Bioimaging ? Autothresholding and segmentation via neural networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12520%2F17%3A43895368" target="_blank" >RIV/60076658:12520/17:43895368 - isvavai.cz</a>
Alternative codes found
RIV/49777513:23520/17:43932945
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-319-56148-6_31#enumeration" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-56148-6_31#enumeration</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-56148-6_31" target="_blank" >10.1007/978-3-319-56148-6_31</a>
Alternative languages
Result language
angličtina
Original language name
Bioimaging ? Autothresholding and segmentation via neural networks
Original language description
Bioimaging, image segmentation, thresholding, and multivariate processing are helpful tools in analysis of series of images from many time lapse experiments. The different methods of mathematic, algorithmization and artificial intelligence could by modified, parametrized or adopted for single purpose case of completely different biological background (namely microorganisms, tissue cultures, aquaculture). However, most of the task is based on initial image segmentation, before features axtraction and comparison tasks are evaluated. In this article, we compare several of classical approaches in bioinformatical and biophysical cases with the neural network approach. The concept of neural network was adopted from the biological neural networks. Th networks need to be trained, however after the learning phase, they should be able to find one solution for various objects. The comparison of the methods is evaluated via error in segmentation according to the human supervisor.
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
20204 - Robotics and automatic control
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
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science
ISBN
978-3-319-56147-9
ISSN
0302-9743
e-ISSN
neuvedeno
Number of pages
11
Pages from-to
358-368
Publisher name
Springer Verlag
Place of publication
Cham
Event location
Granada, Španělsko
Event date
Apr 26, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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