CPC G06F 30/17 (2020.01) [G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06F 2119/18 (2020.01)] | 20 Claims |
1. A method comprising:
inputting a geometry of a substrate surface and manufacturing process parameters to a neural network, the neural network comprising a combination of a linear layer, non-linear activation functions, and a convolution layer, the neural network trained using one or more training sets, each training set comprising a different type of substrate geometry, and a collection of the manufacturing process parameters, the substrate surface configured to receive at least one droplet;
determining a shape of the at least one droplet after it has been deposited on the substrate surface based on an output of the neural network; and
producing a simulation output representing the determined shape of the at least one droplet.
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