基于深度学习的牛脸识别方法综述OA

With the large-scale and intelligent development of animal husbandry in China,traditional cattle identification methods exhibit problems including easy detachment and stress induction and can hardly meet the requirements of precision livestock farming.Cattle face recognition technology based on Deep Learning provides a new approach for individual identification with its non-contact and high-precision characteristics.This paper systematically reviews the research progress of this technology.It illustrates the principles and advantages of Deep Learning in fine-grained recognition.It sorts out key technologies such as network structure optimization,few-shot learning and lightweight deployment.It summarizes the complete process from data collection to model evaluation.In view of current challenges including dependence on two-dimensional appearance features,large demand for annotated data and model complexity,this paper prospects future directions such as multi-modal fusion,self-supervised and few-shot learning and lightweight models to promote the in-depth application of this technology in smart animal husbandry.