DOI
stands for Digital Object Identifier
（
D
igital
O
bject
I
dentifier
）
,
and is the unique identifier for objects on the internet. It can be used to create persistent link and to cite articles.
Using DOI as a persistent link
To create a persistent link, add「http://dx.doi.org/」
「
http://dx.doi.org/
」
before a DOI.
For instance, if the DOI of an article is
10.5297/ser.1201.002
, you can link persistently to the article by entering the following link in your browser:
http://dx.doi.org/
10.5297/ser.1201.002
。
The DOI link will always direct you to the most updated article page no matter how the publisher changes the document's position, avoiding errors when engaging in important research.
Cite a document with DOI
When citing references, you should also cite the DOI if the article has one. If your citation guideline does not include DOIs, you may cite the DOI link.
DOIs allow accurate citations, improve academic contents connections, and allow users to gain better experience across different platforms. Currently, there are more than 70 million DOIs registered for academic contents. If you want to understand more about DOI, please visit airiti DOI Registration （ doi.airiti.com ） 。
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A study on the convolutional neural algorithm of image style transfer
鮑奕諠 , Masters Advisor：林慧珍
繁體中文
最大池化 ； 倒傳遞 ； 風格轉換 ； 過度擬合 ； 深度卷積類神經網路 ； 全卷積網路 ； 感知域 ； 卷積核 ； 合併卷積核 ； max-pooling ； back-propagation ； style transfer ； over-fitting ； deep convolutional neural networks (DCNN) ； fully convolutional networks ； receptive field ； kernel ； merge kernel
- [1] O. Abdel-Hamid, A. Mohamed, and H. Jiang, "Convolutional neural networks for speech recognition," IEEE/ACM Trans. Audio, Speech and Lang.Proc., vol. 22, pp. 1533-1545, Oct., 2014.
連結：
- [2] S. Bell and K. Bala, "Learning visual similarity for product design with convolutional neural networks," ACM Trans. Graph., vol. 34, pp. 98:1-98:10, Aug., 2015.
連結： - [3] Y. Bengio, "Learning deep architectures for AI," Foundations and Trends in Machine Learning, vol. 2, pp. 1-127, 2009.
連結： - [4] A. Dosovitskiy, J. T. Springenberg, and T. Brox, "Learning to generate chairs with convolutional neural networks," CoRR, abs/1411.5928, 2014. Available: http://arxiv.org/abs/1411.5928.
連結： - [5] K. Fukushima, "Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position," Biological Cybernetics, vol. 36, pp. 193-202, 1980.
連結：
