https://scholars.lib.ntu.edu.tw/handle/123456789/598033
Title: | Image Recognition based on Dynamic Highway Networks [基於動態高速公路類神經網路之圖像識別研究] | Authors: | Wang S.-H Lin W.-Z Huang H.-P. HAN-PANG HUANG |
Keywords: | Dynamic highway networks;Highway networks;Machine learning;Complex networks;Image recognition;Motor transportation;Structural optimization;Convolution neural network;Hyperparameters;Machine learning technology;Near-optimal;ON dynamics;Self-adjusting;Multilayer neural networks | Issue Date: | 2021 | Journal Volume: | 42 | Journal Issue: | 1 | Start page/Pages: | 23-31 | Source: | Journal of the Chinese Society of Mechanical Engineers, Transactions of the Chinese Institute of Engineers, Series C/Chung-Kuo Chi Hsueh Kung Ch'eng Hsuebo Pao | Abstract: | With the development of machine learning technology, more and more complex networks are developed. For those networks, determining the hyperparameters is important so that they can provide the best performance under the structure of neural network. However, more parameters should be decided in complex networks. This paper is focused on developing a structure of neural networks which can tune the width in each layer based on the utility of neurons automatically. In order to realize this function, a new structure of neural network called convolution neural network based dynamic highway network is proposed to deal with image recognition problem. With the self-adjusting method, near optimal structure and few parameters are required for training to achieve the same and even better performance which uses more neurons. ? 2021, Chinese Mechanical Engineering Society. All right reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112670055&partnerID=40&md5=6dc580abf8129f2a31f83266e2ba66d4 https://scholars.lib.ntu.edu.tw/handle/123456789/598033 |
ISSN: | 02579731 |
Appears in Collections: | 機械工程學系 |
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