A Perspective of the Noise Removal for Faster Neural Network Training
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU134020" target="_blank" >RIV/00216305:26220/19:PU134020 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8970907" target="_blank" >https://ieeexplore.ieee.org/document/8970907</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICUMT48472.2019.8970907" target="_blank" >10.1109/ICUMT48472.2019.8970907</a>
Alternative languages
Result language
angličtina
Original language name
A Perspective of the Noise Removal for Faster Neural Network Training
Original language description
Image classification is widely used within image processing area. It is known that insufficient amount of data has negative impact on the training of neural networks in terms of accuracy, convergence speed and in some cases even in the inability to converge. On the other hand, big amount of data significantly increases the training time and costs needed for model creation. Every training sample contains the part valuable for decision (face in case of this paper) and noise, i.e. background of the object. This paper introduces method of iterative noise removal during the training with combination with the transfer learning to optimize the speed of the training process. We show the combination of proposed noise removal and transfer learning leads to more effective training process and enables to learn also from limited data sets. The main contribution of this paper is a proposed method that reduces training time and it is able to accelerate the process in average by 69%. The method was tested on binary classification of two persons from LFW database.
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)<br>S - Specificky vyzkum na vysokych skolach
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
978-1-7281-5763-4
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
1-4
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
000540651700047