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First, an improved image object detection method based on faster Region-Convolutional Neural Network (RCNN) is proposed, and Region of Interest (ROI) align is used instead of RoI pooling to reduce the error in the pooling process. Second, it adds the layer of convolution before adding network full-connection layer, thus reducing its parameters, enhance the performance of the classifier and avoid over-fitting. Finally, the combination of softmax and central loss functions is for training network-based model to increase the differences between categories and reduce the changes within categories, and thus the model with network could have more targeted and diversified features. 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