A Comparative Study of Different CNN Models in City Detection Using Landmark Images

dc.contributor.author	Junayed, Masum Shah
dc.contributor.author	Jeny, Afsana Ahsan
dc.contributor.author	Neehal, , Nafis
dc.contributor.author	Atik, Syeda Tanjila
dc.date.accessioned	2022-01-18T07:05:15Z
dc.date.available	2022-01-18T07:05:15Z
dc.date.issued	2020
dc.identifier.uri	http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6780
dc.description.abstract	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.	en_US
dc.language.iso	en_US	en_US
dc.publisher	Scopus	en_US
dc.subject	City detection	en_US
dc.subject	Landmark	en_US
dc.subject	Inception	en_US
dc.subject	ResNet50	en_US
dc.subject	MobileNet	en_US
dc.subject	CNN	en_US
dc.title	A Comparative Study of Different CNN Models in City Detection Using Landmark Images	en_US
dc.type	Article	en_US