bib_template.bib

@inproceedings{cbam,
  title={Cbam: Convolutional block attention module},
  author={Woo, Sanghyun and Park, Jongchan and Lee, Joon-Young and Kweon, In So},
  booktitle={Proceedings of the European conference on computer vision (ECCV)},
  pages={3--19},
  year={2018}
}
@article{mobilenet,
  author       = {Andrew G. Howard and
                  Menglong Zhu and
                  Bo Chen and
                  Dmitry Kalenichenko and
                  Weijun Wang and
                  Tobias Weyand and
                  Marco Andreetto and
                  Hartwig Adam},
  title        = {MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
                  Applications},
  journal      = {CoRR},
  volume       = {abs/1704.04861},
  year         = {2017},
  url          = {http://arxiv.org/abs/1704.04861},
  eprinttype    = {arXiv},
  eprint       = {1704.04861},
  timestamp    = {Thu, 27 May 2021 16:20:51 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/HowardZCKWWAA17.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
@online{lee2021mlcourse,
  author = {Lee, Hung-Yi},
  title = {Machine Learning 2021 Course Slides},
  url = {https://speech.ee.ntu.edu.tw/~hylee/ml/ml2021-course-data/self_v7.pdf},
  year = {2021},
}
@online{kingma2014adam,
  title={Adam: A method for stochastic optimization},
  author={Kingma, Diederik P and Ba, Jimmy},
  url={https://arxiv.org/abs/1412.6980},
  year={2014},
  eprint={1412.6980},
  archivePrefix={arXiv}
}
@article{duchi2011adaptive,
  title={Adaptive subgradient methods for online learning and stochastic optimization.},
  author={Duchi, John and Hazan, Elad and Singer, Yoram},
  journal={Journal of machine learning research},
  volume={12},
  number={7},
  year={2011}
}
@mastersthesis {廖云飞,
author = { 廖云飞 },
title = {道路监控场景下渣土车苫盖检测方法研究},
school = {北京交通大学},
year = {2023}
}
@standard{公安联网标准,
  author    = { 陈朝武 and 崔云红 and 王冰洋 and 朱雷 and 廖双龙 and 孔维生 and 尹萍 },
  title     = {公共安全视频监控联网系统信息传输、交换、控制技术要求},
  edition   = {GB/T 28181-2022},
  year      = {2022},
  publisher = {国家市场监督管理总局;国家标准化管理委员会}
}
@patent{渣土车未苫盖检测,
  author = {山东大学 and 青岛海信信息科技股份有限公司},
  title  = {一种基于计算机视觉的渣土车未苫盖检测系统及检测方法},
  number = {CN202211382753.4},
  date   = {2022-12-23}
}