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SceneRecog: A Deep Learning Scene Recognition Model for Assisting Blind and Visually Impaired Navigate using Smartphones

Kuriakose, Bineeth; Shrestha, Raju; Sandnes, Frode Eika
Conference object
Accepted version
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IEEE_SMC_SceneRecog__the_Original_Copy_submitted_.pdf (2.459Mb)
URI
https://hdl.handle.net/11250/2988634
Date
2022-01-06
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  • Publikasjoner fra Cristin [2594]
  • TKD - Institutt for informasjonsteknologi [860]
Original version
https://doi.org/10.1109/SMC52423.2021.9658913
Abstract
Deep learning models have recently gained popularity in the research community due to their high classification success rates. In this paper, we proposed an EfficientNet-Lite based scene recognition model for scene recognition as a part of the smartphone-based navigation support application for the blind and visually impaired. We created a custom dataset with both indoor and outdoor scenes for training and testing of the model. The main objective of this work is to support people with visual impairments navigate by providing information about the scene via a smartphone application. The results from the experiment show encouraging performance from the proposed model. As a proof of concept, a prototype app was developed on the Android platform. However, the model can be implemented and deployed in any modern smartphone with good processing power.
Publisher
Institute of Electrical and Electronics Engineers
Series
IEEE International Conference on Systems, Man and Cybernetics;2021 IEEE International Conference on Systems, Man, and Cybernetics

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