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[1]刘彪,黄蓉蓉,林和,等.基于卷积神经网络的盲文音乐识别研究[J].智能系统学报,2019,14(01):186-193.[doi:10.11992/tis.201805002]
 LIU Biao,HUANG Rongrong,LIN He,et al.Research on braille music recognition based on convolutional neural networks[J].CAAI Transactions on Intelligent Systems,2019,14(01):186-193.[doi:10.11992/tis.201805002]
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基于卷积神经网络的盲文音乐识别研究(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第14卷
期数:
2019年01期
页码:
186-193
栏目:
出版日期:
2019-01-05

文章信息/Info

Title:
Research on braille music recognition based on convolutional neural networks
作者:
刘彪12 黄蓉蓉1 林和1 苏伟1
1. 兰州大学 信息科学与工程学院, 甘肃 兰州 730000;
2. 解放军69230部队, 新疆 乌苏 833000
Author(s):
LIU Biao12 HUANG Rongrong1 LIN He1 SU Wei1
1. School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China;
2. No.69230 Troops of PLA, Wusu 833000, China
关键词:
机器学习盲文音乐识别卷积神经网络深度学习计算机视觉图像识别人工智能图像处理
Keywords:
machine learningbraille music recognitionconvolution neural networkdeep learningcomputer visionimage recognitionartificial intelligenceimage processing
分类号:
TP39
DOI:
10.11992/tis.201805002
摘要:
盲人音乐家在交流创作的音乐作品时面临着人工转换和效率较低的问题,信息科学与技术的迅速发展为解决此类问题提供了许多解决方案。虽然目前有许多盲文音乐作品的识别方案,但其存在识别效率低和兼容能力不足等缺点。为了避免传统方案在盲文音乐图片特征提取时过多依赖人工经验,通过研究提出并设计了基于卷积神经网络的识别模型。在对盲文音乐图片的样例数据进行预处理之后,通过多次反复迭代训练,模型就可学习到盲文音乐图片中音乐符号的特征。实验结果表明,该模型的识别有效性和较强的泛化能力为盲文音乐作品的识别提供了一种新的解决方案。
Abstract:
Blind musicians are confronted with the problems of manual conversion and low efficiency in the communication of musical works. The rapid development of information science and technology has provided many solutions to these problems. However, most of the recognition schemes for braille music works lack recognition efficiency and compatibility. In consideration of this deficiency, whereby traditional schemes rely heavily on artificial experience in braille music picture extraction, a convolution neural network-based recognition model has been developed. After preprocessing the sample data of braille music pictures through repeated iterative training, the recognition model was able learn the characteristics of music notation in braille music pictures. The experimental results showed the recognition effectiveness and strong generalization ability of the model, which provides a new idea for the recognition of braille music works.

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备注/Memo

备注/Memo:
收稿日期:2018-05-04。
基金项目:广西科技计划项目(桂科AA17204096,桂科AD16380076);兰州市人才创新创业科技项目(2014-RC-3).
作者简介:刘彪,男,1984年生,硕士研究生,主要研究方向为智能软件与机器学习;黄蓉蓉,女,1994年生,硕士研究生,主要研究方向为人工智能与机器学习;林和,男,1963年生,副教授,主要研究方向为人工智能与机器学习。发表学术论文100余篇。
通讯作者:林和.E-mail:linhe@lzu.edu.cn
更新日期/Last Update: 1900-01-01