HOLT-Net: Detecting smokers via human–object interaction with lite transformer network

Author:

Ling Hua-Bao,Huang DongORCID,Cui Jinrong,Wang Chang-DongORCID

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference56 articles.

1. YOLOv4: Optimal speed and accuracy of object detection;Bochkovskiy,2020

2. End-to-end object detection with transformers;Carion,2020

3. Chao, Y.-W., Liu, Y., Liu, X., Zeng, H., Deng, J., 2018. Learning to detect human-object interactions. In: Proc. of IEEE Winter Conference on Applications of Computer Vision. pp. 381–389.

4. Deep learning based driver smoking behavior detection for driving safety;Chien;J. Imag. Graph.,2020

5. Neural networks application to detect the facts of smoking in video surveillance systems;Danilchenko;J. Phys.,2021

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