基于单片机的自动太阳跟踪太阳能电池板

G. Ali, Aqeel Luaibi
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引用次数: 2

摘要

为了学习数据的层次表示,可以使用使用多个处理层的深度学习技术,并产生最先进的结果。深度学习为自然语言处理(NLP)中的分类设计了许多模型和方法。目前已有多种分类算法用于阿拉伯文文档分类,但存在两个问题:高维特征表示和分类准确率低。本文利用深度相关模型和方法对阿拉伯文文本进行了分类,并与各种模型进行了比较。同时也对深度学习在阿拉伯文文本分类中的现状和未来进行了充分的认识,并取得了令人鼓舞的成果。
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Microcontroller based Automatic Sun Tracking Solar Panel
To learn a hierarchal representation of data, deep learning techniques can be used that use multiple processing layers, and produce state of art results. Many models and methods are designed in deep learning for classification in natural language processing (NLP). Various classification algorithms have been used for Arabic documents classification, but they have two problems High dimensional feature representation and the low accuracy of the classification. In this work, an important experiment is made by using deep related models and methods for classifying Arabic text also compare our model with various models. Also to forward a full understand, present and future of deep learning in Arabic text classification and have obtained encouraging results.
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