Deep Belief Networks Using Convolution Neural Networks Algorithm

Abstract

The concept of deep learning is not new to higher educatio n. However, deep learning has drawn more attention in recent years as institutions attempt to tap their student’s full learning potential. To more fully develop student talents, many campuses are shifting from a traditional passive, instructor- dominated pedagogy to active, learner-centered activities. Switching these features of human brain to a learning model, we wish the model can deal with the high-dimensional data, support a fast and intellectual learning algorithm and perform well in the complicated AI tasks like computer vision or speech recognition. This survey reviews a history of deep learning, summarizing the components of Convolutional Neural Networks (CNNs) and Deep Belief Networks (DBNs) together with their learning algorithms and their performances in different applications. Institutions and researchers can use the resulting scales to assess and investigate deep approaches to learning.