Upsampling Algorithms for Autoencoder Segmentation Neural Networks: A Comparison Study
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU134013" target="_blank" >RIV/00216305:26220/19:PU134013 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/abstract/document/8970918" target="_blank" >https://ieeexplore.ieee.org/abstract/document/8970918</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICUMT48472.2019.8970918" target="_blank" >10.1109/ICUMT48472.2019.8970918</a>
Alternative languages
Result language
angličtina
Original language name
Upsampling Algorithms for Autoencoder Segmentation Neural Networks: A Comparison Study
Original language description
This paper compares nine different upsampling methods used in convolutional neural networks in terms of accuracy and processing speed. The process of image segmentation using autoencoder neural networks consists of the image downsampling in the encoder and correspondingly of image upsampling in the decoder part of the network to achieve original image resolution. This paper focuses on the upsampling process in the decoder part of the standard U-Net neural network. Three different interpolations are compared with and without subsequent 1x1 convolution layers and three transpose convolution layers for image upsampling using different size convolutional cores. The experiment has shown that the best practical results were achieved using simple nearest neighbor interpolation upsampling taking into consideration the computational time needed. The network using nearest neighbor interpolation upsampling achieved pixel accuracy of 99.47% and has shown fast training time and convergence in comparison with other networks using different upsampling methods. The data used in this work consist of a lumbar CT spine segmentation dataset.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)
ISBN
978-1-7281-5764-1
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
1-5
Publisher name
Neuveden
Place of publication
Dublin
Event location
Dublin
Event date
Oct 28, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000540651700049