Figure 1.

The platform was built by Faster R-CNN, the composition of Faster R-CNN. The convolutional layer is used to extract the features of the image. The input is the whole image and the output is a set of feature maps. The RPN, used for recommending candidate regions; ROI pooling: just as Faster R-CNN, this converts inputs of different sizes into outputs of fixed length; classification and regression, which produces the final output. Faster R-CNN: Faster region-based convolutional neural network; ROI: Region of interest; RPN: Region proposal network. Conv: Convolutions layers; Relu: Rectified linear unit layers; Pooling: Pooling layers; Full connection: Fully connection layers.