A new method for general work piece recognition based on Neural Network

被引：0
|
作者：
He, Zeqiang [1 ]
Ma, Jiachen [1 ]
Li, Zonglin [1 ]
机构：
[1] Harbin Inst Technol, Harbin 150001, Peoples R China
来源：
PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC) | 2016年
关键词：
Invariant moments; BP neural network; Wavelet neural network; Ada-boost; image recognition; FEATURE-EXTRACTION; CLASSIFIER;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a new method for general work piece recognition based on Wavelet Neural Network is proposed. The composition of the experimental system is introduced and the operating principle is analyzed. The invariant moment is a highly concentrated image feature, which have the characteristics of invariant to translation and rotation. In the selection of the classifier, the Wavelet Neural Network is adopted in that this method has the great advantage of fast training speed and high recognition rate relative to BP Neural Network. Ada-boost is employed because no matter which kind of neural network is used, we can use it to improve the recognition accuracy of the neural network. This is a very wide range of network performance improvement method. The experimental results illustrate that the image recognition method based on "wavelet neural network + ada-boost" has better ability of classification.
引用
收藏
页码：3428 / 3433
页数：6
相关论文
共 50 条
  • [21] A Fault Recognition Method Based on Convolutional Neural Network
    Chen, Lei
    Shi, Jiaqi
    Zhang, Ting
    International Journal of Network Security, 2024, 26 (04) : 589 - 597
  • [22] Research on the Captcha Recognition Method Based On Neural Network
    Liu, Zhifeng
    Tang, Xiaohu
    Wei, Zhenhua
    2018 4TH INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND MATERIAL APPLICATION, 2019, 252
  • [23] Continuous neural decoding method based on general regression neural network
    Dai J.
    Liu X.
    Zhang S.
    Zhang H.
    Xu Q.
    Chen W.
    Zheng X.
    International Journal of Digital Content Technology and its Applications, 2010, 4 (08) : 216 - 221
  • [24] Enterprise Employee Work Behavior Recognition Method Based on Faster Region-Convolutional Neural Network
    Zhang, Lu
    INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY, 2025, 22 (02) : 291 - 302
  • [25] A New Method of Deep Synergetic Neural Network ForFace Recognition
    Wei, Yuanzhang
    Meng, Jicheng
    Shen, Zonghui
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION PROCESSING (ICIIP'16), 2016,
  • [26] Research of Images Recognition Method Based on RBF Neural Network
    Sun, Honghui
    Zhang, Qinghua
    Wang, Hongxia
    Li, Aijun
    2012 7TH INTERNATIONAL CONFERENCE ON SYSTEM OF SYSTEMS ENGINEERING (SOSE), 2012, : 24 - 26
  • [27] Study on Recognition Method of Ferrographic debris Based on Neural Network
    Cao, Yabin
    ADVANCED TECHNOLOGIES IN MANUFACTURING, ENGINEERING AND MATERIALS, PTS 1-3, 2013, 774-776 : 1508 - 1511
  • [28] Dynamic gesture recognition method based on convolutional neural network
    Xu, Xiaoyu
    Deng, Lizhen
    Meng, Qingmin
    2019 INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA), 2019, : 389 - 394
  • [29] Braking Intention Recognition Method Based on the Fuzzy Neural Network
    Tang, Jinhua
    Zuo, Yanyan
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022
  • [30] Robust speaker recognition method based on convolutional neural network
    Zeng C.
    Ma C.
    Wang Z.
    Kong X.
    Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition), 2020, 48 (06): : 39 - 44
12345