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Deep Learning Based Computer Vision Technique for Automatic Heat Detection in Cows

机译:基于深度学习的计算机视觉技术,用于母牛的自动热量检测

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This paper presents a novel deep learning based computer vision technique for automatically monitoring the heat in cows by detecting the heat detector device such as Kamar and its colour. The proposed technique learns the device characteristics and colour properties. It extracts heat detectors from the back of the cow and classifies the device into colour change and no colour change. The main purpose of the technique is to identify the color change in heat detectors on the back of the cow body so that a camera can be installed around a water point or walk over weighing machine. The image data of cows with heat detectors have been collected. The technique has been evaluated on the collected data. The experimental results on a small data showed that the technique can automatically and accurately detect the colour change.
机译:本文提出了一种新颖的基于深度学习的计算机视觉技术,该技术可通过检测热检测器设备(例如Kamar及其颜色)来自动监视奶牛的热量。拟议的技术学习设备的特性和颜色属性。它从母牛的背部抽出热探测器,并将设备分类为变色和无变色。该技术的主要目的是识别奶牛身体背面的热探测器中的颜色变化,以便可以在水位附近安装摄像机或在称重机上行走。带有热探测器的奶牛的图像数据已被收集。该技术已对收集的数据进行了评估。在少量数据上的实验结果表明,该技术可以自动,准确地检测颜色变化。

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