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水中青蛙

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[求助] 请大家帮助查找两篇论文的检索情况~

第一篇:
      篇名:Study on a rapid real-time feature extraction algorithm
      期刊:AMR   V.709     

第二篇:
      篇名:Improved BP neural network in diagnosis of nonlinear fault
      期刊:AMM    V.401-403
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fallsoft

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水中青蛙: 金币+5, ★★★★★最佳答案, 非常感谢! 2013-10-31 09:04:38
Accession number:       
20132916521223
        Title:        Study on a rapid real-time feature extraction algorithm
        Authors:         Xu, Bin1 Email author bin200602006@163.com; Li, Xiangna2 Email author 123595010@qq.com; Xue, Weining2 Email author 47607601@qq.com
        Author affiliation:        1 Department of Mechanical-Electrical Engineering, North China Institute of Science and Technology, Beijing, 101601, China
                2 Department of Electronic and Information Engineering, North China Institute of Science and Technology, Beijing, 101601, China
        Source title:        Advanced Materials Research
        Abbreviated source title:        Adv. Mater. Res.
        Volume:        709
        Monograph title:        Advances in Applied Science, Engineering and Technology
        Issue date:        2013
        Publication year:        2013
        Pages:        575-578
        Language:        English
        ISSN:         10226680
        ISBN-13:         9783037857182
        Document type:        Conference article (CA)
        Conference name:        2013 International Conference on Applied Science, Engineering and Technology, ICASET 2013
        Conference date:        May 19, 2013 - May 21, 2013
        Conference location:        Qingdao, China
        Conference code:         97848
        Publisher:        Trans Tech Publications Ltd, Kreuzstrasse 10, Zurich-Durnten, CH-8635, Switzerland
        Abstract:        A fast feature extraction algorithm is presented in this paper based on the color and point feature, With the aim of required feature points, the location of the object includes object region detection and feature point location. The area of object detection is used to look for the centre of gravity point from the scaling image. The feature point location is based on the object region detection, cuts a picture from the image, and extracts speeded up robust feature (SURF) points of the target within the cut picture. The target position is calculated according to the value of the feature points, it provides a basis for object tracking. The experimental results verify the effectiveness of the proposed method. © (2013) Trans Tech Publications, Switzerland.
        Number of references:        5
        Main heading:         Algorithms
        Controlled terms:         Tracking (position)
        Uncontrolled terms:         Centre of gravity  -  Color features  -  Feature extracting  -  Feature extraction algorithms  -  Monocular vision  -  Object Tracking  -  Real-time features  -  Speeded up robust features
        Classification code:         716.2 Radar Systems and Equipment -  723 Computer Software, Data Handling and Applications -  921 Mathematics
        DOI:        10.4028/www.scientific.net/AMR.709.575
        Database:        Compendex
                Compilation and indexing terms, © 2013 Elsevier Inc.
2楼2013-10-31 08:13:00
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fallsoft

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水中青蛙: 金币+5, ★★★★★最佳答案, 非常感谢! 2013-10-31 09:05:25
Improved BP neural network in diagnosis of nonlinear fault
暂时没有检索
3楼2013-10-31 08:14:07
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水中青蛙

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引用回帖:
3楼: Originally posted by fallsoft at 2013-10-31 08:14:07
Improved BP neural network in diagnosis of nonlinear fault
暂时没有检索

Accession number:        
20132916521223

====就是检索号吧~
4楼2013-10-31 09:34:55
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