Abstract 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.

中文翻译：

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使用计算机视觉和卷积神经网络识别 Pantaneira 牛品种

摘要 本文的目的是使用卷积神经网络 (CNN) 为 Pantaneira 牛品种提供识别。研究了来自 Aquidauana Pantaneira 牛中心 (NUBOPAN) 的 51 只动物。该中心位于巴西中西部地区。四个监控摄像机分布在围栏内，使用不同角度和位置拍摄了 27,849 幅 Pantaneira 牛品种的图像。实验使用了以下三种 CNN 架构：DenseNet-201、Resnet50 和 Inception-Resnet-V。所有网络都提交了超过 50 个时期的 10 倍分层交叉验证。结果表明，所有网络的准确率都达到了 99%，这对未来的研究是令人鼓舞的。