Asynchronous Neural Network Systems

A device, comprising:

• a processor configured to execute a neural network, the neural network being configured to process a series of images, and further comprising:
• a first multi-step processing pathway;
• and
• a second multi-step processing pathway wherein a plurality of steps within the second multi-step processing pathway comprises at least:
• an input from a previous step within the second multi-step processing pathway;
• an input from the first multi-step processing pathway;
• and
• an output configured to generate inferences;
• and
• an inference frequency controller configured to modulate the neural network processing in at least one step within the first multi-step processing pathway.

A method, comprising:

• configuring a neural network to receive a series of images to generate prediction data;
• establishing a multi-step convolution pathway within the neural network;
• establishing a multi-step upsampling pathway within the neural network wherein a plurality of upsampling steps comprise an input to receive output data from a corresponding convolution pathway step;
• wherein, in response to receiving image for processing, feature map output data is generated at a plurality of steps within the convolution pathway, and at least one step of the upsampling pathway utilizes at least the received feature map data to generate prediction data;
• configuring an inference frequency controller to provide an output signal to the neural network;
• and
• configuring the neural network to, in response to receiving the output signal from the inference frequency controller, generate feature map data at fewer than every step within the multi-step convolution pathway and previously processed feature map data is utilized as input data within the multi-step upsampling pathway until a subsequent feature map input is received.

A method comprising:

• configuring an inference frequency controller to receive input data from a plurality of inputs;
• processing the received input data;
• determining a processing frequency for a neural network configured to process time-series data;
• and
• transmitting a signal associated with the determined frequency to the neural network;
• wherein the signal is configured to change the frequency of processing time-series data within the neural network.