An adaptive visual diagnostic model for complex scenes based on unsupervised pseudo-label continuous learning and BiFPN-enhanced YOLO. [PDF]
Front NeurorobotWith the deployment of intelligent systems in open environments, visual perception capabilities are required for engineering applications. Traditional static visual detection models experience feature degradation under environmental changes. Conventional
Xu X, Li L, Jiang S, Li Y, Li B.
europepmc +2 more sources
An Infrared Image Defect Detection Method for Steel Based on Regularized YOLO
SensorsSteel surfaces often display intricate texture patterns that can resemble defects, posing a challenge in accurately identifying actual defects. Therefore, it is crucial to develop a highly robust defect detection model.
Yongqiang Zou, Yugang Fan
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A traffic sign detection model based on coordinate attention - bidirectional feature pyramid network
Shenzhen Daxue xuebao. Ligong ban, 2023 In the field of autonomous driving, the correct detection of traffic signs can provide important information for environmental perception. To address the low recognition rate and misdetection and missed detection issues of various traffic signs, we ...
LANG Binke +3 more
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Development of Face and Landmark Detection using EfficientNetV2 and BiFPN
, 2022 In this paper, we develop improved face and landmark detection algorithm using EfficientNetV2 as backbone and BiFPN as multi-scale feature extractor. EfficientNetV2 are a new family of convolutional networks that have faster training speed and better ...
Kim, Hyunduk +2 more
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Traffic Sign Detection Based on Lightweight YOLOv5 [PDF]
Zhengzhou Daxue xuebao. Gongxue banIn order to improve the detection speed of road traffic signs, an improved model based on lightweight YOLOv5 was proposed. Firstly, Ghost convolution and depthwise convolution were used to build a new Bottleneck, which could reduce the amount of ...
ZHANG Zhen +3 more
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Protective Equipment Wearing Detection Algorithm in Construction Scenarios Based on YOLOv8n [PDF]
Zhengzhou Daxue xuebao. Gongxue banIn view of the problems of protective equipment detection, such as information interference, uneven illumination and occlusion in the construction scene, a lightweight algorithm with improved YOLOv8n was proposed, which was called YOLO-LA .
LI Jun +3 more
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A coal mine underground drill pipes counting method based on improved YOLOv8n
Gong-kuang zidonghuaIn order to improve the efficiency and precision of underground drill pipe counting in coal mines, a coal mine underground drill pipe counting method based on the improved YOLOv8n model is proposed.
JIANG Yuanyuan, LIU Songbo
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Severity Grading Model for Camellia Oleifera Anthracnose Infection Based on Improved YOLACT
智慧农业ObjectiveCamellia oleifera is one of the four major woody oil plants in the world. Diseases is a significant factor leading to the decline in quality of Camellia oleifera and the financial loss of farmers.
NIE Ganggang +3 more
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Crop Pest Target Detection Algorithm in Complex Scenes:YOLOv8-Extend
智慧农业ObjectiveIt is of great significance to improve the efficiency and accuracy of crop pest detection in complex natural environments, and to change the current reliance on expert manual identification in the agricultural production process.
ZHANG Ronghua, BAI Xue, FAN Jiangchuan
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Helmet detection method based on improved YOLOv5
工程科学学报To address the challenge of low detection accuracy in existing safety helmet detection algorithms, particularly in scenarios with small targets, dense environments, and complex surroundings like construction sites, tunnels, and coal mines, we introduce ...
Gongyu HOU +5 more
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