Development of an early warning algorithm to detect sick broilers

•The aim of the paper was to automatically diagnose the health status of broilers.•K-means clustering and the ellipse model were used to segment the images.•Seven features were identified to recognize the health status of broilers.•The SVM model, using the POLY kernel function, obtains an accuracy r...

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Veröffentlicht in:	Computers and electronics in agriculture 2018-01, Vol.144, p.102-113
Hauptverfasser:	Zhuang, Xiaolin, Bi, Minna, Guo, Jilei, Wu, Siyu, Zhang, Tiemin
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Automatic monitoring Broiler chickens Cages Chickens Data acquisition Digital imaging Disease Economic impact Eigenvectors Feature extraction Feature recognition Health Image classification Image processing Image segmentation Learning Machine learning Model accuracy Outbreaks Posture Poultry Prevention Studies Support vector machines SVM Viruses
Online-Zugang:	Volltext
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