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
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
  • [31] Expression Recognition Method Based on a Lightweight Convolutional Neural Network
    Zhao, Guangzhe
    Yang, Hanting
    Yu, Min
    IEEE ACCESS, 2020, 8 : 38528 - 38537
  • [32] Composite taste recognition method based on fuzzy neural network
    Zhang, Yu
    Qi, Mei-Xing
    Tong, Min-Ming
    Journal of Networks, 2013, 8 (09) : 2021 - 2028
  • [33] Recognition Method of Pig Cough Based on Deep Neural Network
    Shen M.
    Wang M.
    Liu L.
    Chen J.
    Tai M.
    Zhang W.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2022, 53 (05): : 257 - 266
  • [34] Coal Structure Recognition Method Based on LSTM Neural Network
    Chen, Yang
    Chen, Cen
    Zhang, Jiarui
    Hu, Fengying
    He, Taohua
    Wang, Xinyue
    Cheng, Qun
    He, Jiayi
    Zhao, Ya
    Zeng, Qianghao
    PROCESSES, 2024, 12 (12)
  • [35] Method on Human Activity Recognition Based on Convolutional Neural Network
    Haibin, Zhang
    Kubota, Naoyuki
    INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2019, PT III, 2019, 11742 : 63 - 71
  • [36] Automatic Phase Recognition Method Based on Convolutional Neural Network
    Ji Ying
    Gong Lingran
    Fu Shuang
    Wang Yawei
    LASER & OPTOELECTRONICS PROGRESS, 2022, 59 (06)
  • [37] A Recognition Method of Surface -Water Based on RBF Neural Network
    Chen Xue-lian
    Hu Jing-tao
    2013 IEEE 4TH INTERNATIONAL CONFERENCE ON ELECTRONICS INFORMATION AND EMERGENCY COMMUNICATION (ICEIEC), 2014, : 217 - 221
  • [38] A Recognition Method of Misjudgment Gesture Based on Convolutional Neural Network
    Sun, Kaiyun
    Feng, Zhiquan
    Ai, Changsheng
    Li, Yingjun
    Wei, Jun
    Yang, Xiaohui
    Guo, Xiaopei
    2017 INTERNATIONAL CONFERENCE ON VIRTUAL REALITY AND VISUALIZATION (ICVRV 2017), 2017, : 272 - 273
  • [39] Chromatographic peak recognition method based on convolutional neural network
    Zhao, Weidong
    Xue, Qingjun
    Liu, Hao
    PROCEEDINGS OF 2021 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INFORMATION SYSTEMS (ICAIIS '21), 2021,
  • [40] An Infant Cry Recognition based on Convolutional Neural Network Method
    Teeravajanadet, K.
    Siwilai, N.
    Thanaselanggul, K.
    Ponsiricharoenphan, N.
    Tungjitkusolmun, S.
    Phasukkit, P.
    2019 12TH BIOMEDICAL ENGINEERING INTERNATIONAL CONFERENCE (BMEICON 2019), 2019,