SAR target detection method based on neural architecture search

The invention discloses an SAR target detection method based on neural architecture search, and relates to the technical field of target detection, and the method comprises the following steps: inputting SAR image data into an SAR target detection model based on neural architecture search, and outputting an SAR target detection result; comprising the following steps: performing feature extraction on SAR image data based on a plurality of search layers of a backbone network searcher; the extracted features are integrated based on a Neck module; and predicting the integrated features based on a Head module to obtain an SAR target detection result. According to the SAR target detection model based on neural architecture search, a high-precision and light-weight model suitable for a current SAR target detection task can be obtained through automatic design, and the manual design burden is greatly relieved. 本发明公开了一种基于神经架构搜索的SAR目标检测方法，涉及目标检测技术领域，包括以下步骤：将SAR图像数据输入至基于神经架构搜索的SAR目标检测模型，输出SAR目标检测结果；包括基于主干网络搜索器的多个搜索层对SAR