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Applying Tensorflow with Convolutional Neural Networks to Train Data and Recognize National Flags

机译:将Tensorflow与卷积神经网络结合使用以训练数据并识别国旗

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In the recent years, machine learning and deep learning has been becoming hot research titles. In many human life's fields, AI takes big roles like auto driving a car, automatically working robots or vacuum cleaner using image recognition techniques. Tensorflow is a machine learning system with open source code was introduced and provided by Google on November 9, 2015. It has been being famously used in images recognition field. In our work, we recognize an image and classify it using tensorflow based on Convolutional Neural Networks (CNNs) and determine what it is. We train 5-layers CNNs by supervised learning from a database. After training process, trained data files are generated. In the next steps, we use this data to recognize input image and classify it. Finally, we test the results by a testing program.
机译:近年来,机器学习和深度学习已成为热门的研究标题。在许多人类生活领域中,人工智能扮演着重要角色,例如使用图像识别技术自动驾驶汽车,自动工作的机器人或吸尘器。 Tensorflow是一种带有开放源代码的机器学习系统,由Google于2015年11月9日推出并提供。它已在图像识别领域中广为使用。在我们的工作中,我们识别图像并使用基于卷积神经网络(CNN)的张量流对其进行分类,然后确定图像的含义。我们通过有监督的数据库学习来训练5层CNN。在训练过程之后,将生成训练后的数据文件。在接下来的步骤中,我们将使用此数据来识别输入图像并将其分类。最后,我们通过测试程序来测试结果。

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