Artificial intelligence-based hybrid deep learning models for image classification: The first narrative review.

Journal: Computers in biology and medicine
Published Date:

Abstract

BACKGROUND: Artificial intelligence (AI) has served humanity in many applications since its inception. Currently, it dominates the imaging field-in particular, image classification. The task of image classification became much easier with machine learning (ML) and subsequently got automated and more accurate by using deep learning (DL). By default, DL consists of a single architecture and is termed solo deep learning (SDL). When two or more DL architectures are fused, the result is termed a hybrid deep learning (HDL) model. The use of HDL models is becoming popular in several applications, but no review of these uses has been designed thus far. Therefore, this study provides the first narrative HDL review by considering all facets of image classification using AI.

Authors

  • Biswajit Jena
    Department of CSE, International Institute of Information Technology, Bhubaneswar, India.
  • Sanjay Saxena
    Department of CSE, International Institute of Information Technology, Bhubaneswar, India.
  • Gopal K Nayak
    Department of CSE, International Institute of Information Technology, Bhubaneswar, India.
  • Luca Saba
    Department of Radiology, A.O.U., Italy.
  • Neeraj Sharma
    School of Biomedical Engineering, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, India.
  • Jasjit S Suri
    Advanced Knowledge Engineering Center, Global Biomedical Technologies, Inc., Roseville, CA, USA. Electronic address: jsuri@comcast.net.