Scopus Indexed Publications

Paper Details


Title
A Comparative Study of Different CNN Models in City Detection Using Landmark Images
Author
Masum Shah Junayed, Afsana Ahsan Jeny, Nafis Neehal, Syed Akhter Hossain, Syeda Tanjila Atik,
Email
ahsan15-5278@diu.edu.bd
Abstract

Navigation assistance using different local Landmarks is an emerging research field now-a-days. Landmark images taken from different camera angles are being vividly used alongside the GPS (Global Positioning System) data to determine the location of the user and help user with navigation. However, determining the location of the user by recognizing the landmarks from different images, without the help of GPS, can be a worthy research trend to explore. Hence, in this paper, we have conducted a comparative study of 3 different popular CNN models, namely - Inception V3, MobileNet and ResNet50, and they have achieved an overall accuracy of 99.7%, 99.5% and 99.7% respectively while determining cities using landmark images.

Keywords
City detection Landmark Inception ResNet50 MobileNet CNN
Journal or Conference Name
Communications in Computer and Information Science
Publication Year
2019
Indexing
scopus