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首页> 外文期刊>International Journal of Advances in Soft Computing and Its Applications >Deep Learning for Image Processing in WEKA Environment
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Deep Learning for Image Processing in WEKA Environment

机译:WEKA环境中用于图像处理的深度学习

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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.
机译:深度学习是一个新术语,最近在研究大数据(例如图像,文本,语音和其他类型的数据)时,在研究人员中很流行。深度学习由于其在图像的可视化和分类方面的出色表现,自最近几年以来已成为一种流行的图像处理算法。如今,大多数图像数据集在图像的大小和种类方面都变得越来越大,可能导致人眼误分类。 。与其他机器学习算法相比,可以通过使用深度学习来解决此问题。深度学习工具有很多开放源,而“ Waikato知识分析环境”(WEKA)是具有进行图像分类的深度学习包的资源之一,被称为WEKA DeepLearning4j。在本文中,我们演示了使用WEKADeepLearning4j对较大数据集进行图像分类的系统方法。希望本文可以为探索WEKA深度学习进行图像分类提供更好的指导。

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