Using defect detection tools, engineers train the software in supervised mode with a collection of images labeled according to whether ceramic capacitors or electrolytic capacitors belong to the category "pass." During operation, the model captures and differentiates both kinds as belonging to the same type. Subsequently, the classification tool learns each unique capacitor property and accommodates intratype variation. Even if they look similar visually, color and label differences distinguish varying electrolytic capacitors effectively. Meanwhile, Cognex Deep Learning accurately classifies and distinguishes individual capacitors within singular images throughout runtime based on patterns learned during development.