Suchergebnisse - "YOLOv3 algorithm"

Human Detection and Action Recognition for Search and Rescue in Disasters Using YOLOv3 Algorithm von Valarmathi, B., Kshitij, Jain, Dimple, Rajpurohit, Srinivasa Gupta, N., Harold Robinson, Y., Arulkumaran, G., Mulu, Tadesse

“… ) division to survey the state of impacted regions. Manual video analysis by human observers takes time and is subject to mistakes …”
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The Application of Action Recognition Based on MPP-YOLOv3 Algorithm in Posture Correction von Wang, Zhongwei, Dong, Shujuan

“… Posture recognition, as a research hotspot, has been widely applied. A recognition model based on bone key point detection is proposed for the posture …”
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Research on automatic identification and evaluation method of piano playing skills based on convolutional neural network von Wu, Xiaoliang

“… This paper proposes a deep learning based piano hand fingering recognition system using YOLOv3 target detection algorithm for network training of the model …”
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Object Detection Algorithm Based on Alternate-Attention von He, Xuejie, Bai, Chenyan, Qi, Haoru, Liu, Honghong

“… But giving the same attention weight to all grids during detection will result in the inability to highlight the detection subject, so the positioning accuracy of the bounding box is still room for improvement …”
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Research on smoke flame detection based on improved YOLOv3 von Wang, Lin ke

“… Although there are detection methods such as temperature and smoke sensors, they are still subject to environmental factors and cannot achieve real-time detection of smoke and flames …”
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Assessment of Automatic Cephalometric Landmarks Identification Using Artificial Intelligence von Bulatova, Galina V

“… ) Deep Learning Convolutional Neural Networks YOLOv3 algorithm and Manually Traced (MT) group. Methods: AAOF Legacy Denver collection was used to obtain 110 cephalometric images for this study …”
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An Image Analysis-Based Automated Method using Deep Learning for Grain Counting von Ajikaran, Ramesh, Hewarathna, Ashen Iranga, Palanisamy, Vigneshwaran, Joseph, Charles, Thuseethan, Selvarajah

“… The datasets consist were separated into three groups: training, validation, and test. For object detection, the YOLOv5, YOLOv4, and YOLOv3 algorithms represent cutting-edge deep learning frameworks …”
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