Integrated Detection Network for Multiple Object Recognition

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00237809" target="_blank" >RIV/68407700:21230/15:00237809 - isvavai.cz</a>
Result on the web
<a href="http://www.sciencedirect.com/science/article/pii/B9780128025819000068" target="_blank" >http://www.sciencedirect.com/science/article/pii/B9780128025819000068</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/B978-0-12-802581-9.00006-8" target="_blank" >10.1016/B978-0-12-802581-9.00006-8</a>

Result language
angličtina
Original language name
Integrated Detection Network for Multiple Object Recognition
Original language description
Recognizing multiple objects involves two interdependent tasks, object localization and classification. The goal of the object localization is to accurately find the object pose parameters relative to an established reference, such as the origin of the image coordinate system. The object classification assigns class labels to the objects according to the prespecified categories. Multiobject recognition has been previously solved by designing a set of individual single-object detectors or by training a combined multiobject detection and classification system. In the medical domain, these models can be further improved by relying on strong spatial prior information present in medical images of a human body. This chapter describes how the spatial prior can be used to recognize multiple anatomical structures, which results in the integrated detection network. The structures are recognized sequentially, one by one, using optimal order such that the later recognitions can benefit from constr
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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