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Titlebook: Intelligent Computing in Signal Processing and Pattern Recognition; International Confer De-Shuang Huang,Kang Li,George William Irwin Book

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发表于 2025-3-21 18:24:26 | 显示全部楼层 |阅读模式
书目名称Intelligent Computing in Signal Processing and Pattern Recognition
副标题International Confer
编辑De-Shuang Huang,Kang Li,George William Irwin
视频video
概述Presents the results of the International Conference on Intelligent Computing, ICIC 2006.Includes the topical section on Intelligent Computing in Signal Processing and Pattern Recognition.Includes a s
丛书名称Lecture Notes in Control and Information Sciences
图书封面Titlebook: Intelligent Computing in Signal Processing and Pattern Recognition; International Confer De-Shuang Huang,Kang Li,George William Irwin Book
描述." Intelligent Computing in Signal Processing and Pattern Recognition " constitutes the results of the International Conference on Intelligent Computing, ICIC 2006, held in Kunming, China, in August 2006. The carefully reviewed contributions are included in five volumes of edited books, including one volume of Lecture Notes in Computer Science (LNCS), one volume of Lecture Notes in Artificial Intelligence (LNAI), one volume of Lecture Notes in Bioinformatics (LNBI), and two volumes of Lecture Notes in Control and Information Sciences (LNCIS). The 149 revised full papers of this volume were reviewed and selected from over 3000 submissions, covering the field of Intelligent Computing in Signal Processing and Pattern Recognition, as well as a Special Session on Computing for Searching Strategies to Control Dynamic Processes..
出版日期Book 2006
关键词Computing for Searching Strategies to Control Dynamic Proces; Control Dynamic Processes; Intelligent C
版次1
doihttps://doi.org/10.1007/978-3-540-37258-5
isbn_softcover978-3-540-37257-8
isbn_ebook978-3-540-37258-5Series ISSN 0170-8643 Series E-ISSN 1610-7411
issn_series 0170-8643
copyrightSpringer-Verlag Berlin Heidelberg 2006
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A Novel Color Image Watermarking Method Based on Genetic Algorithmest enhances security and robustness of the watermarked image. The experimental results show that our method is more flexible than traditional methods and successfully fulfills the compromise between robustness and image quality.
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A Novel Emitter Signal Recognition Model Based on Rough Sethrough simulation. Experiments results demonstrate the excellent performance of this new recognition method as compared to existing two pattern recognition techniques. A brand-new method is provided for researching on emitter recognition.
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A Novel Model for Independent Radial Basis Function Neural Networks with Multiresolution Analysis recognition. According to experiments on FERET face database, our proposed approach could outperform newly proposed ICA algorithm. And it is also confirmed that our proposed approach is more robust to facial expression, illumination and aging than ICA in face recognition.
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