Applications of Deep Learning: A Review

Abstract

Deep learning is a field of artificial intelligence that is based on the working of the human brain in data processing and pattern generation for decision-making purposes. This paper studies the applications of deep learning techniques in the prospect of different emerging areas. Deep learning based on artificial neural networks will be treated as a key tool for the functioning and modelling of future communication networks. The data-driven strategies, that enrich the traditional techniques based on mathematical paradigms, enable artificial neural networks to be integrated with future communication networks. This paper presents a detailed study of the applications of deep learning and also illustrates a case study where deep learning technique is applied to a dataset containing the biomechanical features of orthopaedic patients. The results show the accuracy levels in varying levels of inputs of hidden layer nodes.