YOLOv4 algorithm for the real-time detection of fire and personal protective equipments at construction sites

[1]  Tiago M. Fernández-Caramés,et al.  Real-time personal protective equipment monitoring system , 2012, Comput. Commun..

[2]  Amir H. Behzadan,et al.  Deep learning for site safety: Real-time detection of personal protective equipment , 2020 .

[3]  Chang Wook Ahn,et al.  A Novel YOLOv3 Algorithm-Based Deep Learning Approach for Waste Segregation: Towards Smart Waste Management , 2020, Electronics.

[4]  Sung Wook Baik,et al.  Convolutional Neural Networks Based Fire Detection in Surveillance Videos , 2018, IEEE Access.

[5]  Miguel Cazorla,et al.  Semi-supervised 3D object recognition through CNN labeling , 2018, Appl. Soft Comput..

[6]  Ali Farhadi,et al.  YOLOv3: An Incremental Improvement , 2018, ArXiv.

[7]  Xiaochun Luo,et al.  Detecting non-hardhat-use by a deep learning method from far-field surveillance videos , 2018 .

[8]  Pu Li,et al.  Image fire detection algorithms based on convolutional neural networks , 2020, Case Studies in Thermal Engineering.

[9]  Xiaowei Luo,et al.  Transfer learning and deep convolutional neural networks for safety guardrail detection in 2D images , 2018 .

[10]  Feiniu Yuan,et al.  A Deep Normalization and Convolutional Neural Network for Image Smoke Detection , 2017, IEEE Access.

[11]  Berin Martini,et al.  Embedded Streaming Deep Neural Networks Accelerator With Applications , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[12]  Mei Jiang,et al.  Using channel pruning-based YOLO v4 deep learning algorithm for the real-time and accurate detection of apple flowers in natural environments , 2020, Comput. Electron. Agric..

[13]  Xin Nie,et al.  Deep Neural Network-Based Robust Ship Detection Under Different Weather Conditions , 2019, 2019 IEEE Intelligent Transportation Systems Conference (ITSC).

[14]  Amir H. Behzadan,et al.  Single- and multi-label classification of construction objects using deep transfer learning methods , 2019, J. Inf. Technol. Constr..

[15]  Hong-Yuan Mark Liao,et al.  YOLOv4: Optimal Speed and Accuracy of Object Detection , 2020, ArXiv.

[16]  Jixiu Wu,et al.  Automatic detection of hardhats worn by construction personnel: A deep learning approach and benchmark dataset , 2019, Automation in Construction.

[17]  Hyojoo Son,et al.  A Comparative Study of Machine Learning Classification for Color-based Safety Vest Detection on Construction-Site Images , 2018, KSCE Journal of Civil Engineering.

[18]  Sung Wook Baik,et al.  Efficient Convolutional Neural Networks for Fire Detection in Surveillance Applications , 2020 .

[19]  Li Sun,et al.  A Novel Weakly-Supervised Approach for RGB-D-Based Nuclear Waste Object Detection , 2018, IEEE Sensors Journal.

[20]  Sung Wook Baik,et al.  Early fire detection using convolutional neural networks during surveillance for effective disaster management , 2017, Neurocomputing.

[21]  Yanfang Ye,et al.  Unsupervised Feature Learning for Objects of Interest Detection in Cluttered Construction Roof Site Images , 2016 .

[22]  Ioannis Brilakis,et al.  Construction worker detection in video frames for initializing vision trackers , 2012 .

[23]  Ali Ismail Awad,et al.  Deep Learning in Computer Vision: Principles and Applications , 2020 .

[24]  Liang Zhao,et al.  Fire smoke detection algorithm based on motion characteristic and convolutional neural networks , 2017, Multimedia Tools and Applications.

[25]  Jochen Teizer,et al.  Mobile passive Radio Frequency Identification (RFID) portal for automated and rapid control of Personal Protective Equipment (PPE) on construction sites , 2013 .

[26]  Li Sun,et al.  Weakly-supervised DCNN for RGB-D Object Recognition in Real-World Applications Which Lack Large-scale Annotated Training Data , 2017, ArXiv.

[27]  F Akbar-Khanzadeh Factors contributing to discomfort or dissatisfaction as a result of wearing personal protective equipment. , 1998, Journal of human ergology.

[28]  Wentao Mao,et al.  Fire Recognition Based On Multi-Channel Convolutional Neural Network , 2018 .

[29]  Y. I. Cho,et al.  An Efficient Deep Learning Algorithm for Fire and Smoke Detection with Limited Data , 2018 .

[30]  Dong-Hyun Lee,et al.  CNN-based single object detection and tracking in videos and its application to drone detection , 2020, Multimedia Tools and Applications.

[31]  R. Karthik,et al.  Attention embedded residual CNN for disease detection in tomato leaves , 2020, Appl. Soft Comput..

[32]  Hiam Khoury,et al.  Vision-Based Framework for Intelligent Monitoring of Hardhat Wearing on Construction Sites , 2019, J. Comput. Civ. Eng..

[33]  Peter E.D. Love,et al.  A deep hybrid learning model to detect unsafe behavior: Integrating convolution neural networks and long short-term memory , 2018 .

[34]  Hiam Khoury,et al.  Automated Hardhat Detection for Construction Safety Applications , 2017 .

[35]  Berardo Naticchia,et al.  A monitoring system for real-time interference control on large construction sites , 2013 .

[36]  Huachao Mao,et al.  PPE Compliance Detection using Artificial Intelligence in Learning Factories , 2020 .

[37]  SangHyun Lee,et al.  Computer vision techniques for construction safety and health monitoring , 2015, Adv. Eng. Informatics.

[38]  Hendry,et al.  Automatic License Plate Recognition via sliding-window darknet-YOLO deep learning , 2019, Image Vis. Comput..

[39]  Man-Woo Park,et al.  Hardhat-Wearing Detection for Enhancing On-Site Safety of Construction Workers , 2015 .