AdaBoost-CNN: An adaptive boosting algorithm for convolutional neural networks to classify multi-class imbalanced datasets using transfer learning

Taherkhani Aboozar; Cosma Georgina; McGinnity T. M.

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AdaBoost-CNN: An adaptive boosting algorithm for convolutional neural networks to classify multi-class imbalanced datasets using transfer learning

机译：adaboost-cnn：卷积神经网络的自适应促进算法，用于使用传输学习对多级不平衡数据集进行分类

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来源
《Neurocomputing》 |2020年第3期|351-366|共16页
作者
Taherkhani Aboozar; Cosma Georgina; McGinnity T. M.;
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作者单位

De Montfort Univ Sch Comp Sci & Informat Leicester Leics England;

Loughborough Univ Sch Sci Dept Comp Sci Loughborough Leics England;

Nottingham Trent Univ Sch Sci & Technol Nottingham England|Ulster Univ Intelligent Syst Res Ctr Derry North Ireland;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
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AdaBoost-CNN: An adaptive boosting algorithm for convolutional neural networks to classify multi-class imbalanced datasets using transfer learning

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