Design and development of an indoor navigation system using denoising autoencoder based convolutional neural network for visually impaired people

Author:

Akilandeswari J.,Jothi G.,Naveenkumar A.,Sabeenian R. S.,Iyyanar P.,Paramasivam M. E.

Funder

Science for Equity, Empowerment and Development Division

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Reference66 articles.

1. Afif M, Ayachi R, Pissaloux E, Said Y, Atri M (2020) Indoor objects detection and recognition for an ICT mobility assistance of visually impaired people. Multimed Tools Appl 79(41):31645–31662

2. Ahmad M, Shabbir S, Oliva D, Mazzara M, Distefano S (2020) Spatial-prior generalized fuzziness extreme learning machine autoencoder-based active learning for hyperspectral image classification. Optik 206(163712):1–8

3. Akilandeswari J, Naveenkumar A, Sabeenian RS, Iyyanar P, Paramasivam ME, Jothi G (2021) An investigation on indoor navigation systems. Evolution in computational intelligence. Springer, Singapore, pp 115–124

4. Akilandeswari J, Jothi G, Naveenkumar A, Sabeenian RS, Iyyanar P, Paramasivam ME (2021) Detecting pulmonary embolism using deep neural networks. Int J Perform Eng 17(3):322–332

5. Bonde GD, Barwal PU, Pal SR, Khan SI, Ablankar K (2015) Finding indoor position of person using wi-fi & smartphone: a survey. Int J Innov Res Sci Technol 1(8):202–207

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