IMMI: Interactive Segmentation Toolkit

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F13%3APU104757" target="_blank" >RIV/00216305:26220/13:PU104757 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-41013-0_39" target="_blank" >http://dx.doi.org/10.1007/978-3-642-41013-0_39</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-41013-0_39" target="_blank" >10.1007/978-3-642-41013-0_39</a>

Result language
angličtina
Original language name
IMMI: Interactive Segmentation Toolkit
Original language description
General image segmentation is a non–trivial task, which requires significant computational power and huge amount of knowledge incorporated. Fortunately, it is not necessary in all the cases. In some specific cases, simpler non–supervised or supervised segmentation methods can be used giving even better results. In this paper, a novel trainable segmentation method based on RapidMiner data–mining platform is introduced, and its functionality is described. The method implementation was released under open–source license as a part of IMMI (IMage MIning) extension of the RapidMiner platform. When compared to other trainable segmentation algorithms, the platform provides flexibility connected with all the features of one of the most widely used data–mining platform today. The functionality has been verified on the satellite image use–case, accuracy achieving 78.3% pixel error.
Czech name
—
Czech description
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Project
<a href="/en/project/FR-TI4%2F151" target="_blank" >FR-TI4/151: Research and development of technology for machine emotion detection in unstructured data</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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