Diagnosing lameness with the Random Forest classification algorithm using thermal cameras and digital colour parameters

Author:

ALTAY Yasin,ALBAYRAK DELİALİOĞLU Rabia

Publisher

Mediterranean Agricultural Sciences

Subject

General Engineering

Reference51 articles.

1. Akar Ö, Güngör O (2012) Rastgele orman algoritması kullanılarak çok bantlı görüntülerin sınıflandırılması. Jeodezi ve Jeoinformasyon Dergisi 1(2): 139-146.

2. Akkose M, Celal I (2017) Süt ineklerinde yatma süresinin topallıklara etkisi ve yatma süresini etkileyen faktörler. Lalahan Hayvancılık Araştırma Enstitüsü Dergisi 57(1): 44-51.

3. Alsaaod M, Schaefer AL, Büscher W, Steiner A (2015) The role of infrared thermography as a non-invasive tool for the detection of lameness in cattle. Sensors 15(6): 14513-14525.

4. Archer KJ, Kimes RV (2008) Empirical characterization of random forest variable importance measures. Computational Statistics & Data Analysis 52(4): 2249-2260.

5. Bobić T, Mijić P, Gregić M, Bagarić A, Gantner V (2017) Early detection of the hoof diseases in Holstein cows using thermovision camera. Agriculturae Conspectus Scientificus 82(2): 197-200.

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