Recognition and Classification of Broiler Droppings Based on Deep Convolutional Neural Network
Joint Authors
Wang, Jintao
Shen, Mingxia
Liu, Longshen
Xu, Yi
Okinda, Cedric
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-11-27
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Digestive diseases are one of the common broiler diseases that significantly affect production and animal welfare in broiler breeding.
Droppings examination and observation are the most precise techniques to detect the occurrence of digestive disease infections in birds.
This study proposes an automated broiler digestive disease detector based on a deep Convolutional Neural Network model to classify fine-grained abnormal broiler droppings images as normal and abnormal (shape, color, water content, and shape&water).
Droppings images were collected from 10,000 25-35-day-old Ross broiler birds reared in multilayer cages with automatic droppings conveyor belts.
For comparative purposes, Faster R-CNN and YOLO-V3 deep Convolutional Neural Networks were developed.
The performance of YOLO-V3 was improved by optimizing the anchor box.
Faster R-CNN achieved 99.1% recall and 93.3% mean average precision, while YOLO-V3 achieved 88.7% recall and 84.3% mean average precision on the testing data set.
The proposed detector can provide technical support for the detection of digestive diseases in broiler production by automatically and nonintrusively recognizing and classifying chicken droppings.
American Psychological Association (APA)
Wang, Jintao& Shen, Mingxia& Liu, Longshen& Xu, Yi& Okinda, Cedric. 2019. Recognition and Classification of Broiler Droppings Based on Deep Convolutional Neural Network. Journal of Sensors،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1187490
Modern Language Association (MLA)
Wang, Jintao…[et al.]. Recognition and Classification of Broiler Droppings Based on Deep Convolutional Neural Network. Journal of Sensors No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1187490
American Medical Association (AMA)
Wang, Jintao& Shen, Mingxia& Liu, Longshen& Xu, Yi& Okinda, Cedric. Recognition and Classification of Broiler Droppings Based on Deep Convolutional Neural Network. Journal of Sensors. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1187490
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1187490