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首页> 外文期刊>Computers and Electronics in Agriculture >Recognition of Pantaneira cattle breed using computer vision and convolutional neural networks
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Recognition of Pantaneira cattle breed using computer vision and convolutional neural networks

机译:使用计算机视觉和卷积神经网络认识Pantaneira牛品种

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摘要

The objective of this paper is to provide recognition for Pantaneira cattle breed using Convolutional Neural Networks (CNN). Fifty-one animals from the Aquidauana Pantaneira cattle Center (NUBOPAN) were studied. The center is located in the Midwest region of Brazil. Four monitoring cameras were distributed in the fences and took 27,849 images of Pantaneira cattle breed using different angles and positions. The following three CNN architectures were used for the experiment DenseNet-201, Resnet50 and Inception-Resnet-V. All networks were submitted to 10-fold stratified cross-validation over 50 epochs. The results showed an accuracy of 99% in all networks, which is encouraging for future research.
机译:本文的目的是利用卷积神经网络(CNN)为Pantaneira牛品种提供识别。 研究了来自Aquidauana Pantaneira牛中心(Nubopan)的五十一只动物。 该中心位于巴西中西部地区。 使用不同的角度和位置,在围栏中分发了四个监控摄像机,并使用了27,849份Pantaneira牛种子图像。 以下三个CNN架构用于实验DenSenet-201,Reset50和Inception-Resnet-V. 所有网络都提交到50多个时期的10倍分层交叉验证。 所有网络中的结果表明,所有网络的准确性为99%,这是对未来的研究令人鼓舞的。

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