Cat’s Nose Recognition Using You Only Look Once (Yolo) and Scale-Invariant Feature Transform (SIFT)
Rifka Widyastuti, Chuan‐Kai Yang · 2018
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%.