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Title: Automated Parking System in Smart Campus Using Computer Vision Technique
Authors: Banerjee, S.
Ashwin, T.S.
Ram Mohana Reddy, Guddeti
Issue Date: 2019
Citation: IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2019, Vol.2019-October, , pp.931-935
Abstract: In today's world we need to maintain safety and security of the people around us. So we need to have a well connected surveillance system for keeping active information of various locations according to our needs. A real-time object detection is very important for many applications such as traffic monitoring, classroom monitoring, security rescue, and parking system. From past decade, Convolutional Neural Networks is evolved as a powerful models for recognizing images and videos and it is widely used in the computer vision related work for the best and most used approach for different problem scenario related to object detection and localization. In this work, we have proposed a deep convolutional network architecture to automate the parking system in smart campus with modified Single-shot Multibox Detector (SSD) approach. Further, we created our dataset to train and test the proposed computer vision technique. The experimental results demonstrated an accuracy of 71.2% for the created dataset. � 2019 IEEE.
Appears in Collections:2. Conference Papers

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