A Comprehensive review of Transfer Learning on Deep Convolutional Neural Network Models
International Journal of Advanced Trends in Computer Science and Engineering · 2020
In deep learning the most significant break though in the field of image recognition, language processing was done by Convolutional Neural Network (CNN).The CNN is a powerful algorithm which is capable of using features extraction at multiple levels and this is done based on the distribution of data automatically.The rapid growth in Big Data and the high-performance architectures have made it possible for the growth of CNN.Transfer Learning is the method for performance improvement in the specific problem with the transferring of knowledge learned from other domains.Transfer learning have a wide range of applications and it is widely used in deep learning algorithms There is rapid growth in the use of transfer learning in the pre trained models in CNN.The transfer learning helps to improve the performance of the models and it helps in saving time by acting as an optimization technique.This survey attempts to provide a comprehensive review in understanding the mechanisms of transfer learning and the pretrained models in CNN.