关键词: 深度卷积神经网络, 目标检测, 特征表达, 特征提取

Abstract: Deep convolutional Neural Networks（DNNs） have made breakthroughs in object detection, because of its more powerful ability of feature learning and feature representation. In this paper, the research progress of convolutional neural networks has been expounded in object detection. Firstly, the development and existing problems of traditional object detection are reviewed. It introduces the principles of the DNNs and the improvement of common techniques. Then, object detection framework which combines region proposal is introduced. It introduces YOLO algorithm, which aims at object detection as regression problem. Finally, some existing problems in the present study are briefly summarized and the new directions for future development are expected.

Key words: Deep convolutional Neural Networks（DNNs）, object detection, feature representations, feature extraction