Improved ResNet-50 deep learning algorithm for identifying chicken gender.

Accurate identification of chicken gender helps farms to optimize breeding sex ratios and programs. A chicken gender identification method based on an improved ResNet-50 deep learning algorithm was proposed in this study. The Squeeze-and-Excitation (SE) attention was introduced to improve the residual units of ResNet-50, and the Swish function and Ranger optimizer were combined for ensuring feature learning and training effectiveness to further enhance the model performance. A public dataset acquired from a commercial farm was used to train and test the algorithm, which has a total of 960 images of chickens with different genders, scenes, and behaviors. The ablation tests were performed to verify the contribution of the SE module, Swish, and Ranger optimizer to the algorithm. The deep features of the proposed algorithm were visualized with heat maps to show the contribution of different body parts to gender identification. Moreover, the algorithm was compared with five typical recognition...