This paper presents an efficient strategy of applying the deep learning structure to solve the copy-move forgery detection problem. The copy-move forgery detection problem is to detect copy-move image forgery regions in an image. The proposed scheme first detects copy-move replaced regions using SRM filter. The BusterNet method detects the image foreground manipulation for searching the copy-move forgery regions. The presented scheme includes two major topics as foreground copy-move forgery regions detection and background copy-move forgery regions detection. The proposed scheme is a combination of these two schemes. In the proposed scheme, results of the Mask R-CNN and Semantic Co-Segmentation Network can be further utilized for detecting copy-move results.