人工智能
卷积神经网络
计算机科学
模式识别(心理学)
计算机视觉
图像(数学)
特征提取
鉴定(生物学)
上下文图像分类
植物
生物
作者
Kailong Zhou,Zhuo Li,Zhen Geng,Jing Zhang,Xiao Guang Li
标识
DOI:10.1109/bigmm.2016.29
摘要
Considering the fact that pornographic images are flooding on the web, we propose a pornographic image recognition method based on convolutional neural network. This method can be divided into two parts: coarse detection and fine detection. Because majority of images are normal, we use coarse detecting to quickly identify the normal images with no or fewer skin-color regions and facial images. For the images which contain much more skin-color regions, they need further identification through fine detecting. At first, we trained the CNN using the strategy of pre-training mid-level features non-fixed fine-tuning, then based on the trained model, we can classify whether the image is pornographic or not. Compared with exiting methods, performance of our method is better than the state-of-the-art.
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