Author:
Ding Yadong,Wu Yu,Huang Chengyue,Tang Siliang,Wu Fei,Yang Yi,Zhu Wenwu,Zhuang Yueting
Subject
Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications
Reference72 articles.
1. H. Cai, L. Zhu, S. Han, Proxylessnas: Direct neural architecture search on target task and hardware. arXiv preprint arXiv:1812.00332, 2018.
2. Estimating depth from monocular images as classification using deep fully convolutional residual networks;Cao;IEEE Trans. Circuits Syst. Video Technol.,2017
3. J. Chang, Y. Guo, M. Gaofeng, Z. Lin, S. Xiang, C. Pan, et al., Data: Differentiable architecture approximation with distribution guided sampling, IEEE Trans. Pattern Anal. Mach. Intell. (2020).
4. X. Chen, L. Xie, J. Wu, Q. Tian, Progressive differentiable architecture search: Bridging the depth gap between search and evaluation. arXiv preprint arXiv:1904.12760, 2019.
5. T.W. Chin, C. Zhang, D. Marculescu, Layer-compensated pruning for resource-constrained convolutional neural networks. arXiv preprint arXiv:1810.00518, 2018.
Cited by
20 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献