关键词: 目标检测, 深度学习, 计算机视觉, 卷积神经网络, 目标分类检测

Abstract: Object detection is an important problem in computer vision, which has critical research value in the field of pedestrian tracking, license plate recognition and unmanned driving. In recent years, the accuracy of image classification is greatly improved with deep learning, thus the object detection methods based on deep learning have gradually become mainstream. The development and present situation of object detection methods are reviewed, and a prospect is made. Firstly, the development, improvement and deficiency of the traditional algorithms and depth learning-based algorithms are summarized, and then compared. Finally, the difficulties and challenges of the object detection method based on deep learning are discussed, and the possible development direction is prospected.

Key words: object detection, deep learning, computer vision, convolutional neural networks, object classification detection