Earticle

초록

영어

As accidents and crimes have increased at an alarming rate lately, most people are faced with the necessity of security and surveillance in private places as well as in public places. Therefore, the demand for intelligent surveillance systems has been increasing, and various technologies for image recognition and analysis from cameras are being developed for use in automatic monitoring. Among these techniques, the most popular and advanced method is deep learning. It is a field of machine learning based on neural networks. In this paper, we propose the object classifier technique with the Convolutional Neural Networks (CNN) algorithm, which is most widely used in image processing. Additionally, we implement the image analysis bot system based on the above proposed algorithm.

목차

Abstract
 1. Introduction
 2. Convolutional Neural Networks
  2.1. Affiliations
  2.2. Subsampling Layers
  2.3. Full Connection Layers
 3. Experimental Results
  3.1. Pedestrian Detection
  3.2. Application of Intelligent Surveillance System
 4. Conclusions
 Acknowledgments
 References

키워드

저자

• Ming-Shou An [ Dong-A University, Dept. of Electronics Engineering, 37 Nakdong-daero 550 beon-gil Saha-gu, Busan, Korea ]
• Dae-Seong Kang [ Dong-A University, Dept. of Electronics Engineering, 37 Nakdong-daero 550 beon-gil Saha-gu, Busan, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605