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Low-power object-detection challenge on unmanned aerial vehicles

Nature Machine Intelligence volume 4, pages 1265–1266 (2022)Cite this article

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A design contest for object detection with deep learning on embedded small devices leads to winning hardware–software co-design approaches.

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Fig. 1: IoU, power and throughput performance of each year’s top three teams from 2018 to 2022.

References

  1. Xu, X. et al. IEEE Trans. Pattern Anal. Mach. Intell. 43, 392–403 (2019).

    Article  Google Scholar 

  2. Wang, Y. et al. in Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence (Thiruvathukal, G. K., Lu, Y.-H., Kim, J., Chen, Y. & Chen, B.) pp. 35–64 (CRC Press, 2022).

  3. Zhang, X. et al. in 36th International Conference on Machine Learning (ICML) Workshop on ODML-CDNNR (2019).

  4. Zhang, X. et al. in Conference on Machine Learning and Systems (MLSys) (2020).

  5. Bao, Z., Zhan, K., Zhang, W. & Guo, J. in 2021 IEEE Symposium in Low-Power and High-Speed Chips (COOL CHIPS) https://doi.org/10.1109/COOLCHIPS52128.2021.9410327 (IEEE, 2021).

  6. Jiang, W., Yu, H., Liu, X., Sun, H., Li, R. & Ha, Y. in 2021 58th ACM/IEEE Design Automation Conference (DAC), pp. 1027–1032 (IEEE, 2021).

  7. Guoqing, L. Zhang, M., Li, J., Lv, F. &Tong, G. Pattern Recognit. 109, 107610 (2021).

  8. Jiang, W. et al. IEEE Trans. Comp. Aided Des. Integr. Circuits Syst. 39, 4805–4815 (2020).

    Article  Google Scholar 

  9. Jiang, W. et al. IEEE Trans. Comput. 70, 595–605 (2021).

    Article  MathSciNet  Google Scholar 

  10. Goeders, J., Hao, C. & Zhuo, C. Contest Winning Designs; https://byuccl.github.io/dac_sdc_2022/info/ (2022).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA

    Zhenge Jia & Yiyu Shi

  2. Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China

    Xiaowei Xu

  3. Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA

    Jingtong Hu

Authors
  1. Zhenge Jia
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  2. Xiaowei Xu
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  3. Jingtong Hu
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  4. Yiyu Shi
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Correspondence to Yiyu Shi.

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Jia, Z., Xu, X., Hu, J. et al. Low-power object-detection challenge on unmanned aerial vehicles. Nat Mach Intell 4, 1265–1266 (2022). https://doi.org/10.1038/s42256-022-00567-4

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