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Cat’s Nose Recognition Using You Only Look Once (Yolo) and Scale-Invariant Feature Transform (SIFT)

机译:只看一次就可以识别猫的鼻子(Yolo)和尺度不变特征变换(SIFT)

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This paper proposes a cat recognition system through cat's nose using You only look once (Yolo) and Scale-Invariant Feature Transform (SIFT). For first part, this system detects the nose of a cat image using Yolo. After the nose is detected, we recognize the cat's nose using SIFT method and make sure that the nose has been recognized correctly. The accuracy of the nose detection is 99.85% for the first dataset which contains 700 images and 96.89% for the second dataset that contains 677 images. This system work with several step and do automatic. The cat's nose recognition system was tested by 1337 cat's image and 700 cat's nose images as reference data. Finally, the average accuracy of this system is 95.87%.
机译:本文提出了一种“只看一次”(Yolo)和尺度不变特征变换(SIFT)的猫鼻子识别系统。首先,该系统使用Yolo检测猫的鼻子。检测到鼻子后,我们使用SIFT方法识别猫的鼻子,并确保正确识别了鼻子。包含700张图像的第一个数据集的鼻子检测精度为99.85%,包含677张图像的第二个数据集的鼻子检测精度为96.89%。该系统分几步工作,并且自动执行。该猫的鼻子识别系统已通过1337张猫的图像和700张猫的鼻子图像作为参考数据进行了测试。最后,该系统的平均准确度为95.87%。

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