A Brief Overview of Developing Convolutional Neural Network Using Genetic Algorithm - Lone, Mudasir Ali; Islam, Mohammad (International Journal of Computer Sciences and Engineering, 2019)
This paper presents an overview of developing Convolutional Neural Network using Genetic Algorithm. CNNs have been quite popular for image recognition and classification problems, but developing and training a CNN is a timeconsuming and computationally costly and complex process. In this paper we discuss and review various GA based methods used for automatically generating and developing CNN networks and optimizing their networks for various pattern recognition problems and various tasks on image datasets. This paper looks at how using genetic approach for developing a network reduces its computational complexity compared to the traditional methods and increases the efficiency and accuracy of the network while also making the training process easier. We look at the genetic encoding used to generate a network and perform its evolution. A general survey of developing CNNs using GA is presented in order to understand the improvement in performance achieved through the given method. We look at the relative performance of CNNs developed through genetic approach and make a general comparison with the ones produced manually.