Title:   Review Of Deep Learning: Concepts, Approaches, Applications & Future Directions

Authors: Mr. Dinesh D.V, Assistant Professor Government First Grade College R.T. Nagar, Bengaluru

Abstract: In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. Moreover, it has gradually become the most widely used computational approach in the field of ML, thus achieving outstanding results on several complex cognitive tasks, matching or even beating those provided by human performance. One of the benefits of DL is the ability to learn massive amounts of data. The DL field has grown fast in the last few years and it has been extensively used to successfully address a wide range of traditional applications. More importantly, DL has outperformed well‑known ML techniques in many domains, e.g., cybersecurity, natural language processing, bioinformatics, robotics and control, and medical information processing, among many others. Finally, we further present the challenges and suggested solutions to help researchers understand the existing research gaps. It is followed by a list of the major DL applications. Computational tools including FPGA, GPU, and CPU are summarized along with a description of their influence on DL. The paper ends with the evolution matrix, benchmark datasets, and summary conclusion.

Keywords:  Deep learning applications, Image classification, Transfer learning, Medical image analysis, Supervised learning

DOI: 10.5281/zenodo.8118695

International Journal of Applied Pattern Recognition, 2023 Vol.7 No.1, pp.87 - 92

Received: 12 Jan 2022
Accepted: 18 June 2022
Published online: 6 Oct 2022