Open Access
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
Article Number 01024
Number of page(s) 5
Section Modeling, Analysis, and Simulation of Intelligent Manufacturing Processes
Published online 19 June 2018
  1. Xingchen Zhou. Deep Model Based Offline Handwritten Chinese Character Recognition[D]. ZheJiang University,2016. [Google Scholar]
  2. Zhiqiang Liu, Yong Dou, Jingfei Jiang, Jinwei Xu, Shijie Li, Yongmei Zhou, and Yingnan Xu. 2017. Throughput-Optimized FPGA Accelerator for Deep Convolutional Neural Networks. ACM Trans. Reconfigurable Technol. Syst. 10, 3, Article 17 (July 2017), 23 pages. DOI: 10.1145/3079758 [Google Scholar]
  3. Mingxing Duan, Kenli Li, Canqun Yang, Keqin Li, A hybrid deep learning CNN–ELM for age and gender classification, Neurocomputing, Volume 275,2018,Pages 448-461,ISSN 0925-2312, DOI:10.1016/j.neucom.2017.08.062 [Google Scholar]
  4. Yu Zijian. FPGA-based Accelerator For Convolutional Neural Network[D].ZheJiang University,2016. [Google Scholar]
  5. Hiroki Nakahara, Tomoya Fujii, and Shimpei Sato. 2017. A fully connected layer elimination for a binarizec convolutional neural network on an FPGA. In Field Programmable Logic and Applications (FPL), 2017 27th International Conference on.IEEE, 1–4 [Google Scholar]
  6. Li Jiao, Cheng Luo, Wei Cao, Xuegong Zhou, and Lingli Wang. 2017. Accelerating low bit-width convolutional neural networks with embedded FPGA. In Field Programmable Logic and Applications (FPL), 2017 27th International Conference on. IEEE, 1–4. [Google Scholar]
  7. Fengfu Li, Bo Zhang, and Bin Liu. 2016. Ternary weight networks. arXiv preprint arXiv:1605.04711 (2016). [Google Scholar]
  8. M. Rastegari, V. Ordonez, J. Redmon, and A. Farhadi. XNORNet: ImageNet Classification Using Binary Convolutional Neural Networks. European Conference on Computer Vision (ECCV), Oct 2016. arXiv:1603.05279. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.