Exploratory Architectures Analysis of Various Pre-trained Image Classification Models for Deep Learning
deep learning; image classification; neural network
The image classification is one of the significant applications in the area of Deep Learning (DL) with respective to various sectors. Different types of neural network architectures are available to perform the image classification and each of which produces the different accuracy. The dataset and the features used are influence the outcome of the model. The research community is working towards the generalized model at least to the domain specific. On this gesture the contemporary survey of various Deep Learning models is identified using knowledge information management methods to move further to provide optimal architecture and also to generalized Deep Learning model to classify images narrow down to the sector specific. The study systematically presents the different types of architecture, its variants, layers and parameters used for each version of Deep Learning model. Domain specific applications and limitations of the type of architecture are detailed. It helps the researchers to select appropriate Deep Learning architecture for specific sector. 2024 by the authors.
Journal of Advances in Information Technology, Vol-15, No. 1, pp. 66-78.
https://doi.org/10.12720/jait.15.1.66-78 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183348264&doi=10.12720%2fjait.15.1.66-78&partnerID=40&md5=835724298bb9f8c31d2fdd872094d8e3
Deepa S., Department of Computer Science, Christ University, Bangalore, India; Zeema J.L., Department of Computer Science, Christ University, Bangalore, India; Gokila S., Department of Computer Applications, Hindustan Institute of Technology and Science, Chennai, India