COMPREHENSION METHOD OF NEURAL NETWORK FOR UNRECOGNIZABLE OBJECTS

原文（中国語）

A comprehension method of neural network for unrecognizable objects comprises: determining at least one type of at least one object in an under-test information by an object recognition model to output a quantity value of recognizable objects, generating a total quantity value of objects by segmenting the at least one object in the under-test information, and comparing whether the quantity value of the recognizable objects is equal to the total quantity value of the objects. When the quantity value of recognizable objects is less than the total quantity value of objects, it means the under-test information contains unknown objects that are not recognized by the object recognition model. The processing unit trains the object recognition model that at least one unrecognizable object is included in the under-test information. The present invention provides a neural network mechanism for comprehending unknown objects similar to humans.