Individual Dairy Cattle Recognition Based on Deep Convolutional Neural Network

张满囤; 单新媛; 于津苏; 郭迎春; 李睿文; 徐明权

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Individual Dairy Cattle Recognition Based on Deep Convolutional Neural Network

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摘要

Image based individual dairy cattle recognition has gained much attention recently. In order to further improve the accuracy of individual dairy cattle recognition, an algorithm based on deep convolutional neural network( DCNN) is proposed in this paper,which enables automatic feature extraction and classification that outperforms traditional hand craft features. Through making multigroup comparison experiments including different network layers,different sizes of convolution kernel and different feature dimensions in full connection layer,we demonstrate that the proposed method is suitable for dairy cattle classification. The experimental results show that the accuracy is significantly higher compared to two traditional image processing algorithms: scale invariant feature transform( SIFT) algorithm and bag of feature( BOF) model.

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《东华大学学报：英文版》 |2018年第2期|107-112|共6页
作者
张满囤; 单新媛; 于津苏; 郭迎春; 李睿文; 徐明权;
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作者单位

School of Computer Science and Engineering;

Hebei University of Technology;

Tianjin 300401;

China;

Hebei Province Key Laboratory of Big Data Calculation;

Tianjin 300401;

China;

Traditional Chinese Veterinary Medicine College;

Agricultural University of Hebei;

Baoding 071000;

China;

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原文格式 PDF
正文语种 chi
中图分类 TP391.41;
关键词
deep; learning; deep; convolutional; neural; network(DCNN); dairy; cattle; individual; recognition;

Individual Dairy Cattle Recognition Based on Deep Convolutional Neural Network

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