基于视觉信息和卷积神经网络的街道停车位自动检测

Tala Bazzaza, Zuhao Chen, Sandhiya Prabha, H. R. Tohidypour, Yixiao Wang, M. Pourazad, P. Nasiopoulos, Victor C. M. Leung
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引用次数: 2

摘要

本文提出了一种独特的实时街道停车检测方案,该方案利用视觉信息和YOLOv4卷积神经网络来准确检测可用停车位。我们还引入了一个新的视频数据集,它是专门为这个任务捕获的,用于训练我们的网络。我们的网络是同类中的第一个,成功地检测到可用的街道停车位。我们的模型的性能评估证实了它在所有类型的场景中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Street Parking Space Detection Using Visual Information and Convolutional Neural Networks
This paper proposes a unique real-time street parking detection scheme that utilizes visual information and the YOLOv4 convolutional neural network to accurately detect available parking spaces. We also introduce a new video dataset that is captured specifically for this task and is used for training our network. Our network being the first of its kind, successfully detects available street parking spaces. Performance evaluations of our model confirm its efficacy across all types of scenarios.
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