the proceedings contain 108 papers. the special focus in this conference is on Advanced Hybrid informationprocessing. the topics include: A Method of Resolving the Conflict of Shared Resources in Online Teaching of D...
ISBN:
(纸本)9783031505485
the proceedings contain 108 papers. the special focus in this conference is on Advanced Hybrid informationprocessing. the topics include: A Method of Resolving the Conflict of Shared Resources in Online Teaching of Design Professional Artworks Based on Feedback Integration;design of Substation Battery Remote Monitoring System Based on LoRa technology;optimization Scheduling Algorithm of Logistics Distribution Vehicles Based on Internet of Vehicles Platform;design of Logistics information Tracking System for Petrochemical Enterprises Under the Background of Intelligent Logistics;real Time Tracking of the Position of Intelligent Logistics Cold Chain Transportation Vehicles Based on Wireless Sensor Networks;a Real Time Tracking Method for Intelligent Logistics Delivery Based on Recurrent Neural Network;a Real Time Tracking Method for Unmanned Traffic Vehicle Paths Based on Electronic Tags;error Motion Tracking Method for Athletes Based on Multi Eye Machine Vision;research on Real Time Tracking Method of Multiple Moving Objects Based on Machine Vision;a Method for Identity Feature Recognition in Wireless Visual Sensing Networks Based on Convolutional Neural Networks;feature Recognition of Rural Household Domestic Waste Based on ZigBee Wireless Sensor Network;a Method of Recognizing Specific Movements in Children’s Dance Teaching Video Based on Edge Features.
Livestock Internet of things is the application of Internet of things (IOT) to the animal husbandry to realize the collection, transmission, and calculation processing of animal husbandry information to achieve smart ...
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the proceedings contain 108 papers. the special focus in this conference is on Advanced Hybrid informationprocessing. the topics include: A Method of Resolving the Conflict of Shared Resources in Online Teaching of D...
ISBN:
(纸本)9783031505454
the proceedings contain 108 papers. the special focus in this conference is on Advanced Hybrid informationprocessing. the topics include: A Method of Resolving the Conflict of Shared Resources in Online Teaching of Design Professional Artworks Based on Feedback Integration;design of Substation Battery Remote Monitoring System Based on LoRa technology;optimization Scheduling Algorithm of Logistics Distribution Vehicles Based on Internet of Vehicles Platform;design of Logistics information Tracking System for Petrochemical Enterprises Under the Background of Intelligent Logistics;real Time Tracking of the Position of Intelligent Logistics Cold Chain Transportation Vehicles Based on Wireless Sensor Networks;a Real Time Tracking Method for Intelligent Logistics Delivery Based on Recurrent Neural Network;a Real Time Tracking Method for Unmanned Traffic Vehicle Paths Based on Electronic Tags;error Motion Tracking Method for Athletes Based on Multi Eye Machine Vision;research on Real Time Tracking Method of Multiple Moving Objects Based on Machine Vision;a Method for Identity Feature Recognition in Wireless Visual Sensing Networks Based on Convolutional Neural Networks;feature Recognition of Rural Household Domestic Waste Based on ZigBee Wireless Sensor Network;a Method of Recognizing Specific Movements in Children’s Dance Teaching Video Based on Edge Features.
Human pose estimation is an essential task in computer vision, applied in motion recognition, motion capture, augmented reality, etc. the emergence of Lite HRNet balances computational complexity with high precision, ...
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this initiative aims to quickly identify individuals who violate traffic laws and notify them of their violations via What's App, reducing the burden on law enforcement officers."the major goal is to improve ...
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Fatigue driving is a longstanding hazard in the field of road traffic safety. the factors such as longtime driving, lack of sleep, and work pressure result in driver fatigue which impair driver ability to detect and r...
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ISBN:
(纸本)9798400708305
Fatigue driving is a longstanding hazard in the field of road traffic safety. the factors such as longtime driving, lack of sleep, and work pressure result in driver fatigue which impair driver ability to detect and respond to sudden situations, and increase the risk of serious traffic accidents. this paper proposes a novel method for driver fatigue detection based on YOLOv5 algorithm. Firstly, a fatigue detection dataset is collected and created for this purpose. the YOLOv5 algorithm is then utilized to detect driver multiple facial fatigue features such as yawning, closed eyes, and head nodding, and the driver's fatigue status is determined based on the statistical frequency of the three fatigue characteristics. Furthermore, the YOLOv5 trained model is deployed on the Tensor processing Unit (TPU) computing device. the experimental results demonstrated that the YOLOv5 algorithm model achieved a mAP@0.5 of 98.51% when evaluated on the validation sets. the driver fatigue detection system deployed on the TPU computing device can perform at 25 fps with an average accuracy of 93.8%. this system can monitor the driver's status in real time in practical applications, timely remind drivers to pay attention to safety, and help reduce the risk of traffic accidents caused by fatigue driving.
the current base station management faces challenges such as imprecise information perception, a lack of precise prediction techniques for load and energy consumption, and the absence of refined optimization methods f...
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ISBN:
(纸本)9798400708305
the current base station management faces challenges such as imprecise information perception, a lack of precise prediction techniques for load and energy consumption, and the absence of refined optimization methods for multi-source comprehensive scheduling. It can only achieve a quantitative complementarity of energy on the supply side, the grid side, and the load side, without considering the differences in energy quality of various forms of energy and their optimal scheduling in conversion, transmission, storage, and utilization. Simultaneously, there is a severe deficiency in crowss-temporal and spatial allocation and utilization of energy, as well as the use of edge computing and big data analytics for precise prediction and optimization scheduling. this has resulted in low overall energy utilization efficiency, high carbon emissions, and other issues. there is an urgent need to break through the key technologies of accurate perception, precise prediction, precise scheduling, and fine control in the energy Internet of things system for base stations. the project team has put forth a scientifically sound solution, addressing issues related to precise perception of base station status, accurate load prediction, fine optimization of energy management, and precise control of comprehensive energy systems. they have proposed the "Uncertain Data processing Algorithm for Base Station Energy Consumption" to tackle and solve the challenge of precise load prediction in energy IoT based on high-noise, low-quality data.
A high gain vertical polarization omnidirectional antenna is proposed, with overall size of 250mm×16mm×1mm. A double U-shaped symmetrical dipole oscillator is used as radiation oscillator, and then four radi...
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In recent years, withthe rapid development of deep learning, many computer vision tasks have achieved breakthroughs again and again. In many computer vision tasks, fault detection has been widely concerned because of...
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ISBN:
(纸本)9798350377040;9798350377033
In recent years, withthe rapid development of deep learning, many computer vision tasks have achieved breakthroughs again and again. In many computer vision tasks, fault detection has been widely concerned because of its great application value. Compared with traditional image target fault detection methods, the image target fault detection method based on deep learning digs image features layer by layer through deep neural networks, and can learn more advanced abstract features without manual feature design, and has better generalization. Based on deep learning technology, this paper studies the algorithm of image target fault detection. In this paper, a fault detection method based on attention mechanism is proposed to solve the problem that the fault detection based on object detection cannot distinguish the fault with not obvious features. this method uses the attention mechanism to assign different weights to each feature graph when the network performs multi-scale feature fusion, so that the network selectively pays attention to the higher-order semantic information and lower-order detail informationthat are more helpful for fault identification, and improves the recognition ability of the network for the faults with less obvious features. In the experimental verification stage, the performance of the proposed method is higher than that of the benchmark method on both private and public datasets. Among them, 93.28% mAP@all is achieved on the private dataset, which is 1.16% higher than that of the benchmark method (92.04%). 78.55% mAP@0.5 was achieved on the publicly available VOC dataset, an improvement of 1.48% compared to 77.07% for the benchmark method. At the same time, FPS of this method can be maintained at 74,mAP@0.5 up to 99.55%, which can fully meet the real-time requirements and achieve high detection accuracy, which proves that the algorithm in this paper has reached the advanced level.
As intelligent transportation systems evolve, traffic management faces increasing challenges in processing vast amounts of heterogeneous data and supporting complex decision-making processes. To address these challeng...
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