@inproceedings{9b065fe0c6f54b36b1e335ea115da705,
title = "Review of Object Detection Techniques",
abstract = "As the front-end technology of artificial intelligence, computer vision has been widely studied in recent years, and the introduction of deep learning methods has accelerated this process. This paper shows the progress made in object detection in the last 5 years, followed by the mainstream model topology including Convolutional Neural Network and Transformer. We further compared the accuracy and model complexity of different backbones, analyzed the differences and the inner link between Convolutional Neural Network and Transformer, at the end of the thesis, the prospect of future development is presented.",
keywords = "Computer Vision, Convolutional Neural Networks, Deep Learning, Object Detection, Transformer",
author = "Boyang Yu and Feng Jin and Lei Dong and Mengqi Gao and Yanbo Jia",
note = "Publisher Copyright: {\textcopyright} 2022 Technical Committee on Control Theory, Chinese Association of Automation.; 41st Chinese Control Conference, CCC 2022 ; Conference date: 25-07-2022 Through 27-07-2022",
year = "2022",
doi = "10.23919/CCC55666.2022.9902668",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "7136--7143",
editor = "Zhijun Li and Jian Sun",
booktitle = "Proceedings of the 41st Chinese Control Conference, CCC 2022",
address = "United States",
}