Deep Single Models vs. Ensembles: Insights for a Fast Deployment of Parking Monitoring Systems-Reference-Cited by-同舟云学术

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Deep Single Models vs. Ensembles: Insights for a Fast Deployment of Parking Monitoring Systems

Published:2023-12-15 Issue: Volume:198 Page:1379-1384
ISSN:
Container-title:2023 International Conference on Machine Learning and Applications (ICMLA)
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Author:

Hochuli Andre Gustavo¹,Barddal Jean Paul¹,Palhano Gillian Cezar²,Mendes Leonardo Matheus²,Lisboa de Almeida Paulo Ricardo³

Affiliation:

1. Pontificia Universidade Catolica do Parana,Graduate Program in Informatics (PPGIa),Curitiba,PR,Brazil

2. Pontificia Universidade Catolica do Parana,Curitiba,PR,Brazil

3. Universidade Federal do Parana,Department of Informatics (DInf),Curitiba,PR,Brazil

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10459339/10459727/10459789.pdf?arnumber=10459789

Reference20 articles.

1. Smart parking sensors, technologies and applications for open parking lots: a review

2. Automatic vision-based parking slot detection and occupancy classification

3. An Efficient Algorithm for Detection of Vacant Spaces in Delimited and Non-Delimited Parking Lots

4. Real-Time Parking Lot Occupancy Detection System with VGG16 Deep Neural Network using Decentralized Processing for Public, Private Parking Facilities

5. A systematic review on computer vision-based parking lot management applied on public datasets;Almeida;Expert Systems with Applications,2022

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