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Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2018; 27th International C Věra K?rková,Yannis Manolopoulos,Ilias Maglogianni Confe

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發(fā)表于 2025-3-30 08:12:47 | 只看該作者
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Artificial Neural Networks and Machine Learning – ICANN 201827th International C
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0302-9743 mation and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and 978-3-030-01420-9978-3-030-01421-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
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發(fā)表于 2025-3-31 19:41:01 | 只看該作者
Rank-Revealing Orthogonal Decomposition in Extreme Learning Machine Designining input domain into the output space of hidden neurons) which provides the basis for linear mean square (LMS) regression problem. The conditioning of this problem is the important factor influencing ELM implementation and accuracy. It is demonstrated that rank-revealing orthogonal decomposition
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An Improved CAD Framework for Digital Mammogram Classification Using Compound Local Binary Pattern ar is identified at its early stage. A Computer-aided diagnosis (CAD) system is an efficient computerized tool used to analyze the mammograms for finding cancer in the breast and to reach a decision with maximum accuracy. The presented work aims at developing a CAD model which can classify the mammog
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