Training method of, and inspection system based on, iterative deep learning system

A training method of an iterative deep learning system, comprising the steps of:

• a) providing at least one unlabeled image of an object;
• b) labeling the unlabeled image of the object to produce a labeled image of the object;
• c) storing the labeled image of the object into an image database if the deep learning system is being trained with a labeled version of the unlabeled image of the object for a first time;
• d) identifying the labeled image of the object in the image database and outputting an identification result through the deep learning system and training the deep learning system according to an error between output and expected output of the identification result;
• and
• e) providing another unlabeled image of the object to the trained deep learning system to identify said another unlabeled image of the object and produce an inspection result;
• wherein determining whether the inspection result has satisfied a qualification condition and terminating training if the inspection result has satisfied the qualification condition, or repeating the steps a) to e) if the inspection result has not satisfied the qualification condition.