Abstract

As a classic subject in the field of image processing and computer vision, target detection has a wide range of applications in traffic monitoring, image retrieval, human-computer interaction and so on. It aims at detecting objects of interest in a static image. In view of the strong expressive ability of convolutional neural networks in deep learning, this paper presents the classical detection framework R-CNN of deep learning. Based on the above detection framework, the functional requirements, such as data pre-processing, training model and image prediction, as well as the non-functional requirements of the target detection system are analysed. According to the above requirements, a target detection system based on deep learning is developed. Practice has proved that the system has good performance in terms of hardware and performance.

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