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LEIA - Low-end image analysis to continuously monitor growth and body conformation of fattening pigs

dc.contributor.authorAppel, Christoph
dc.contributor.authorJungbluth, Thomas
dc.contributor.authorHartung, Eberhard
dc.contributor.editorBöttinger, Stefan
dc.contributor.editorTheuvsen, Ludwig
dc.contributor.editorRank, Susanne
dc.contributor.editorMorgenstern, Marlies
dc.date.accessioned2019-05-15T10:40:52Z
dc.date.available2019-05-15T10:40:52Z
dc.date.issued2007
dc.description.abstractVariability within a group of animals is an important information which can be used for further optimization of pig fattening. Hence, this project will provide a generic methodology to continuously monitor the differences of growth and body conformation within a group of animals using a set of robust and simple, i.e. low-end image analysis (LEIA) algorithms. The methodology will be breed independent. The verification of the methodology is done under practical conditions with fattening pigs. The project will provide non-dimensional parameters to describe a group’s heterogeneity with regards to changes in time. Time-series analyses will be used for the estimation of the future development of variability within the group.en
dc.identifier.isbn978-3-88579-195-9
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/22861
dc.language.isoen
dc.publisherGesellschaft für Informatik e. V.
dc.relation.ispartofAgrarinformatik im Spannungsfeld zwischen Regionalisierung und globalen Wertschöpfungsketten – Referate der 27. GIL Jahrestagung
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-101
dc.titleLEIA - Low-end image analysis to continuously monitor growth and body conformation of fattening pigsen
dc.typeText/Conference Paper
gi.citation.endPage22
gi.citation.publisherPlaceBonn
gi.citation.startPage19
gi.conference.date05.-07. März 2007
gi.conference.locationStuttgart
gi.conference.sessiontitleRegular Research Papers

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