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A Novel Modified Evolutionary Algorithm based Image Retrieval Framework : Theoretical Analysis and Applications
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- 발행기관
- 보안공학연구지원센터(IJSIP) 바로가기
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- 간행물
- International Journal of Signal Processing, Image Processing and Pattern Recognition 바로가기
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- 통권
- Vol.9 No.1 (2016.01)바로가기
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- 페이지
- pp.221-230
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A270091
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- With the fast development of data analysis and computer science technology, the design and implementation of image retrieval system has been a hot topic. The prior research focus more on image-size based approaches which are not intelligent or convenient. In this paper, we present a novel modified evolutionary algorithm based image retrieval framework theoretically with applications. To achieve more accuracy in less number of iteration, this paper, proposed a new approach to enhance the performance of content guided retrieval methodology by improving the performance of RF through Particle Swarm Optimization, Genetic Algorithm and Support Vector Machine. The objective of using Genetic Algorithm and Particle Swarm Optimization is to increase the number of images in relevant set where SVM is used to classify the relevant and irrelevant images. The experimental and numerical simulation indicate the efficiency of our method which means the presented technique is helpful in the fields where high accuracy rate of image retrieval is required. Further work of interest is also discussed in the final section.
목차
Abstract
1. Introduction
2. The Background and Related Preliminary Knowledge
2.1. The Related Work
2.2. The Genetic Algorithm
2.3. The Particle Swarm Optimization Framework
3. Our Proposed Framework
3.1. Theoretical Overview
3.2. The Swarm Representation and User Feedback
3.3. The Swarm Initialization and Fitness Evaluation
3.4. The GA Procedure and Further Steps
4. Experiment and Simulation Result
4.1. The Set-up of the Experiment
4.2. The Experiment and Result
4.3. The Numeric Analysis of the Result
5. Conclusion and Summary
References
키워드
Image Retrieval Evolutionary Algorithm Content Guided Retrieval Methodology Particle Swarm Optimization Theoretical Research저자
간행물 정보
발행기관
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- 발행기관명
- 보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
- 설립연도
- 2006
- 분야
- 공학>컴퓨터학
- 소개
- 1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업
간행물
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- 간행물명
- International Journal of Signal Processing, Image Processing and Pattern Recognition
- 간기
- 격월간
- pISSN
- 2005-4254
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.9 No.1
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