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In the process of intelligent detection of surface defects, there would be several problems in practical applications, such as it is difficulty to collect magnetic core samples with defects, small defect target and the disequilibrium on defective samples and the hardness when locating defects. This article studies the existing problems that appear when detecting the surface defects on magnetic core,an image enhancement and detection method which based on deep learning is proposed. Primarily, the images of magnetic core defects are generated by deep convolutional generative adversarial network, and then the Poisson Blending method is used to produce the enhanced data set. Finally, the intelligent defect detection is achieved grounded on YOLO-v3 network. The experimental results indicate that the proposed method can yield images with higher quality and more clear defects, and the accuracy of defect detection is enhanced by 5.6%.