Objects Classification by Learning-Based Visual Saliency Model and Convolutional Neural Network

Figure 2

The algorithm flow chart of this paper. We establish a learning-based visual saliency model to simulate human visual information processing mechanism and then obtain saliency map which can be used to get the humans’ classification RoIs. CNN is used to simulate human neutral network, and the humans’ classification RoIs is CNN’s input. After the processing of CNN, we obtain the result of classification which is close to humans.