文章基本信息

标题：Deep Learning for Image Processing in WEKA Environment
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作者：Zanariah Zainudin ; Siti Mariyam Shamsuddin ; Shafaatunnur Hasan 等
期刊名称：International Journal of Advances in Soft Computing and Its Applications
印刷版ISSN：2074-8523
出版年度：2019
卷号：11
期号：1
页码：1-21
出版社：International Center for Scientific Research and Studies
摘要：Deep learning is a new term that is recently popular amongresearchers when dealing with big data such as images, texts, voicesand other types of data. Deep learning has become a popularalgorithm for image processing since the last few years due to itsbetter performance in visualizing and classifying images.Nowadays, most of the image datasets are becoming larger in termsof size and variety of the images that can lead to misclassificationdue to human eyes. This problem can be handled by using deeplearning compared to other machine learning algorithms. Thereare many open sources of deep learning tools available andWaikato Environment for Knowledge Analysis (WEKA) is one ofthe sources which has deep learning package to conduct imageclassification, which is known as WEKA DeepLearning4j. In thispaper, we demonstrate the systematic methodology of using WEKADeepLearning4j for image classification on larger datasets. Wehope this paper could provide better guidance in exploring WEKAdeep learning for image classification.
关键词：Image Classification; WEKA DeepLearning4j; WEKA Image; Deep;Learning; Convolutional Neural Network.