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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Mai Mariam Mohamed Aminuddin
universiti teknikal malaysia melaka
Computer Science & IT Engineering

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Android based application for visually impaired using deep learning approach Haslinah Mohd Nasir; Noor Mohd Ariff Brahin; Mai Mariam Mohamed Aminuddin; Mohd Syafiq Mispan; Mohd Faizal Zulkifli
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i4.pp879-888

Abstract

People with visually impaired had difficulties in doing activities related to environment, social and technology. Furthermore, they are having issues with independent and safe in their daily routine. This research propose deep learning based visual object recognition model to help the visually impaired people in their daily basis using the android application platform. This research is mainly focused on the recognition of the money, cloth and other basic things to make their life easier. The convolution neural network (CNN) based visual recognition model by TensorFlow object application programming interface (API) that used single shot detector (SSD) with a pre-trained model from Mobile V2 is developed at Google dataset. Visually impaired persons capture the image and will be compared with the preloaded image dataset for dataset recognition. The verbal message with the name of the image will let the blind used know the captured image. The object recognition achieved high accuracy and can be used without using internet connection. The visually impaired specifically are largely benefited by this research.
Co-Authors Haslinah Mohd Nasir Mohd Faizal Zulkifli Mohd Syafiq Mispan Noor Mohd Ariff Brahin