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UAV Vehicle Detection System Based on YOLOv8 7

UAV Vehicle Detection System Based on YOLOv8

引用

7th international conference on computer Network, Electronic and automation, ICCNEA 2024

作者： Chang, Hao Wang, Zhongsheng School of Computer Science and Engineering Xi’an Technological University Shaanxi Xi’an China

To utilize the drone vehicle detection technology to observe the road traffic conditions in real-time, thereby improving the operational effectiveness and safety of the traffic system, this paper adopts a vehicle target detection algorithm based on YOLOv8. YOLOv8 is the latest iteration developed by Ultralytics, which has further improvements and enhancements compared to YOLOv5. In the backbone network, YOLOv8 employs a C2f structure with richer gradient flow, boosting feature selection capabilities, and enhancing target detection performance and accuracy;In the detection head, YOLOv8 utilizes a Decoupled Head design and uses an improved Anchor-Free method to reduce computational complexity while improving detection efficiency;In terms of loss function, YOLOv8 utilizes the The Task-Aligned Assigner positive sample allocation strategy, and adds the Distribution Focal Loss to improve the model's generalization ability. This paper divides the vehicles data set into 5 types, trains it using a pre-training model, and optimizes the network parameters through multiple iterations to achieve better detection performance. The experimental results indicate that YOLOv8 reaches the mAP of over 97% on the experimental data set, which is an improvement of approximately 8% compared to YOLOv5, and achieves a good detection performance, and is highly practical. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Aircraft detection

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Wheeled Mobile Robot Navigation Based on the Fusion of A* Algorithm and Improved Dynamic Window Approach 1

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Jiao, Ting Kong, Lingxin Hu, Conglin School of Automation and Software Engineering Shanxi University Taiyuan030031 China

ISBN: (数字)9789819603138

ISBN: (纸本)9789819603121

The A* method is frequently utilized for strategizing navigational routes for autonomous wheeled robots, but it is not applicable to scenarios with dynamic obstacles. While the Dynamic Window Approach (DWA) algorithm can adapt to dynamic environments, it is limited in terms of path smoothing and the flexibility of adjusting the weights within its evaluation function. To address these challenges, this paper proposes a hybrid path planning strategy that integrates the A* algorithm with an enhanced DWA algorithm, aiming at improving navigation efficiency and ensuring safety of robots in environments containing both static and dynamic obstacles. Initially, we introduce the principles of the A* and DWA algorithm. Subsequently, by incorporating a smooth evaluation function into the DWA algorithm and proposing a mechanism to dynamically adjust the weights, we improve the algorithm’s local obstacle avoidance capability. Further, by combining these two algorithms, we utilize the A* algorithm for global path planning and the improved DWA algorithm for local obstacle avoidance along the path. A series of real-robot tests validate the efficiency of the suggested approach in handling static and dynamic obstacles, demonstrating its good navigation performance in complex environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Mobile robots

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Monitoring System of Rare Earth Electrolysis Equipment Based on OPC UA Technology 2

Monitoring System of Rare Earth Electrolysis Equipment Based...

引用

2022 2nd international conference on computer, Internet of Things and Control engineering, CITCE 2022

作者： Chen, Jie Liu, Feifei Wen, Zhenxin Zhou, Dong School of Electrical Engineering and Automation Jiangxi University of Science and Technology Jiangxi Ganzhou341000 China

A set of rare earth electrolysis equipment monitoring systems based on OPC unified architecture is proposed given the complex environment of the rare earth electrolysis workshop, the difficulty of data acquisition, and the interconnection between equipment. The monitoring client of rare earth electrolysis equipment based on OPC UA communication protocol is designed and developed with C # language. The connection between the OPC UA server and the monitoring system is realized, and the data acquisition and real-time monitoring of the running state of the electrolysis equipment are completed. The primary goal of the rare earth electrolysis field equipment is to acquire and monitor rare earth electrolysis process current, voltage, and other internal state data in real-time. © Published under licence by IOP Publishing Ltd.

关键词： Rare earths

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Balancing Real-world Interaction and VR Immersion with AI Vision Robotic Arm 20

Balancing Real-world Interaction and VR Immersion with AI Vi...

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20th IEEE international conference on Mechatronics and automation, ICMA 2023

作者： Yang, Xiaoran Zhan, Yang Iwasaki, Yukiko Shi, Miaohui Tang, Shijie Iwata, Hiroyasu Waseda University Dept. Modern Mechanical Engineering 3-4-1 Ookubo Shinjuku-ku Tokyo169-8555 Japan Waseda University Dept. Computer Science and Engineering 3-4-1 Ookubo Shinjuku-ku Tokyo169-8555 Japan

ISBN: (纸本)9798350320831

With the widespread adoption of Virtual Reality (VR) technology, VR devices can be more realistic and make the tasks they perform feel real to the user. It is this sense of realism that makes more and more people are using VR headsets. While using VR devices, the need to interact with the real world will also exist. For example, when people are using a VR headset to study and work, they have a physiological need (thirst, hunger, etc.), and need to interact with reality. But the closed nature of the VR headset causes this interaction to be very disruptive to the immersion of the user's current task. To address this issue, we propose an interaction method that combines an AI vision algorithm and a robotic arm to preserve immersion during task performance in VR. This method addresses the challenge of interacting with the real world while using closed VR devices. Our experiments show that our method outperforms see-through and mapping methods, allowing users to quickly re-immerse themselves after interruptions and reducing interruptions during real-world task performance. Future research will focus on improving this method without sensitization and expanding the range of real-world operations that can be performed. © 2023 IEEE.

关键词： Virtual reality

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Evaluating the Impact of Passive Fatigue on Pilots Using Performance and Subjective States Measures 20th

Evaluating the Impact of Passive Fatigue on Pilots Using Per...

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20th international conference on engineering Psychology and Cognitive Ergonomics (EPCE) Held as Part of the 25th international conference on Human-computer Interaction (HCII)

作者： Conte, Stefano Harris, Donald Blundell, James Coventry Univ Fac Engn Environm & Comp Coventry CV1 5FB W Midlands England Coventry Univ Inst Clean Growth & Future Mobil Coventry CV1 5FB W Midlands England

ISBN: (纸本)9783031353918;9783031353925

Fatigue is a serious threat to flight safety, being a contributing factor of many aviation accidents. Sleep-related fatigue has been the most researched;however, fatigue also depends on task-related factors such as time-on-task and workload. Desmond and Hancock [1] theorized two opposite types of task-related fatigue: active fatigue (induced by cognitive overload) and passive fatigue (elicited by prolonged, understimulating and monotonous tasks). Research mainly conducted in the automotive sector demonstrated the existence of these different states and found that passive fatigue is linked to decline in performance and vigilance, together with task disengagement. automation is extensively used in most flights, and though pilots are particularly vulnerable to passive fatigue due to the nature of their tasks (especially during cruise with autopilot engaged), no specific passive fatigue research involving pilots exist. This study intended to fill that gap, by employing well-rested licensed pilots (N = 26) who underwent an experiment involving the Multi-Attribute Task Battery (MATB) which replicates some of the tasks encountered during flight. Pilots were randomly assigned to either a one-hour very lowworkload scenario intended to induce passive fatigue, or a one-hour moderate workload control scenario. Pilot performance on the MATB was measured as simple reaction times (SRTs) and the frequency of missed cues on a systemmonitoring task. Subjective measures were used to evaluate how task engagement and perceived workload changed over the course of the experiment. Results confirmed that passive fatigue had a detrimental effect on performance as pilots in that scenario showed significantly slower SRTs compared to the control group. Task engagement scores did not decline as predicted, but instead increased significantly more in the passive fatigue scenario, indicating a possible self-assessment inefficacy generated by the monotonous tasks. These findings suggests that wakefu

关键词： Passive Fatigue Pilot Fatigue automation Autopilot Underload Workload Flight Safety Reaction Time Task Engagement Vigilance MATB

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An Approach for Securing Data Access with Blockchain Technology and Machine Learning 4

An Approach for Securing Data Access with Blockchain Technol...

引用

4th international conference on Computation, automation and Knowledge Management, ICCAKM 2023

作者： Ahire, Nilesh B. Chaudhari, Sarthak A. Jagtap, Varunraje J. Shinde, Prathamesh S. Kapale, Namdev D. Sanjivani College of Engineering Savitribai Phule Pune University Department of Electronics and Computer Engineering Pune India

ISBN: (纸本)9798350393248

The quantity of data is quickly expanding as a direct result of the increasing number of devices that are linked to the internet. Big data offers a wide range of potential uses and benefits, but it also poses a number of challenges that need to be surmounted before the quality of the services that are provided can be improved. These problems are associated with the security and integrity of data, analytics, the organization of large amounts of data, and acumen. Big data will see tremendous expansion as a consequence of the methods it has made available for decentralized data administration, the reconciliation of digital property, and the sharing of data through the internet of things. It is very difficult for unauthorized parties to access the data that is kept on the blockchain network due to the fact that the data is encrypted and the network is decentralized. This article provides some insightful and in-depth discussion on the applications of big data. These results might be investigated using machine learning techniques that are driven by the context in which the data was collected. This study investigates the classification of data via the use of machine learning and blockchain techniques, as well as various selection procedures, query strategies, application development, and safety measures. Through the use of blockchain technology, problems with the protection of highly secure data may be overcome. This paper presents a comprehensive investigation of the relationships that exist between blockchain technology and machine learning. In addition, we will investigate a variety of challenges that may be encountered when using the blockchain technology to the process of machine learning. © 2023 IEEE.

关键词： Blockchain

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A Study to Compare YOLO Family Models for Metal Surface Anomaly Detection

A Study to Compare YOLO Family Models for Metal Surface Anom...

引用

2023 IEEE international conference on Big Data, BigData 2023

作者： Koc, Abdusselam Albayrak, Ozlem Kurt, Yasar Unal, Perin Ted University Faculty of Computer Engineering Ankara Turkey Research and Development Teknopar Industrial Automation Ostim Technical University Graduation School of Engineering and Sciences Ankara Turkey Ostim Technical University Graduation School of Engineering and Sciences Turkey

ISBN: (纸本)9798350324457

Anomaly detection is an important process that needs to be automated. Metal is an essential material that is heavily used in manufacturing of many different products. Automated detection of anomalies on metal surfaces is a topic that has been widely studied both by the researchers in the academia and by the practitioners. In the recent years, many studies have been conducted that apply deep learning for anomaly detection on metal surfaces. In this study, using NEU-DET data set, we have applied YOLO family models (YOLOv4, YOLOv5, YOLOv6, YOLOv7 and YOLOv8) in order to classify defects of images of steel. The results presented that with respect to mAP50 YOLOv8 has outperformed the other models. In the short term, we aim to utilize real images taken from home appliances products and perform a replication study. As for the long-term research we aim to develop and test our model based on real data set belonging to a Horizon Europe project. YOLOv8 has presented the best performance. © 2023 IEEE.

关键词： Anomaly Detection computer Vision Deep Learning

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Analysis of Doubly-fed Wind Turbines Oscillation Considering the Influence of Wind Speed 7

Analysis of Doubly-fed Wind Turbines Oscillation Considering...

引用

2022 7th international Seminar on computer Technology, Mechanical and Electrical engineering, ISCME 2022

作者： Yang, Dongju School of Electrical and Automation Engineering Shandong University of Science and Technology Shandong Province Qingdao266590 China

The accepted models of wind turbine and generator, respectively, were used to investigate how wind speed affected the subsynchronous oscillation of Double-fed wind turbine. Secondly, the oscillation characteristics of output are analyzed in the model/simulation of the PSCAD / EMTDC platform. The energy consumed when the wind speed changes are mainly affected by the subsystem of wind turbine. Below rated wind speed, increasing wind speed can inhibit subsynchronous oscillation, and increase the stability of the unit. The wind speed on the sub-synchronous oscillation is small as higher than normal wind speed. © Published under licence by IOP Publishing Ltd.

关键词： Wind turbines

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AI and IoT in Digital Marketing: Enhancing automation, Personalization, and Consumer Interaction

AI and IoT in Digital Marketing: Enhancing Automation, Perso...

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2025 international conference on Pervasive Computational Technologies, ICPCT 2025

作者： Naredla, Suman Singh, Madhulika Chaturvedi, Nidhi Banerjee, Devleena Gobinath, V.M. Anil Tiwari, Dr. Sr University School of Business Telangana Warangal India Quantum University Computer Science and Engineering Uttarakhand Roorkee India Emirates Aviation University Faculty of Business Management Dubai United Arab Emirates Christ University India Rajalakshmi Institute of Technology Mechanical Engineering Department Tamilnadu Chennai India Rnb Global University Bikaner Department of Commerce and Management India

ISBN: (纸本)9798331508685

An interconnected system of Internet-enabled devices that can collect and transmit statistics via a wireless connection without the assistance of people is known as the Internet of Things (IoTs). Accordingly, the IoT's seductive power is causing significant shifts in the current corporate environment. The digital marketing industry stands to gain the most from this innovation, which is currently causing major shifts in many other sectors. Using a variety of digital marketing strategies, this innovation gathers numerous types of consumer statistics. IoT technological advancements' impact on digital marketing tactics and customer interaction has emerged as a crucial research topic as it begins to pervade many facets of everyday existence. This investigation examines the application of IoT-based machine learning (ML) in digital marketing for the food business. To give ML-based suggestions, consumer data is analyzed, interests are identified, and conduct is predicted using ML approaches. The ensemble technique aggregates the results of multiple ML techniques to produce an individual forecast. The accuracy matrices graphs for the K-nearest neighbor and decision trees produced excellent estimations, with 100% accuracy and 0.0 error, correspondingly. The naïve Bayes method achieved 97.2% accuracy with a 0.029 error, successfully identifying the right tags across every category. The guided ensemble of 3 ML methods is demonstrated by effectively enhancing digital marketing tactics in the food distribution industry by reducing duration and expenses. © 2025 IEEE.

关键词： Decision trees

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Research on Video Sample Collection and Processing Methods Based on Artificial Intelligence Platform 11th

Research on Video Sample Collection and Processing Methods B...

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11th international conference on Applications and Techniques in Cyber Intelligence, ATCI 2023

作者： Hu, An Wang, Qi Xu, Xiaoguang Zhao, Yao Ji, Qian Pei, Lei State Grid Henan Information and Telecommunication Company Henan Province Zhengzhou450052 China State Grid Henan Electric power Company Henan Province Zhengzhou450052 China Henan Jiuyu Tenglong Information Engineering Co. Ltd Henan Province Zhengzhou450052 China

This paper summarizes the video sample collection and processing methods based on artificial intelligence platform, focusing on video noise cancellation, content segmentation and classification, and feature extraction and representation techniques. The paper believes that the deep learning technology, especially the convolutional neural network, shows great potential in image recognition and video analysis, and effectively improves the level of automation and accuracy of video processing. This paper discusses the importance of building a large-scale and high-quality video sample library, and how to improve the processing efficiency and accuracy of video data through intelligent technology. © 2024 The Authors. Published by Elsevier B.V.

关键词： Convolutional neural networks

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