Combining Autoencoder and Yolov6 Model for Classification and Disease Detection in Chickens.

Nguyen KH, Nguyen HVN, Tran HN, Quach L-D. Combining Autoencoder and Yolov6 Model for Classification and Disease Detection in Chickens. ICIIT '23: Proceedings of the 2023 8th International Conference on Intelligent Information Technology. 2023; Pages 132-138. https://doi.org/10.1145/3591569.3591591

Summary: This study proposes a method for classifying and detecting diseases in chickens using a combination of Autoencoder and Yolov6 models. The approach utilizes computer vision to identify lesions and improve disease recognition across different chicken breeds. Data enhancement techniques were employed during preprocessing, resulting in an impressive validation mean average precision (val/mAP) of 99.15% and over 90% accuracy on the test dataset. The method shows potential for early detection of diseases in captive chicken populations, enhancing food safety and production quality for human consumption.