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http://dx.doi.org/10.14400/JDC.2017.15.3.201

Performance Improvement of Object Recognition System in Broadcast Media Using Hierarchical CNN  

Kwon, Myung-Kyu (Dept. of Fusion Technology, Graduate School of Venture, Hoseo University)
Yang, Hyo-Sik (Samil PricewaterhouseCoopers)
Publication Information
Journal of Digital Convergence / v.15, no.3, 2017 , pp. 201-209 More about this Journal
Abstract
This paper is a smartphone object recognition system using hierarchical convolutional neural network. The overall configuration is a method of communicating object information to the smartphone by matching the collected data by connecting the smartphone and the server and recognizing the object to the convergence neural network in the server. It is also compared to a hierarchical convolutional neural network and a fractional convolutional neural network. Hierarchical convolutional neural networks have 88% accuracy, fractional convolutional neural networks have 73% accuracy and 15%p performance improvement. Based on this, it shows possibility of expansion of T-Commerce market connected with smartphone and broadcasting media.
Keywords
Convolutional Neural Network; T-Commerce; Deep Learning; Object Recognition; Pooling;
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