The invention provides a method for detecting and identifying dense weak and small targets in a wide remote sensing image. According to the method, sample amplification is carried out by means of Mosaic, rotation, MixUp, zooming and the like, and abundant and multi-scale training samples are obtained; secondly, improving a YOLOv5 network by utilizing Transform, adding a weak and small target detection head, enhancing the characterization capability of the model on global information and context information in an image, and improving the weak and small target detection and recognition performance in a dense scene; meanwhile, a multi-model fusion prediction method is used, the prediction precision is improved, and the model is prevented from falling into local optimum; and finally, detecting and identifying dense weak and small targets in the wide remote sensing image by using a block detection method. According to the method, multi-model fusion prediction is used, the model target detection and identification capability can be improved, and the model is prevented from falling into local optimum.