Author:
Sun Yanan,Yen Gary G.,Zhang Mengjie
Publisher
Springer International Publishing
Reference29 articles.
1. Howard, A. G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., & Adam, H. (2017). Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv:1704.04861.
2. Huang, G., Liu, S., van der Maaten, L., & Weinberger, K. Q. (2018). Condensenet: An efficient densenet using learned group convolutions. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 2752–2761). IEEE. ISBN 978-1-5386-6420-9. https://doi.org/10.1109/CVPR.2018.00291, https://ieeexplore.ieee.org/document/8578389/.
3. Liu, H., Simonyan, K., & Yang, Y. (2019). DARTS: Differentiable architecture search. In International Conference on Learning Representations.
4. Yang, T.-J., Howard, A., Chen, B., Zhang, X., Go, A., Sandler, M., Sze, V., & Adam, H. (2018). NetAdapt: Platform-aware neural network adaptation for mobile applications. In V. Ferrari, M. Hebert, C. Sminchisescu, & Y. Weiss (Eds.), Computer Vision—ECCV 2018 (Vol. 11214, pp. 289–304). Springer International Publishing. ISBN 978-3-030-01248-9 978-3-030-01249-6. https://doi.org/10.1007/978-3-030-01249-6_18.
5. Yao, S., Zhao, Y., Shao, H., Liu, S., Liu, D., Su, L., & Abdelzaher, T. (2018). Fastdeepiot: Towards understanding and optimizing neural network execution time on mobile and embedded devices. In Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems—SenSys ’18 (pp. 278–291). ACM Press. ISBN 978-1-4503-5952-8. https://doi.org/10.1145/3274783.3274840.