Target detection method and device based on attention mechanism deep learning network

The invention provides a target detection method based on an attention mechanism deep learning network. The method is characterized by comprising: extracting a feature map of an image to be detected through a target detection model containing an attention mechanism module, detecting the position and the category of a target from the feature map, and the attention mechanism module comprising at least one attention module M1 used for generating an attention weight matrix with the same size according to the feature map and acting on the feature map; at least one attention receptive field module M2 used for carrying out feature extraction on the feature map; and at least one attention feature fusion module M3 used for fusing the features of different levels of the network. According to the target detection method, high detection speed is ensured on the basis of high detection accuracy, and meanwhile, the model is simple in structure and small in calculated amount. 本发明提供一种基于注意力机制深度学习网络的目标检测方法，其特征在于，通过含有注意力机制模块的目标检