MicrAnt: Towards Regression Task Oriented Annotation Tool for Microscopic Images
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F20%3A81953" target="_blank" >RIV/60460709:41210/20:81953 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-51002-2_15#enumeration" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-51002-2_15#enumeration</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-51002-2_15" target="_blank" >10.1007/978-3-030-51002-2_15</a>
Alternative languages
Result language
angličtina
Original language name
MicrAnt: Towards Regression Task Oriented Annotation Tool for Microscopic Images
Original language description
Annotating a dataset for training a Supervised Machine Learning algorithm is time and annotators attention intensive. Our goal was to create a tool that would enable us to create annotations of the dataset with minimal demands on experts time. Inspired by applications such as Tinder, we have created an annotation tool for describing microscopic images. A graphical user interface is used to select from a couple of images the one with the higher value of the examined parameter. Two experiments were performed. The first compares the speed of annotation of our application with the commonly used tool for processing microscopic images. In the second experiment, the texture description was compared with the annotations from MicrAnt application and commonly used application. The results showed that the processing time using our application is 3 times lower and the Spearman coefficient increases by 0,05 than using a commonly used application. In an experiment, we have shown that the annotations processed usin
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
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Combinatorial Image Analysis
ISBN
978-3-030-51002-2
ISSN
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e-ISSN
1611-3349
Number of pages
10
Pages from-to
209-218
Publisher name
Springer
Place of publication
Novi Sad, Serbia
Event location
Novi Sad, Serbia
Event date
Jun 16, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000000000000000