深羊:家畜面部图像的亲属关系分配

Lech Szymanski, Michael Lee
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引用次数: 2

摘要

对于不务农的人来说,所有的羊可能看起来都一样,但实际上它们在形态上有很大的不同;包括面部特征。图像分析已经证明,基于计算机的牲畜面部识别是非常准确的。我们研究了深度学习在遗传评估中分配牲畜亲属关系的可行性-给定两张羊脸图像,我们提出的模型预测它们的遗传关系。在这项工作中,我们提出了两个CNN模型:一个用于人脸检测(报告80%的准确率),另一个用于亲属关系检测(报告68%的平衡准确率)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Sheep: kinship assignment in livestock from facial images
For the non-farmer folk all sheep might look the same, but they are in fact morphologically quite different; including when it comes to facial features. Image analysis has already demonstrated that computer-based facial recognition in livestock is very accurate. We investigate the viability of deep learning for assigning kinship in livestock for use in genetic evaluation- given two images of sheep faces, our proposed model predicts their genetic relationship. In this work we present two CNN models: one for face detection (reporting 80% accuracy) and one for kinship detection (reporting 68% balanced accuracy).
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