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Classification of Graphical User Interfaces Through Gaze-Based Features Read chapter Read first chapter

2019 | OriginalPaper | Chapter

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

Authors : Masum Shah Junayed, Afsana Ahsan Jeny, Nafis Neehal, Syeda Tanjila Atik, Syed Akhter Hossain

Published in: Recent Trends in Image Processing and Pattern Recognition

Publisher: Springer Singapore

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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.

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previous chapter Comparative Study and Analysis of Dimensionality Reduction Techniques for Hyperspectral Data
next chapter Comparison of Deep Learning, Data Augmentation and Bag of-Visual-Words for Classification of Imbalanced Image Datasets
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Metadata
Title
A Comparative Study of Different CNN Models in City Detection Using Landmark Images
Authors
Masum Shah Junayed
Afsana Ahsan Jeny
Nafis Neehal
Syeda Tanjila Atik
Syed Akhter Hossain
Copyright Year
2019
Publisher
Springer Singapore
Book
Recent Trends in Image Processing and Pattern Recognition

Print ISBN: 978-981-13-9180-4

Electronic ISBN: 978-981-13-9181-1

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-981-13-9181-1_48

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