Quantum transfer learning for image classification

Quantum machine learning, an important element of quantum computing, recently has gained research attention around the world. In this paper, we have proposed a learning model to classify images using classifier. We exhibit results comprehensive classifier with transfer applied image datasets in particular. The work uses hybrid technique along classical pre-trained network and variational circuits as their final layers on small scale dataset. implementation is carried out processor chosen set highly informative functions PennyLane cross-platform software package for computers evaluate high-resolution performance proved be more accurate than its counterpart outperforms all other existing models terms time competence.