A live pornographic image detection method based on semi-supervised learning in dense antagonistic networks
A semi-supervised learning and image detection technology, applied in image analysis, image enhancement, image data processing, etc., can solve the problems of long training time and low classification accuracy, reduce labor costs, improve detection accuracy, and improve identification ability Effect
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[0029] In order to better illustrate the technical solution of the present invention, the present invention will be further described below through an embodiment in conjunction with the accompanying drawings.
[0030] The content of pornographic images in this implementation case is defined as: through the visual depiction or representation of nudity, sexual organs, sexual intercourse, etc., images related to sex, which arouse the viewer's sexual interest and sexual excitement. Use pornographic images as positive samples and non-pornographic images as negative samples. Since the manual collection of sample images has the characteristics of long cycle, small quantity, and high cost, it cannot fully meet the large number of sample images required for model training. Therefore, other methods are needed to enhance the sample images, which can improve the recognition rate of model training to a certain extent. .
[0031] Step 1. Initial training data collection and labeling;
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