0Human Detection using Improved YOLOv2: Images Captured by the UAV

Kwon, Juwon; Kwon, Soonchul

doi:10.36478/jeasci.2019.3946.3949

J. Eng. Appl. Sci.

2019

DOI: 10.36478/jeasci.2019.3946.3949

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0Human Detection using Improved YOLOv2: Images Captured by the UAV

Juwon Kwon¹,

Soonchul Kwon²

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“…image, we can easily get the position coordinates and prediction box size of the target in the image[24]. rough location information, we can obtain the relative position of the target and the camera with the camera as the reference frame.…”

mentioning

confidence: 99%

Research on Intelligent Embedded Fan System Based on YOLOv2 Lightweight Algorithm

Wei

Zhao

et al. 2022

Computational Intelligence and Neuroscience

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With the development of artificial intelligence, the application of intelligent algorithms to low-power embedded chips has become a new research topic today. Based on this, this study optimizes the YOLOv2 algorithm by tailoring and successfully deploys it on the K210 chip to train the face object detection algorithm model separately. The intelligent fan with YOLOv2 model deployed in K210 chip can detect the target of the character and obtain the position and size of the character in the machine coordinates. Based on the obtained information of character coordinate position and size, the fan's turning Angle and the size of air supply are intelligently perceived. The experimental results show that the intelligent fan design method proposed here is a new embedded chip intelligent method of cutting and improving the YOLOv2 algorithm. It innovatively designed solo tracking, crowd tracking, and intelligent ranging algorithms, which perform well in human perception of solo tracking and crowd tracking and automatic air volume adjustment, improve the accuracy of air delivery and user comfort, and also provide good theoretical and practical support for the combination of AI and embedded in other fields.

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confidence: 99%

Research on Intelligent Embedded Fan System Based on YOLOv2 Lightweight Algorithm

Wei

Zhao

et al. 2022

Computational Intelligence and Neuroscience

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Human detection based on deep learning YOLO-v2 for real-time UAV applications

Boudjit

Ramzan

2021

Journal of Experimental & Theoretical Artificial Intelligen

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0Human Detection using Improved YOLOv2: Images Captured by the UAV

Cited by 2 publications

References 0 publications

Research on Intelligent Embedded Fan System Based on YOLOv2 Lightweight Algorithm

Research on Intelligent Embedded Fan System Based on YOLOv2 Lightweight Algorithm

Human detection based on deep learning YOLO-v2 for real-time UAV applications

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