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Research on automatic segmentation and recognition of oracle bone script images based on deep learning technology 4

Research on automatic segmentation and recognition of oracle...

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4th international conference on computer Graphics, Image, and Virtualization, ICCGIV 2024

作者： Ruan, Qiaoqiao Chang, Xinyu Cui, Ziyi School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781510683242

Oracle bone script is an important form of ancient Chinese writing, and its study is significant for understanding ancient society, culture, and the development of language. With technological advancements, particularly in computer vision and deep learning, the digital study of oracle bone script has become feasible. This research aims to enhance the efficiency of automatic segmentation and recognition of oracle bone script images through deep learning technology. First, this paper investigates the unique challenges presented by oracle bone script images, such as dotted noise, artificial textures, and intrinsic patterns, and applies image preprocessing techniques such as gray-scaling, binarization, and noise reduction to optimize image quality. Second, convolutional neural networks (CNNs) are employed for image segmentation to accurately isolate individual characters within the oracle bone script images. Then, recurrent neural networks (RNNs) are used to automatically recognize the segmented characters, achieving the conversion from images to text. Finally, tests on original rubbings validate the model's high accuracy and reliability in automatic single-character segmentation and recognition. This study not only improves the level of automation in the image processing of oracle bone script but also provides methods and references for the image processing of other ancient artifacts. © 2024 SPIE.

关键词： Convolutional neural networks

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Industry 4.0 and Beyond - Present Trends, Emerging Solutions and Future Technologies in the Area of the Industrial automation 9

Industry 4.0 and Beyond - Present Trends, Emerging Solutions...

引用

Joint 9th international conference on Digital Arts, Media and Technology with 7th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2024

作者： Zahariev, Plamen Hristov, Georgi Chaisricharoen, Roungsan Bencheva, Nina Beloev, Ivan Zlatov, Nikolay Le, Chi Hieu Georgiev, Georgi Kinaneva, Diyana University of Ruse 'Angel Kanchev' Department of Telecommunications Ruse Bulgaria Mae Fah Luang University School of Information Technology Chiang Rai Thailand University of Ruse 'Angel Kanchev' Department of Transport Ruse Bulgaria Institute of Mechanics Bulgarian Academy of Sciences Sofia Bulgaria University of Greenwich Faculty of Science & Engineering Kent United Kingdom

ISBN: (纸本)9798350318241

The constant development of new technologies and production methods and their integration in the various fabrication and manufacturing processes has fuelled several waves of novelties and innovations in the industrial domain, which are also known as the industrial revolutions. These transformative processes have changed humanity forever and have shifted the economic models and the manufacturing methods of our societies - from the hand-based farming and manual production of goods to the total utilization of information systems, machines and robots for the large-scale fabrication of high-quality products and the delivery of modern services. The industrial revolutions have led to increased production volumes, higher manufacturing efficiency, lower prices, better working conditions, improved salaries and to significant improvements of the infrastructure, the railroad and the road networks. The recent technological advancements and the development of novel paradigms for the use of autonomous robots, cyber-physical systems, artificial intelligence algorithms, quantum computing and nanotechnologies are slowly changing the overall landscape and are pushing humanity towards the next wave of Industrial revolutions. While these innovations are offer significant benefits, they are also presenting a new set of challenges for the companies and their staff. In this paper we present and discuss the present trends, emerging solutions and future technologies in the area of the Industrial automation. The Introduction section of the paper provides a brief overview of the past and present Industrial revolutions and highlights the advantages and the disadvantages of their underlying technologies. The next chapter of the paper presents in more details the trending technologies and the solutions of the present-day Industrial automation domain. The paper continues with discussions about the emerging Industry 5.0 technologies and solutions. The next chapter of the manuscript is dedicated to

关键词： Industry 4.0

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Application of machine vision based foreign object recognition in conveyor protection

Application of machine vision based foreign object recogniti...

引用

2023 international conference on computer Graphics, Artificial Intelligence, and Data Processing, ICCAID 2023

作者： Yu, Zhiqiang Automation Co. Ltd. Changzhou Jiangsu China Middling Coal Science and Engineering Group Changzhou Research Institute Co. Ltd. Changzhou Jiangsu China

ISBN: (纸本)9781510677685

The current low level of intelligence in the main transportation process of coal mines, traditional protection devices can only passively shut down after accidents occur. Although they prevent further losses from expanding, they cannot provide early warning and fundamentally avoid accidents. This article designs a foreign object recognition system based on machine vision and applies it to the protection of the main transportation belt conveyor. Use YOLOv5s as the deep learning model, and deploy the trained model to the edge computing module. Real time video is captured by an industrial intrinsic safety camera and transmitted to the edge computing module to identify the foreign matters in the coal flow. Finally, only the recognition results are transmitted externally. When a high level of foreign object danger is detected, an alarm signal will be sent to the collaborative controller, which will issue a shutdown command to the specific single controller. Simultaneously upload the processed real-time video and alarm information to the control platform for display. This design improves the intelligence, stability, and reliability of the protection of the current main conveyor belt conveyor, achieving preventive measures. © 2024 SPIE.

关键词： computer vision

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Smart Street Lighting for Sustainable Urban Environments: Sensor-Based automation and Efficiency

Smart Street Lighting for Sustainable Urban Environments: Se...

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2024 IEEE international conference on Computing, Applications and Systems, COMPAS 2024

作者： Afrin, Sumaiya Abdi, Khalid Ferdows, Rubayea Ahmed, Fuad IUBAT-International University of Business Agriculture and Technology Dept of Computer Science and Engineering Bangladesh Dept of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798331529765

In recent times, many streetlights have been wasting energy by staying on unnecessarily during the evenings and nights. This not only harms the environment but also costs a lot of money. The goal of Smart Street Lighting is to stop this wasteful energy use and make better use of resources. While other researchers have worked on this issue, we have a specific aim: to create a smart street lighting system that only turns on when it's needed and turns off when it's not. To achieve this, we're using laser sensors, ZigBee wireless technology, and a powerful microprocessor. Our system identifies when there are vehicles on the road using sensors. It then turns on the streetlights only where they are needed. This saves energy by not lighting empty areas. We can control and monitor each streetlight remotely through ZigBee technology, and everything is connected to a computer that makes the streetlights work smarter. Our sensors are good at detecting objects and people with an accuracy of 89.87 percent. This innovation can reduce electricity consumption by 38.1 percent and cut lighting maintenance costs by 48 percent. © 2024 IEEE.

关键词： Zigbee

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Using FactoryML for Deployment of Machine Learning Models in Industrial Production 29

Using FactoryML for Deployment of Machine Learning Models in...

引用

29th IEEE international conference on Emerging Technologies and Factory automation, ETFA 2024

作者： Wewer, Christian Remi Mahapatra, Harshit Esterle, Lukas Larsen, Peter Gorm Aarhus University Department of Electrical and Computer Engineering Aarhus Denmark Alexandra Institute Aarhus Denmark

ISBN: (纸本)9798350361230

This paper presents the FactoryML framework that simplifies the deployment and integration of Machine Learning (ML) models in manufacturing factory environments. FactoryML facilitates packaging of ML models into a portable format and it facilitates the communication of deployed ML models in factory environments via Programmable Logic Controllers. In general FactoryML reduces the barrier to take learned models from a research and development side into an operational setting. The value of FactoryML has been demonstrated in a case study with a Danish company as well. © 2024 IEEE.

关键词： Adversarial machine learning

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Optimization of Neural Networks using Swarm Intelligence Techniques for Achieving Energy Efficiency in Smart Building Architecture 1

Optimization of Neural Networks using Swarm Intelligence Tec...

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1st IEEE international conference on Cognitive Robotics and Intelligent Systems, ICC - ROBINS 2024

作者： Raja, M. Karthick Shermatova, Makhbuba Al Ansari, Mohammed Saleh Abdufattokhov, Shokhjakhon Rao, Vuda Sreenivasa Raj, I. Infant Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India Turin Polytechnic University in Tashkent Civil Engineering and Architecture Department Tashkent Uzbekistan University of Bahrain College of Engineering Department of Chemical Engineering Bahrain Turin Polytechnic University Automatic Control and Computer Engineering Dept Italy Tashkent Intl. University of Education Dept of Information Technologies Tashkent Uzbekistan Koneru Lakshmaiah Education Fou. Green Fields Department of Computer Science and Engineering A.P Vaddeswaram522302 India K. Ramakrishnan College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy621 112 India

ISBN: (纸本)9798350372748

The increasing prevalence of smart building architectures, driven by the integration of Internet of Things (IoT) devices and automation systems, has led to a surge in energy consumption. This research explores the application of swarm intelligence techniques as an innovative approach to optimize neural networks, aiming to strike a balance between maintaining the desired performance levels and minimizing energy consumption. The study investigates the integration of swarm-based optimization algorithms, such as Particle Swarm Optimization (PSO) into the training and operation of neural networks. These algorithms enable the networks to dynamically adapt and optimize their parameters in response to changing environmental conditions and user requirements. The research focuses on developing a comprehensive framework that considers the specific challenges posed by smart building architectures, including real-time data processing, sensor integration, and adaptive control. The proposed approach aims to achieve optimal neural network configurations that minimize energy consumption while ensuring reliable and responsive operation of smart building systems. The results demonstrate the potential of swarm intelligence to significantly improve the energy efficiency of neural network-enabled smart building architectures, providing a promising avenue for sustainable and intelligent infrastructure. The proposed model has an accuracy of 98.23% which is 7.64% higher than that of the traditional approaches. © 2024 IEEE.

关键词： Energy efficiency

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Research on automatic thrower control based on brain-computer interface

Research on automatic thrower control based on brain-compute...

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2023 international conference on automation Control, Algorithm, and Intelligent Bionics, ACAIB 2023

作者： Sun, Hang Li, Changsheng Zhang, He Nanjing University of Science and Technology China

ISBN: (纸本)9781510667662

In order to explore the feasibility of brain-computer interface in the weapon system application, an experience of automatic thrower model controlled by brain-computer interface is designed to compete the firing task. According to the lens of automatic thrower model fed back from the screen, the testee carries out the practical or imaginary actions, and then through the nonintrusive BCI equipment, load 6 kinds of EGG signal which are collected from the testee to the trained convolutional neural network. 9 kinds of signal controlling the actions of automatic thrower model would be output. Control the switching functions of automatic thrower model through setting to realize 9 actions including Forward, backward, left, right, turret left, right, muzzle up, down, and launch, so as to complete the firing task. The comprehensive accuracy rate of implementation is 78.83%. The result of this experience shows that the brain-computer interface has the feasibility in the military field, which is worthy of researchers to carry out deeper studies. © 2023 SPIE.

关键词： Brain computer interface

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Dijkstra and A* algorithms in Automated Vehicle Driving

Dijkstra and A* algorithms in Automated Vehicle Driving

引用

2023 international conference on Mechatronic engineering and Artificial Intelligence, MEAI 2023

作者： Lin, Yingpeng Chang'an Dublin International Transportation College Chang'an University Xian China

ISBN: (纸本)9781510674608

Path planning technology is one of the current hotspots of research in many intelligent technology fields, which has a broad application prospect and research value. With the rapid improvement of computer arithmetic power and the widespread popularization of automation, automatic driving has gradually become a hot topic of people's attention. Among them, path planning algorithms play a central role in the field of automatic driving. In this paper, firstly, it will summarize and introduce the development history and basic principles of the two basic path algorithms, Dijkstra algorithm and A* algorithm, list the advantages and disadvantages of these two path planning methods based on graph search and the application scenarios, and then analyze and compare Dijkstra algorithm and A* algorithm, discuss their advantages and disadvantages in the field of intelligent driving, and finally make an outlook of future development directions of the path planning technology in the field of intelligent driving. The research in this paper will provide certain reference value to the researchers of path planning algorithms for intelligent vehicles. It will be of great value to the research and application of new path planning algorithms based on Dijkstra and A* algorithms in the future. © 2024 SPIE.

关键词： Motion planning

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Implementation of Fuzzy Logic Model to Solve Traffic Congestion Problem at Road Intersections

Implementation of Fuzzy Logic Model to Solve Traffic Congest...

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2024 IEEE international conference on automation and Computation, AUTOCOM 2024

作者： Negi, Vinay Jha, Sundaram Kumar Behl, Rachna Mriirs Dept. of Computer Science & Engineering Faridabad India

ISBN: (纸本)9798350382723

This research aims to tackle traffic congestion at intersections, primarily caused by static traffic light timings that don't adapt to changing traffic conditions. The proposed solution involves using adaptive fuzzy controllers, which can adjust their decisions based on fuzzy IF-THEN rules. These controllers employ both Mamdani and Sugeno fuzzy logic. The Mamdani method considers factors like the number of vehicles, queue length, emergency vehicle access, and road width to optimize traffic light timings and reduce unnecessary green signals. The Sugeno-type fuzzy logic enhances controller efficiency and decreases waiting times. The study also explores the application of direct adaptive fuzzy controllers to manage unstable systems, which is relevant in optimizing traffic control. Ultimately, the goal is to develop a simulator capable of predicting the right traffic light timings in real-time. This involves extending green light timings for lanes with high vehicle volumes and also for the emergency vehicles to alleviate congestion at intersections. © 2024 IEEE.

关键词： Traffic congestion

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Non-Volatile Memory Express (NVMe) Resource Pooling Mechanism Based on PCIe 4

Non-Volatile Memory Express (NVMe) Resource Pooling Mechanis...

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4th international conference on Electronic Information engineering and computer Communication, EIECC 2024

作者： Xu, Guoqiang Jiangsu Automation Research Institute Computer Department Lianyungang China Northwestern Polytechnical University School of Navigation Xi'an China

ISBN: (纸本)9798331534622

With the rapid development of big data and cloud computing technologies, the demand for storage system performance is constantly *** paper explores the PCIe-based NVMe resource pooling mechanism, aiming to improve the performance and scalability of modern data center storage systems. By designing a multi-node interconnection mechanism, the cross-node sharing and dynamic allocation of NVMe device resources are realized by using PCIe NTB card. Studies include virtual injection of remote devices, remote access to BARs, and interrupt message remapping to ensure that remote devices can be effectively recognized by the operating system. Tests showed that remote shared NVMe device performance was close to local devices, verifying the feasibility of the *** designed PCIe-based NVMe resource pooling and sharing mechanism is tested, and the final BW and IOPS performance results are analyzed, and the BW and IOPS performance of random read remote shared NVMe operation is 95% higher than that of local NVMe devices. The BW and IOPS performance of the Random Write remote shared NVMe operation is 90% higher than that of the local NVMe device. In the NVMe resource pooling and sharing mechanism, remote shared NVMe disks can be used instead of local NVMe disks. © 2024 IEEE.

关键词： Nonvolatile storage

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