中国农业大学学报2025，Vol.30Issue(8)：132-140,9.DOI:10.11841/j.issn.1007-4333.2025.08.12
基于改进TransformerCNN的轻量化笼养鸡发声识别模型
A lightweight cage chicken vocalization recognition model based on improved TransformerCNN
摘要
Abstract
To solve the problems of high difficulty and poor real-time detection of traditional cage chicken vocalization,this paper proposes a chicken vocalization detection algorithm based on lightweight TransformerCNN.Firstly,by introducing the EfficientViT lightweight network to replace the original backbone network,the number of parameters and computational complexity are reduced,and the real-time performance of network algorithm detection is improved;Secondly,replacing ReLU with Hardswift activation function can improve the recognition accuracy of the model without adding additional weights and bias parameters.Finally,by combining linear self-attention mechanism instead of traditional Softmax operation,the model's ability to capture chicken vocalization features is further enhanced,improving the robustness of detection.The results show that:1)Compared with the basic TransformerCNN model,the introduction of EfficientViT,linear self-attention,and Hardswift activation function significantly improves the inference speed and computational complexity of the model.Although the average accuracy slightly decreases,it performs better in real-time performance and lightweight nature.2)Compared with other lightweight backbone networks,EfficientViT has significant advantages in inference speed,computational complexity,and model storage requirements,making it suitable for real-time audio classification tasks.3)Compared with mainstream audio classification models,TC+EfficientViT has improved detection accuracy,real-time performance,and model size,which can better meet the requirements of efficient and real-time deployment.In conclusion,in the intelligent welfare breeding environment,through contactless detection of chicken vocalization,a database of vocalizations in cage chicken populations can be established,providing key data for further analysis of chicken health status.关键词
笼养鸡/发声识别/轻量化模型/实时检测/EfficientViTKey words
cage chicken farming/voice recognition/lightweight model/real-time detection/efficientViT分类
农业科技引用本文复制引用
祝万军,王蕾,李鹏,袁超,陈金鑫,唐瑜嵘,沈明霞..基于改进TransformerCNN的轻量化笼养鸡发声识别模型[J].中国农业大学学报,2025,30(8):132-140,9.基金项目
江苏省科技项目(BE2022379) （BE2022379）
