|Table of Contents|

A Convolutional Neural Network Based on Mobile Application forIdentification of Buildings in Natural Scene(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2019年03期
Page:
37-
Research Field:
计算机工程
Publishing date:

Info

Title:
A Convolutional Neural Network Based on Mobile Application forIdentification of Buildings in Natural Scene
Author(s):
Xu Boming1; Liu Xiaofeng1; Ye Qiaolin1; Zhang Fuquan1; Zhou Jingzheng2
1.College of Information Science and Technology,Nanjing Forestry University,Nanjing 210042,China)(2.Bureau of Science and Information Technology,The Ministry of Public Security of the People’s Republic of China,Beijing 100741,China
Keywords:
transfer learning; deep learning; convolutional neural network; mobile system transplantation
PACS:
TP311
DOI:
10.3969/j.issn.1672-1292.2019.03.006
Abstract:
It is very difficult to identify the image of buildings in natural scenes due to the presence of background noise in natural scenes and the interference of complex factors such as illumination,rotation,and shooting angle. Aiming at the dependence of traditional building extraction methods on human design and the improvement of building edge feature extraction algorithm,the paper uses a convolutional neural network based on the image recognition technology to classify landmark buildings in natural scenes and the realistic demand to transplant CNN models to mobile terminals for fast identification of complex scenes,obtains bottleneck layer of MobileNet through Keras,and adds a new classifier for transfer learning. A large number of data augmentation and test set augmentation are applied to the input image. After three versions of transfer learning,the accuracy of 98.2%,95.6% and 97.2% are achieved within 480 iterations in three test set. Compared with other feature extraction algorithms,CNN has the advantages of non-transformation and automatic extraction of features,and achieves a higher accuracy in a shorter period of time. At the same time,MobileNet weight only occupies 15.3 MB with high precision and less calculation,which can be widely transplanted to mobile devices. The system based on model transplantation has the functions of photo recognition,photo album recognition,menu display,etc. Which provides a mobile platform users with a convenient and simple tool to quickly and accurately obtain the information of buildings in natural scenes.

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Last Update: 2019-09-30