| CPC G06V 10/62 (2022.01) [G06V 10/454 (2022.01); G06F 2218/02 (2023.01); G06F 2218/08 (2023.01)] | 20 Claims |

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1. A method, comprising:
determining a probability of a presence of a feature to be tracked in a physical signal in a time sequence of physical signals using an artificial neural network having a single weight set, the physical signal being an input to the artificial neural network and capable of having different resolutions;
executing the artificial neural network in a nominal mode of operation in response to the probability of the presence of the feature being less than a threshold, the physical signal in the nominal mode being a physical signal having a nominal resolution;
executing the artificial neural network in an accelerated process mode of operation in response to the probability of the presence of the feature being greater than the threshold, a processing rate of the physical signal is increased in the accelerated process mode in comparison to the nominal mode, the physical signal in the accelerated process mode being a physical signal having a reduced resolution lower than the nominal resolution; and
tracking the feature in the time sequence of physical signals based on output data generated by executing the artificial neural network in the accelerated process mode.
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