Method, artificial neural network, device, computer program and machine-readable memory medium for the semantic segmentation of image data

A network for semantically segmenting image data of an imaging sensor, comprising:

• an artificial neural network, including an encoder path, a decoder path, the encoder path transitioning into the decoder path, the transition taking place via a discriminative path, configured to perform the following in the discriminative path:
• dividing an input tensor as a function of a division function into at least one first slice tensor and at least one second slice tensor, the input tensor originating from the encoder path;
• connecting the at least one first slice tensor to the at least one second slice tensor as a function of a first connection function to obtain at least one concatenated tensor;
• connecting the at least one first slice tensor to a class tensor as a function of a second connection function to obtain a decoder tensor, the class tensor being of the at least one concatenated tensor;
• and
• outputting the decoder tensor to the decoder path of the neural network.

A device for semantically segmenting image data of an imaging sensor, comprising:

• an artificial neural network, including an encoder path, a decoder path, the encoder path transitioning into the decoder path, the transition taking place via a discriminative path, configured to perform the following in the discriminative path:
• dividing an input tensor as a function of a division function into at least one first slice tensor and at least one second slice tensor, the input tensor originating from the encoder path;
• connecting the at least one first slice tensor to the at least one second slice tensor as a function of a first connection function to obtain at least one concatenated tensor;
• connecting the at least one first slice tensor to a class tensor as a function of a second connection function to obtain a decoder tensor, the class tensor being of the at least one concatenated tensor;
• and
• outputting the decoder tensor to the decoder path of the neural network.

A non-transitory computer readable medium having a computer program, which is executable by a processor, comprising:

• a program code arrangement having program code for providing calculation resource-saving semantic segmentation of image data of an imaging sensor with an artificial neural network, by performing the following in a discriminative path of the artificial neural network, which includes an encoder path, a decoder path, the encoder path transitioning into the decoder path, the transition taking place via the discriminative path:
• dividing an input tensor as a function of a division function into at least one first slice tensor and at least one second slice tensor, the input tensor originating from the encoder path;
• connecting the at least one first slice tensor to the at least one second slice tensor as a function of a first connection function to obtain at least one concatenated tensor;
• connecting the at least one first slice tensor to a class tensor as a function of a second connection function to obtain a decoder tensor, the class tensor being of the at least one concatenated tensor;
• and
• outputting the decoder tensor to the decoder path of the neural network.