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Deep learning versus traditional methods for parking lots occupancy classification

机译：深入学习与传统的停车场入住分类方法

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Mohamed Sayed Farag; Mostafa Mohamed Mohie El Din; Hassan Ahmed Elshenbary;
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年度 2020
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专利

1. Deep learning-based vehicle occupancy detection in an open parking lot using thermal camera [J] . Paidi Vijay, Fleyeh Hasan, Nyberg Roger G. Intelligent Transport Systems, IET . 2020,第10期

机译：使用热敏摄像机的开放式停车场中基于深度学习的车辆占用检测
2. Deep learning for decentralized parking lot occupancy detection [J] . Amato Giuseppe, Carrara Fabio, Falchi Fabrizio, Expert Systems with Application . 2017,第APRa期

机译：深度学习用于分散式停车场占用率检测
3. An Image Feature-Based Method for Parking Lot Occupancy [J] . Paula T?tulea, Florina C?lin, Remus Brad, Future Internet . 2019,第8期

机译：基于图像特征的停车场占用方法
4. Real-Time Parking Lot Occupancy Detection System with VGG16 Deep Neural Network using Decentralized Processing for Public, Private Parking Facilities [C] . Vighnesh Dhuri, Afzal Khan, Yash Kamtekar, International Conference on Advances in Electrical, Computing, Communications and Sustainable Technologies . 2021

机译：使用分散处理公共停车设施与VGG16深神经网络的实时停车位检测系统
5. High school students' comparisons of newer versus traditional learning methods. [D] . Grence-Leggett, Lynn. 2005

机译：高中生比较新型学习方法和传统学习方法的比较。
6. Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning [O] . Xinggang Wang, Wei Yang, Jeffrey Weinreb, -1

机译：通过全自动磁共振成像分类搜索前列腺癌：深度学习与非深度学习
7. A deep learning approach to real-time parking occupancy prediction in transportation networks incorporating multiple spatio-temporal data sources [O] . Shuguan Yang, Wei Ma, Xidong Pi, 2019

机译：一种深入的学习方法，可以采用多种时空数据源的运输网络实时停车占用预测

Deep learning versus traditional methods for parking lots occupancy classification

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