Using a neural network to produce a digital map for a location

A non-transitory computer-readable medium for producing a digital map for a location, the non-transitory computer-readable medium including instructions that when executed by one or more processors cause the one or more processors to:

• receive information that identifies a first location and a second location;
• store a first file and a second file, wherein:
• the first file is for the first location,
• the second file is for the second location,
• the first file includes a set of image data and a set of node data,
• the second file includes another set of image data and another set of node data,
• the set of node data includes information that identifies nodes in a neural network, information that identifies inputs of the nodes, and values of weights to be applied to the inputs, and
• the another set of node data includes the information that identifies the nodes in the neural network, the information that identifies the inputs of the nodes, and other values of weights to be applied to the inputs, a value of a weight of a node, in the other set of node data for the second location, being different from a value of the weight of the node in the set of node data for the first location;
• and
• retrieve, in response to a receipt of the information that identifies the first location, the first file;
• apply, in response to a retrieval of the first file, the values of the weights to the inputs of the nodes;
• receive, in response to the retrieval of the first file, image data, of the set of image data, for the neural network;
• execute, in response to an application of the values of the weights and a receipt of the image data, of the set of image data, the neural network to produce the digital map for the first location;
• and
• transmit the digital map for the first location to an automotive navigation system.

A method for producing a digital map fora location, the method comprising:

• receiving, by a processor, information that identifies a first location and a second location;
• storing, by the processor, a first file and a second file, wherein:
• the first file is for the first location,
• the second file is for the second location,
• the first file includes a set of image data and a set of node data,
• the second file includes another set of image data and another set of node data,
• the set of node data includes information that identifies nodes in a neural network, information that identifies inputs of the nodes, and values of weights to be applied to the inputs, and
• the another set of node data includes the information that identifies the nodes in the neural network, the information that identifies the inputs of the nodes, and other values of weights to be applied to the inputs, a value of a weight of a node, in the other set of node data for the second location, being different from a value of the weight of the node in the set of node data for the first location;
• retrieving, by the processor and in response to a receipt of the information that identifies the first location, the first file;
• applying, by the processor and in response to a retrieval of the first file, the values of the weights to the inputs of the nodes;
• receiving, by the processor and in response to the retrieval of the first file, image data, of the set of image data for the neural network;
• executing, by the processor and in response to an application of the values of the weights and a receipt of the image data, of the set of image data the neural network to produce the digital map for the first location;
• and
• transmitting, by the processor, the digital map for the first location to an automotive navigation system.

A system, comprising:

• a processor;
• and
• a memory storing a module including instructions that cause the processor, in response to a retrieval of:
• a first file, to:
• apply first weight values to a neural network,
• receive first location image data into the neural network,
• produce a first location map, and
• communicate the first location map to an automotive navigation system;
• and
• a second file, to:
• apply second weight values to the neural network,
• receive second location image data into the neural network,
• produce a second location map;
• and
• communicate the second location map to the automotive navigation system.