@inproceedings{4269b4411f774f228ea6aeed9f311011,
title = "Abnormal object detection and recognition in the complex construction site via cloud computing",
abstract = "For the construction site image understanding, object detection and recognition are the most important tasks. In the construction site with electrical equipment, the scene need to be monitored carefully to avoid accident. In our work, one anomaly detection method via the cloud computation is proposed. The method consists of the one-stage deep learning object detection model and the one-class classification. The one-stage object detection method detects and recognizes the objects in the scenes. Then, the one-class SVM alarms the abnormal region. The proposal algorithm has been tested on several scenes of real construction sites, and achieves fine results practicably.",
keywords = "Anomaly detection, Cloud computing, Object detection, One-class classification",
author = "Chuang Wang and Jiakun Li and Tian Wang and Peng Shi and Hichem Snoussi and Xin Su",
note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 2019 Conference on Research in Adaptive and Convergent Systems, RACS 2019 ; Conference date: 24-09-2019 Through 27-09-2019",
year = "2019",
month = sep,
day = "24",
doi = "10.1145/3338840.3355648",
language = "英语",
series = "Proceedings of the 2019 Research in Adaptive and Convergent Systems, RACS 2019",
publisher = "Association for Computing Machinery, Inc",
pages = "71--75",
booktitle = "Proceedings of the 2019 Research in Adaptive and Convergent Systems, RACS 2019",
}