The invention discloses an optical remote sensing image target detection method based on an integrated deep convolutional network, and mainly solves problems in the prior art that the number of targets which are wrongly detected and a testing process is complex and tedious. The method comprises the following specific steps: (1), constructing a multi-branch deep network; (2), generating a trainingdata set containing a target area; (3), carrying out the first training of the integrated deep convolutional network; (4), generating training data sets of all regions; (5), carrying out the second training of the integrated deep convolutional network; (6), generating a test data set; (7), obtaining a test result map; (8), calculating an average precision. The method can achieve the extraction oftarget candidate frames of all no-target regions as negative samples, makes the most of the information of an optical remote sensing image, achieves the better discrimination of the target in the optical remote sensing image and a complex background, is simple in testing process, and is small in number of targets which are wrongly detected in a detection result.