Parking slot occupancy prediction using LSTM-Reference-Cited by-同舟云学术

Parking slot occupancy prediction using LSTM

Published:2022-09-10 Issue: Volume: Page:
ISSN:1614-5046
Container-title:Innovations in Systems and Software Engineering
language:en
Short-container-title:Innovations Syst Softw Eng

Author:

Kasera Rohit Kumar^ORCID,Acharjee Tapodhir

Publisher

Springer Science and Business Media LLC

Subject

Software

Link

https://link.springer.com/content/pdf/10.1007/s11334-022-00481-3.pdf

Reference37 articles.

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2. Zheng Y, Rajasegarar S, Leckie C (2015) Parking availability prediction for sensor-enabled car parks in smart cities. In: 2015 IEEE tenth international conference on intelligent sensors, sensor networks and information processing (ISSNIP), pp 1–6. https://doi.org/10.1109/ISSNIP.2015.7106902

3. Bura H, Lin N, Kumar N, Malekar S, Nagaraj S, Liu K (2018) An edge based smart parking solution using camera networks and deep learning. In: 2018 IEEE international conference on cognitive computing (ICCC), pp 17–24. https://doi.org/10.1109/ICCC.2018.00010

4. Rahim RU, Aslam M, Zoolnurain, Khan MG, Basra IA (2021) Pakistani standard vehicle plates recognition using deep neural networks. In: 2021 International conference on artificial intelligence (ICAI), pp 158–163. https://doi.org/10.1109/ICAI52203.2021.9445199

5. Bhatta S, Srivastava H, Das SK, Singh P (2021) License plate detection for smart parking management. In: International conference on emerging trends and advances in electrical engineering and renewable energy, vol 690, pp 71–79. https://doi.org/10.1007/978-981-15-7504-4_8

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