Penttilä, Jeremias, kirjoittaja
Format: Master's thesis
Language:eng
Subjects:
älytekniikka
poikkeavuus
havaitseminen
neuroverkot
koneoppiminen
hyperspektrikuvat
konvoluutio
autoenkooderit
machine learning
anomaly detection
hyperspectral images
hdbscan
convolutional neural network
autoencoder
convolutional autoencoder
CAE
SCAE
deep learning
autoenkooderi
Online Access:JYX-julkaisuarkisto / JYX Digital Archive
  • Description
  • Other Versions (1)
  • Staff View
Description
Access:Aineisto on vapaasti saatavissa.

Similar Items

  • A method for anomaly detection in hyperspectral images, using deep convolutional autoencoders
    by: Penttilä, Jeremias
    Published: (2017)
  • Applications of images anomalies detection using deep learning in department store
    by: Banstola, Ram
    Published: (2020)
  • Convolutional neural networks and stochastic modelling in hyperspectral data analysis
    by: Annala, Leevi, kirjoittaja
    Published: (2020)
  • Convolutional neural networks and stochastic modelling in hyperspectral data analysis
    by: Annala, Leevi, kirjoittaja
    Published: (2020)
  • Perceived differences between natural and convolution reverberation types in 5.0 surround sound
    by: Shriram, Alluri R.
    Published: (2011)

Search Options

  • Search History
  • Advanced Search
  • New Items

Need Help?

  • Search Tips

Contact

  • University of Jyväskylä
  • Open Science Centre
  • Accessibility report