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

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).