An indoor scene recognition system based on deep learning evolutionary algorithms
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-023-09177-7.pdf
Reference29 articles.
1. Afif M, Ayachi R, Said Y, Pissaloux E, Atri M (2020) Indoor image recognition and classification via deep convolutional neural network. Proceedings of the 8th international conference on sciences of electronics, technologies of information and telecommunications (SETIT’18), vol 1. Springer International Publishing, Cham, pp 364–371
2. Afif M, Ayachi R, Said Y, Atri M (2021) Deep learning-based application for indoor wayfinding assistance navigation. Multimedia Tools Appl 80(18):27115–27130
3. Afif M, Ayachi R, Atri M (2022) Indoor objects detection system implementation using multi-graphic processing units. Cluster Comput. https://doi.org/10.1007/s10586-021-03419-9
4. Afif M, Ayachi R, Said Y, Atri M (2023) Deep learning-based technique for lesions segmentation in CT scan images for COVID-19 prediction. Multimedia Tools Appl. https://doi.org/10.1007/s11042-023-14941-w
5. Ayachi R, Afif M, Said Y, Atri M (2020a) Traffic signs detection for real-world application of an advanced driving assisting system using deep learning. Neural Process Lett 51:837–851
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