首页> 外国专利> DEEP LEARNING SYSTEM AND LEARNING METHOD USING OF CONVOLUTIONAL NEURAL NETWORK BASED IMAGE PATTERNING

DEEP LEARNING SYSTEM AND LEARNING METHOD USING OF CONVOLUTIONAL NEURAL NETWORK BASED IMAGE PATTERNING

机译:基于卷积神经网络的图像学习深度学习系统及学习方法

摘要

The present invention relates to a deep learning system using image patterning based on a convolutional neural network and an image learning method using the same, which includes an image input unit for inputting an input image; A patterning module for generating an input image received from the image input unit as a plurality of patterned pattern images; A CNN learning unit based on a convolution neural network (CNN) that learns an input image received from an image input unit and a pattern image received from a patterning module; A CNN execution unit for receiving learning information from the CNN learning unit and an input image received from the image input unit; And a final classifier for receiving image information from the CNN executing unit and classifying objects of the image information according to types.The present invention provides an image learning apparatus capable of enhancing the quality of image learning information that is vulnerable to various environmental problems (shaking, illuminance, noise, degradation of recognition rate, etc.) and a deep learning system using the same.
机译:本发明涉及使用基于卷积神经网络的图像图案化的深度学习系统和使用该深度学习系统的图像学习方法,其包括用于输入输入图像的图像输入单元;图案化模块,用于将从图像输入单元接收的输入图像生成为多个图案化的图案图像;基于卷积神经网络(CNN)的CNN学习单元,其学习从图像输入单元接收的输入图像和从构图模块接收的图案图像; CNN执行单元,用于从CNN学习单元接收学习信息以及从图像输入单元接收的输入图像;以及最终分类器,其用于从CNN执行单元接收图像信息并根据类型对图像信息的对象进行分类。本发明提供一种图像学习设备,其能够提高易受各种环境问题(抖动)影响的图像学习信息的质量。 ,照度,噪声,识别率下降等)以及使用该方法的深度学习系统。

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