Ceramic Type Recognition Algorithm Based on Ontology Modeling and Transfer Learning

Abstract

Image classification is the key research in the field of computer vision. Based on real data, this paper adopts the method of image ontology modeling and image transfer learning. In this paper, the image knowledge is transferred to the experimental data, and the neural network is trained by knowledge verification. This paper proposes a ceramic type recognition algorithm based on ontology modeling and transfer learning(ICOT) for image classification. Experimental results show that the proposed algorithm is better than the traditional algorithm. This paper provides a general idea for similar problems.