| CPC G06V 40/28 (2022.01) [G06F 3/017 (2013.01); G06F 18/217 (2023.01); G06F 18/22 (2023.01); G06V 10/454 (2022.01); G06V 30/194 (2022.01); G06V 40/113 (2022.01)] | 21 Claims |

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1. A method of determining a hand pose using neural network systems, the method including:
receiving a first set of estimates of hand position parameters from one or more generalist neural networks and/or specialist neural networks for at least one hand joint of a plurality of hand joints;
for the at least one hand joint of the plurality of hand joints, determining a principal distribution of the first set of estimates;
receiving a second set of estimates of hand position parameters from the one or more generalist neural networks and/or specialist neural networks for the at least one hand joint of the plurality of hand joints; and
for the at least one hand joint of the plurality of hand joints:
calculating a similarity measure between the second set of estimates and the principal distribution of the first set of estimates;
identifying select estimates in the second set of estimates based on the similarity measure;
calculating contribution weights of the select estimates based on the similarity measure; and
determining a principal distribution of the second set of estimates based on the contribution weights of the select estimates.
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