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Chicken Disease Classification Based on Digital Images Using the YOLOv11 Method
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Date
Authors
Amelia, Malika
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Volume Title
Publisher
Politeknik Negeri Batam
Abstract
Abstract—Chicken diseases are still one of the main problems in the world of animal husbandry, especially for small farmers who do not
yet have access to adequate disease detection technology. To overcome this problem, this study aims to build a chicken disease
classification system that works based on digital images. This system uses the You Only Look Once version 11, YOLOv11 algorithm.
YOLO is a deep learning-based method that can be used to classify and detect objects quickly and efficiently. With this method, the system
developed is expected to be able to recognize the type of disease in chickens automatically only through images. The results of this system
are expected to be able to help farmers in early detection of chicken diseases so that treatment actions can be carried out more quickly and
precisely.
Keywords— Chicken Diseases, Digital Image Classification, Deep Learning, YOLOv11
Description
Citation
IEEE
