Bilateral attention mechanism-based target detection method under complex background

The invention discloses a bilateral attention mechanism-based target detection method under a complex background, which can be used for carrying out accurate foreground target detection under the complex background. The method mainly comprises the following steps: constructing a training set, a verification set and a test set according to a disclosed target detection data set under a complex background; constructing an artificial neural network detection model Bi-SINet based on a bilateral attention mechanism; an SGD optimizer is used on a Pytorch deep learning platform to optimize the Bi-SINet model; and the detection performance of the convergent Bi-SINet network model is evaluated on the constructed test set. Compared with a current main target detection algorithm SINet under a complex background, the method provided by the invention can obtain better detection performance. According to the method, the average absolute error is reduced, a higher enhancement-alignment index, a structure index and a weighted