Opin vísindi

Fletta eftir efnisorði "Deep learning"

Fletta eftir efnisorði "Deep learning"

Röðun: Raða: Niðurstöður:

  • Icon
    Blind Hyperspectral Unmixing Using Autoencoders 
    Pálsson, Burkni (University of Iceland, School of Engineering and Natural Sciences, Faculty of Electrical and Computer Engineering, 2023-09)
    The subject of this thesis is blind hyperspectral unmixing using deep learning based autoencoders. Two methods based on autoencoders are proposed and analyzed. Both methods seek to exploit the spatial correlations in the hyperspectral images to improve ...
  • Icon
    The capability of recurrent neural networks to predict turbulence flow via spatiotemporal features 
    Hassanian, Reza; Bouhlali, Lahcen; Riedel, Morris (IEEE, 2022-07-06)
    This study presents a deep learning (DL) neural network hybrid data-driven method that is able to predict turbulence flow velocity field. Recently many studies have reported the application of recurrent neural network (RNN) methods, particularly the ...
  • Icon
    Deep Convolutional Capsule Network for Hyperspectral Image Spectral and Spectral-Spatial Classification 
    Zhu, Kaiqiang; Chen, Yushi; Ghamisi, Pedram; Jia, Xiuping; Benediktsson, Jon Atli (MDPI AG, 2019-01-22)
    Capsule networks can be considered to be the next era of deep learning and have recently shown their advantages in supervised classification. Instead of using scalar values to represent features, the capsule networks use vectors to represent features, ...
  • Icon
    Hyperspectral Unmixing Using a Neural Network Autoencoder 
    Palsson, Burkni; Sigurdsson, Jakob; Sveinsson, Jóhannes Rúnar; Ulfarsson, Magnus (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    In this paper, we present a deep learning based method for blind hyperspectral unmixing in the form of a neural network autoencoder. We show that the linear mixture model implicitly puts certain architectural constraints on the network, and it effectively ...
  • Icon
    SegAE: Unsupervised white matter lesion segmentation from brain MRIs using a CNN autoencoder 
    Atlason, Hans; Love, Askell; Sigurdsson, Sigurdur; Gudnason, Vilmundur; Ellingsen, Lotta María (Elsevier BV, 2019)
    White matter hyperintensities (WMHs) of presumed vascular origin are frequently observed in magnetic resonance images (MRIs) of the elderly. Detection and quantification of WMHs is important to help doctors make diagnoses and evaluate prognosis of their ...