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Neural Processing Letters
Published in: Neural Processing Letters 3/2020

20-03-2020

Deep Learning Based Application for Indoor Scene Recognition

Authors: Mouna Afif, Riadh Ayachi, Yahia Said, Mohamed Atri

Published in: Neural Processing Letters | Issue 3/2020

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Abstract

Recognizing indoor scene and objects and estimating their poses present a wide range of applications in robotic field. This task becomes more challenging especially in cluttered environments like the indoor scenery. Scaling up convnets presents a key component in achieving better accuracy results of deep convolutional neural networks. In this paper, we make use of the rethinked efficient neural networks and we fine-tune them in order to develop a new application used for indoor object and scene recognition system. This new application will be especially dedicated for blind and visually impaired persons to explore new indoor environments and to fully integrate in daily life. The proposed indoor object and scene recognition system achieves new state-of-the-art results in MIT 67 indoor dataset and in scene 15 dataset. We obtained 95.60% and 97% respectively as a recognition rate.
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Metadata
Title
Deep Learning Based Application for Indoor Scene Recognition
Authors
Mouna Afif
Riadh Ayachi
Yahia Said
Mohamed Atri
Publication date
20-03-2020
Publisher
Springer US
Published in
Neural Processing Letters / Issue 3/2020
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-020-10231-w

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