With rapid development of the Internet, the web contents become huge. Most of
the websites are publicly available and anyone can access the contents
everywhere such as workplace, home and even schools. Nev-ertheless, not all the
web contents are appropriate for all users, especially children. An example of
these contents is pornography images which should be restricted to certain age
group. Besides, these images are not safe for work (NSFW) in which employees
should not be seen accessing such contents. Recently, convolutional neural
networks have been successfully applied to many computer vision problems.
Inspired by these successes, we propose a mixture of convolutional neural
networks for adult content recognition. Unlike other works, our method is
formulated on a weighted sum of multiple deep neural network models. The
weights of each CNN models are expressed as a linear regression problem learnt
using Ordinary Least Squares (OLS). Experimental results demonstrate that the
proposed model outperforms both single CNN model and the average sum of CNN
models in adult content recognition.