关键词: 多数据集学习, 修图识别, 深度学习, 神经网络设计, 图像处理

Abstract:

The rapid development of image processing software has led to the rise of a large number of repair and beautification applications in the field of mobile applications. However, their popularity has also brought some social problems and security problems, such as the serious distortion of online lovers, the forgery of photographic works, etc. For mobile phone image modification APP software, a neural network model based on multi-dataset learning is proposed and its network topology is given. Different from the traditional parallel operation of multiple neural networks, the proposed network model can share the model parameters, and learn multiple data sets at the same time. Thus, the detection application has the ability of multi-feature recognition. In addition, a loss function for multi-task network model is proposed to enhance the ability of deep feature learning. The experimental results show that the accuracy of the proposed method is higher than that of the traditional method. The generalization performance of the proposed method is superior, and it can recognize the image which has been repaired by many kinds of software.

Key words: multi-dataset learning, image modification recognition, deep learning, design of neural network, image processing