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

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2018)

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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Correspondence to Afsana Ahsan Jeny .

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Junayed, M.S., Jeny, A.A., Neehal, N., Atik, S.T., Hossain, S.A. (2019). A Comparative Study of Different CNN Models in City Detection Using Landmark Images. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1035. Springer, Singapore. https://doi.org/10.1007/978-981-13-9181-1_48

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

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9180-4

  • Online ISBN: 978-981-13-9181-1

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