Method for the classification of parking spaces in a surrounding region of a vehicle with a neural network

A non-transitory machine-readable medium comprising a plurality of machine-readable instructions executed by one or more processors, the plurality of machine-readable instructions causing the one or more processors to perform operations for a classification of parking spaces in a surrounding region of a vehicle with a driver support system, wherein the vehicle comprises at least one first surroundings sensor and one second surroundings sensor, the operations comprising:

• receiving first sensor data out of the surrounding region by the driver support system from the at least one first surroundings sensor;
• recognizing a parking-space-like partial region of the surrounding region in the first sensor data;
• requesting second sensor data acquired by the at least one second surroundings sensor out of the parking-space-like partial region by the driver support system as soon as the parking-space-like partial region is recognized in the first sensor data;
• transmitting the requested second sensor data to a vehicle-side computing unit comprising a deep neural network (DNN);
• and
• classifying the parking-space-like partial region into categories with the DNN, wherein the categories comprise legal, parkable parking spaces and illegal, non-parkable parking spaces,
• wherein the deep neural network (DNN) is pre-trained for the classification of parking spaces, while the pre-training of the deep neural network (DNN) is done through vehicle-side recording of second sensor data comprising image data.