BVCNN: a multi-object image recognition method based on the convolutional neural networks

摘要

This article puts forward a kind of huge amounts of multi-object image recognition method - BVCNN. Firstly, BING method is used to recognize images, which greatly reduces the time of estimating image targets, and makes it possible that quickly identify multiple target images, compared to traditional convolution neural networks only achieving single target image recognition; Secondly, vectorization of deep convolutional neural networks is used for deep learning of characteristics in local image and recognition, which speeds up network training and testing; thirdly, using the context information in multi-object image classification, to a certain extent, helps to distinguish individual of similar characteristics according to environment, improving the multi-object image recognition accuracy. According to experiments, identifying a single image by this model only need less than 1 s, and this model can be used for image information fusion.