Deep learning for decentralized parking lot occupancy detection

作者：

Highlights：

• We propose an effective CNN architecture for visual parking occupancy detection.

• The CNN architecture is small enough to run on smart cameras.

• The proposed solution performs and generalizes better than other SotA approaches.

• We provide a new training/validation dataset for parking occupancy detection.

摘要

•We propose an effective CNN architecture for visual parking occupancy detection.•The CNN architecture is small enough to run on smart cameras.•The proposed solution performs and generalizes better than other SotA approaches.•We provide a new training/validation dataset for parking occupancy detection.

论文关键词：Machine learning,Classification,Deep learning,Convolutional neural networks,Parking space dataset

论文评审过程：Received 14 July 2016, Revised 21 September 2016, Accepted 27 October 2016, Available online 29 October 2016, Version of Record 2 January 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.10.055