信阳师范学院学报（自然科学版）2025，Vol.38Issue(1)：59-65,7.DOI:10.3969/j.issn.2097-583X.2025.01.008
融合通道和空间注意力的茶叶病害目标检测方法
Tea disease detection method using fusion of channel and spatial attentions
摘要
Abstract
Accurate and rapid detection of tea disease is of great economic significance to the tea industry. However,the problems such as scale variation,mutual occlusion and complex background of disease-affected leaves greatly reduce the prediction accuracy of the detector. A tea disease target detection method,integrating channel-spatial attention,was proposed to achieve accurate and efficient disease detection. Firstly,the multi-layer self-attention mechanism was used to extract multi-scale features of tea diseases to obtain local detail features of tea images at different scales. Secondly,the new channel attention module was introduced to extract richer channel information,suppress complex background noise and enhance the ability of model feature representation. In addition,a new spatial attention module was also proposed to further extract the spatial relationship of features,reduce redundant information and optimize computational overhead. The experimental results showed that the tea pest detection method with channel-spatial attention could cope with the challenges of leaf scale changes,mutual occlusion and complex background.关键词
茶叶病害检测/目标检测/通道注意力/空间注意力/特征融合Key words
tea disease detection/object detection/channel attention/spatial attention/feature fusion分类
计算机与自动化引用本文复制引用
孙艳歌,蒋明毅,冯岩,郭华平,张莉,吴飞..融合通道和空间注意力的茶叶病害目标检测方法[J].信阳师范学院学报（自然科学版）,2025,38(1):59-65,7.基金项目
国家自然科学基金项目(62062004) （62062004）
河南省自然科学基金项目(232300421167) （232300421167）
河南省留学人员科研择优资助项目 （）
