Method for Generating Digital Image Pairs as Training Data for Neural Networks

A method for generating a digital image pair for training a neural network to correct noisy image components of noisy images includes determining an extent of object movements within an overlapping region of a stored first digital image and a stored second digital image of an environment of a mobile...

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Bibliographic Details
Main Author MARTIN MEINKE
Format Patent
LanguageChinese
English
Published 30.10.2020
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:A method for generating a digital image pair for training a neural network to correct noisy image components of noisy images includes determining an extent of object movements within an overlapping region of a stored first digital image and a stored second digital image of an environment of a mobile platform, and determining a respective acquired solid angle of the environment of the mobile platform of the first and second digital images. The method further includes generating the digital image pair from the first digital image and the second digital images, when the respective acquired solidangles of the environment of the first and the second digital image do not differ from one another by more than a defined difference, and the extent of the object movements within the overlapping region of the first and the second digital image is less than a defined value. 用于生成数字图像对作为神经网络的训练数据的方法。一种用于创建数字图像对来训练神经网络对受到噪声干扰的图像的受到噪声干扰的图像部分进行修正的方法，所述方法具有如下步骤：确定在移动平台的周围环境的所存储的第一数字图像和所存储的第二数字图像的重叠区域之内对象移动的程度；确定所述移动平台、第一和第二数字图像
Bibliography:Application Number: CN202010331756