Handwritten Character Recognition Based on BP Neural Network

被引：6
|
作者：
Wang, Xin [1 ]
Huang, Ting-lei [1 ]
Liu, Xiao-yu [1 ]
机构：
[1] Guilin Univ Elect Technol, Sch Comp & Control, Guilin, Peoples R China
来源：
THIRD INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING | 2009年
关键词：
handwritten character recognition; Genetic Algorithm; BP neuralnetwork;
D O I：
10.1109/WGEC.2009.206
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper researches on the issue of computer recognition to the handwritten character images, including lowercase letters and Arabic numerals. In this paper, we preprocess on characters in order to unified the basic features. And then, we apply the basic method of making the grids to extract the features of chacrater, and classify the respectives. At last, we apply the latest heuristic modifications of Backpropagation algorithm to recognize the handwritten characters successfully. The basic datas of this research are testing and debugging on visual studio 2005, a large number of test experiments' datas show that the discrimination of heuristic modifications of Backpropagation algorithm is up to 95 percentage, further improving validity and correctness of this latest algorithm.
引用
收藏
页码：520 / 524
页数：5
相关论文
共 50 条
  • [41] Alphanumeric Character Recognition Based on BP Neural Network Classification and Combined Features
    Luo, Yong
    Chen, Shuwei
    He, Xiaojuan
    Jia, Xue
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2013, 6 (06) : 1108 - 1115
  • [42] Printed New Tai Lue Character Recognition Based on BP Neural Network
    Li, Dengfeng
    Yu, PengFei
    Li, Haiyan
    Peng, Ge
    2016 IEEE INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (ICSIP), 2016, : 339 - 342
  • [43] Extended Fuzzy Hyperline Segment Neural Network for Handwritten Character Recognition
    Pawar, Dipti
    INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, IMECS 2012, VOL I, 2012, : 43 - 46
  • [44] Handwritten Character Recognition by Alternately Trained Relaxation Convolutional Neural Network
    Wu, Chunpeng
    Fan, Wei
    He, Yuan
    Sun, Jun
    Naoi, Satoshi
    2014 14TH INTERNATIONAL CONFERENCE ON FRONTIERS IN HANDWRITING RECOGNITION (ICFHR), 2014, : 291 - 296
  • [45] Bengali Handwritten Character Recognition Using Deep Convolutional Neural Network
    Purkaystha, Bishwajit
    Datta, Tapos
    Islam, Md Saiful
    2017 20TH INTERNATIONAL CONFERENCE OF COMPUTER AND INFORMATION TECHNOLOGY (ICCIT), 2017,
  • [46] Handwritten Character Recognition Using Multiscale Neural Network Training Technique
    Ganapathy, Velappa
    Liew, Kok Leong
    PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 29, 2008, 29 : 32 - 37
  • [47] Optical Character Recognition of Arabic Handwritten Characters using Neural Network
    Hussien, Rana S.
    Elkhidir, Azza A.
    Elnourani, Mohamed G.
    2015 INTERNATIONAL CONFERENCE ON COMPUTING, CONTROL, NETWORKING, ELECTRONICS AND EMBEDDED SYSTEMS ENGINEERING (ICCNEEE), 2015, : 456 - 461
  • [48] Handwritten optical character recognition by hybrid neural network training algorithm
    Sampath, A. K.
    Gomathi, N.
    IMAGING SCIENCE JOURNAL, 2019, 67 (07): : 359 - 373
  • [49] Hindi Handwritten Character Recognition using Deep Convolution Neural Network
    Chaudhary, Deepak
    Sharma, Kaushal
    PROCEEDINGS OF THE 2019 6TH INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM), 2019, : 961 - 965
  • [50] Deep Convolutional Neural Network Classifier for Handwritten Devanagari Character Recognition
    Singh, Pratibha
    Verma, Ajay
    Chaudhari, Narendra S.
    INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 2, INDIA 2016, 2016, 434 : 551 - 561
12345