Use of MATLAB neural networks toolbox in a character recognition problem

被引：6
|
作者：
Trebar, M [1 ]
机构：
[1] Univ Ljubljana, Fac Chem & Informat Sci, Dhaka 1000, Bangladesh
来源：
COMPUTER APPLICATIONS IN ENGINEERING EDUCATION | 2005年 / 13卷 / 01期
关键词：
character recognition; input-output mapping; data encoding; neural networks;
D O I：
10.1002/cae.20031
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
We present the use of the MATLAB Neural Network Toolbox (NN Toolbox) in simulations of neural networks. We suggest ways for undergraduate students to solve a character recognition problem with feed-forward neural networks. The software provides the user with a very simple way to define several neural network architectures with different parameters, The solution of the character recognition problem is described from the beginning: collecting the data, data encoding, defining the input-output mapping architecture to the training, and testing the neural networks with the NN Toolbox. (c) 2005 Wiley Periodicals, Inc.
引用
收藏
页码：66 / 71
页数：6
相关论文
共 50 条
  • [41] An approach to offline Arabic character recognition using neural networks
    1600, Emirates Telecommunications Corporation (ETISALAT); Etisalat College of Engineering (ECE); IEEE Circuits and Systems Society (CAS); Institute of Electrical and Electronics Engineers (IEEE); University of Sharjah (UOS) (Institute of Electrical and Electronics Engineers Inc., United States):
  • [42] Arabic Handwritten Character Recognition Based on Convolution Neural Networks
    Research Laboratory in Algebra, Numbers Theory and Intelligent Systems RLANTIS, Monastir University, Monastir, Tunisia
    不详
    不详
    94140, France
    Commun. Comput. Info. Sci., 2022, (286-293):
  • [43] Arabic Handwritten Character Recognition Based on Convolution Neural Networks
    Bouchriha, Lamia
    Zrigui, Ahmed
    Mansouri, Sadek
    Berchech, Salma
    Omrani, Syrine
    ADVANCES IN COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2022, 2022, 1653 : 286 - 293
  • [44] OPTICAL CHARACTER-RECOGNITION USING ARTIFICIAL NEURAL NETWORKS
    ALPAYDIN, E
    FIRST IEE INTERNATIONAL CONFERENCE ON ARTIFICIAL NEURAL NETWORKS, 1989, : 191 - 195
  • [45] Character recognition by best anisotropic local bases and neural networks
    Uzunov, V
    Gotchev, A
    Huttunen, H
    Egiazarian, K
    Astola, J
    IMAGE PROCESSING: ALGORITHMS AND SYSTEMS IV, 2005, 5672 : 151 - 160
  • [46] Character recognition and its announcing using artificial neural networks
    Rao, MVR
    JOURNAL OF THE INSTITUTION OF ELECTRONICS AND TELECOMMUNICATION ENGINEERS, 1995, 41 (5-6): : 321 - 323
  • [47] Novel design of neural networks for handwritten Chinese character recognition
    Yip, DHF
    Yu, WWH
    VISION GEOMETRY VII, 1998, 3454 : 324 - 329
  • [48] On-line character analysis and recognition with fuzzy neural networks
    Sánchez, EG
    Dimitriadis, YA
    Más, MRS
    García, PS
    Izquierdo, JMC
    Coronado, JL
    INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2001, 7 (03): : 163 - 175
  • [49] Optical Chinese character recognition using probabilistic neural networks
    Carnegie Mellon Univ, Pittsburgh, United States
    Pattern Recognit, 8 (1279-1292):
  • [50] FPGA Implementation of Izhikevich Spiking Neural Networks for Character Recognition
    Rice, Kenneth L.
    Bhuiyan, Mohammad A.
    Taha, Tarek M.
    Vutsinas, Christopher N.
    Smith, Melissa C.
    2009 INTERNATIONAL CONFERENCE ON RECONFIGURABLE COMPUTING AND FPGAS, 2009, : 451 - +
12345