Method for acquiring neural network training set and system thereof

The invention provides a method for acquiring a neural network training set and a system thereof. The method comprises the steps of: S100, acquiring category information of an image set to be filtered; S200, filtering a target image, and obtaining a target image data set corresponding to the image s...

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Bibliographic Details
Main Author LUO PEIYUAN
Format Patent
LanguageChinese
English
Published 28.09.2018
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
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Summary:The invention provides a method for acquiring a neural network training set and a system thereof. The method comprises the steps of: S100, acquiring category information of an image set to be filtered; S200, filtering a target image, and obtaining a target image data set corresponding to the image set to be filtered, wherein the similarity of the target image and the sample image reaches the imagedata of a preset similarity threshold, and the sample image is a template image corresponding to the category information of the image set to be filtered; and S300, performing a confrontation training on the target image data to obtain a sample data set. The invention is capable of reducing manual screening of sample data sets, improving screening efficiency and screening reliability, and improving the accuracy of the neural network. 本发明提供了种神经网络训练集的获取方法及其系统，其方法包括：S100获取待筛选图像集的类别信息；S200筛选目标图像，获得所述待筛选图像集对应的目标图像数据集；所述目标图像为与样本图像之间相似度达到预设相似度阈值的图像数据；所述样本图像为待筛选图像集的类别信息对应的模板图像；S300对所述目标图像数据进行对抗训练获得样本数据集。本发明实现减少人工筛选样本数据集，提升筛选
Bibliography:Application Number: CN201810438759