首页> 外国专利> METHOD FOR CONFIGURING AN IMAGE EVALUATION DEVICE AND ALSO IMAGE EVALUATION METHOD AND IMAGE EVALUATION DEVICE

METHOD FOR CONFIGURING AN IMAGE EVALUATION DEVICE AND ALSO IMAGE EVALUATION METHOD AND IMAGE EVALUATION DEVICE

机译:配置图像评估装置的方法以及图像评估方法和图像评估装置

摘要

The aim of the invention is to configure an image analysis device (BA). This is achieved in that a plurality of training images (TPIC) assigned to an object type (OT) and an object sub-type (OST) are fed into a first neural network module (CNN) in Order to detect image features. Furthermore, training output data sets (FEA) of the first neural network module (CNN) are fed into a second neural network module (MLP) in Order to detect object types using image features. According to the invention, the first and second neural network module (CNN, MLP) are trained together such that training output data sets (OOT) of the second neural network module (MLP) at least approximately reproduce the object types (OT) assigned to the training images (TPIC). Furthermore, for each object type (OT1, OT2):—training images (TPIC) assigned to the object type (OT1, OT2) are fed into the trained first neural network module (CNN),—the first neural network module training output data set (FEA1, FEA2) generated for the respective training image (TPIC) is assigned to the object sub-type (OST) of the respective training image (TPIC), and—by means of the aforementioned sub-type assignments, a sub-type detection module (BMLP1, BMLP2) is configured to detect object sub-types (OST) using image features for the image analysis device (BA).
机译:本发明的目的是配置图像分析装置(BA)。这是实现的,因为将分配给对象类型(OT)和对象子类型(OST)的多个训练图像(TPIC)被馈送到第一神经网络模块(CNN)中以便检测图像特征。此外,第一神经网络模块(CNN)的训练输出数据集(FEA)被馈送到第二神经网络模块(MLP)中,以便使用图像特征检测对象类型。根据本发明,第一和第二神经网络模块(CNN,MLP)一起培训,使得第二神经网络模块(MLP)的训练输出数据集(OOT)至少近似再现分配给的对象类型(OT)训练图像(TPIC)。此外,对于每个对象类型(OT1,OT2): - 分配给对象类型的训练图像(TPIC)(OT1,OT2)被馈送到训练的第一神经网络模块(CNN)中, - 第一神经网络模块训练输出数据为各个训练图像(TPIC)生成的设置(FEA1,FEA2)被分配给相应训练图像(TPIC)的对象子类型(OST),借助于上述子类型分配,一个子 - 类型检测模块(BMLP1,BMLP2)被配置为使用图像分析设备(BA)的图像特征来检测对象子类型(OST)。

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