Exploring imbalanced class issue in handwritten dataset using convolutional neural networks and deep belief networks

• Main Authors: Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Abdullah, Ahmad Zarir
• 格式: Conference or Workshop Item
• 语言: English
• 出版: 2016
• 主题: QA75 Electronic computers. Computer science
• 在线阅读: http://irep.iium.edu.my/53436/9/53436.pdf; http://irep.iium.edu.my/53436/; http://www.ftsm.ukm.my/mcait2016/

Imbalanced class is one of the challenges in classifying big data. Data disparity produces a biased output of a model regardless how recent the technology is. However, deep learning algorithms such as convolutional neural networks and deep belief networks showed promising results in many domains, es...