Implementation of deep neural networks for testing and quality control in the production of memory devices

A method, comprising:

• preparing multiple instances of a circuit element mounted onto one or more circuit boards;
• generating photographic images of the prepared multiple instances of a circuit element mounted onto one or more circuit boards;
• generating artificial images of multiple instances of the circuit element mounted onto one or more circuit boards;
• training a neural network on a combination of the photographic images and the artificial images of multiple instances of a circuit element mounted onto one or more circuit boards;
• applying the trained neural network to one or more additional instances of the circuit element mounted to a circuit board;
• analyzing results of the application of the trained neural network to the one or more additional instances of the circuit element mounted to a circuit board;
• and
• determining whether one or more of the additional instances of the circuit element are defectively mounted to the circuit board.