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A study on license plate recognition based on convolutional neural network 3

A study on license plate recognition based on convolutional ...

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3rd international conference on Computer Vision and Data Mining, ICCVDM 2022

作者： Shi, Xiangui Wang, Xiaole Chen, Tao Qian, Cong Liu, Yiming School of Big Data and Artificial Intelligence Anhui Xinhua University Hefei230088 China College of Computing and Information Technologies National University Manila Philippines

ISBN: (纸本)9781510661363

With the rapid development of advanced technologies such as artificial intelligence and Internet of Things, intelligent traffic management has been widely used. License plate recognition technology is particularly important in intelligent traffic management as the unique identification of vehicles, but due to the influence of natural environment, recognition angle, image clarity, size of license plate and other factors, the traditional license plate recognition technology is less robust and difficult to accurately identify the number plate number. In this paper, we describe a license plate recognition technique implemented by constructing Convolutional Neural Networks (CNN), which is able to recognize license plate numbers more accurately and has certain significance for further research on deep learning in the field of intelligent traffic management. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Image processing

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Facilitating Human Feedback for GenAI Prompt Optimization 3

Facilitating Human Feedback for GenAI Prompt Optimization

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3rd international conference on Hybrid Human-Artificial intelligence, HHAI 2024

作者： Sherson, Jacob Vinchon, Florent Center for Hybrid Intelligence Dep. of Management Aarhus University Denmark Université Paris-Cité and Gustave Eiffel LAPEA F-92100 France

ISBN: (纸本)9781643685229

This study investigates the optimization of Generative AI (GenAI) systems through human feedback, focusing on how varying feedback mechanisms influence the quality of GenAI outputs. We devised a Human-AI training loop where 32 students, divided into two groups, evaluated AI-generated responses based on a single prompt. One group assessed a single output, while the other compared two outputs. Preliminary results from this small-scale experiment suggest that comparative feedback might encourage more nuanced evaluations, highlighting the potential for improved human-AI collaboration in prompt optimization. Future research with larger samples is recommended to validate these findings and further explore effective feedback strategies for GenAI systems. © 2024 The Authors.

关键词： machine learning

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Partial Discharge pattern recognition of 10kV XLPE Cable Defects Based on VMD and GA-BP 3

Partial Discharge Pattern Recognition of 10kV XLPE Cable Def...

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3rd international Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2023

作者： Qin, Chunxu Zhu, Pengfei Liu, Liqiang Xue, Yunpeng Shang, Jiafeng Huang, Yongxiang Engineering Research Center of Large Energy Storage Technology Ministry of Education Inner Mongol University of Technology Hohhot010051 China

The study of cable partial discharge pattern recognition is of great importance for the stability of power cables. In the high voltage laboratory, a platform was established to test partial discharge signals of 10kV XLPE cable, such as metal impurities, water infiltration of main insulation, and scratches of main insulation, utilizing the high frequency current method. The entropy value of each modal component were studied by using variation modal decomposition for the collected PD *** quantities such as the power spectral entropy mean, fuzzy entropy mean, sample entropy mean of each modal component, and IMF1's fuzzy entropy value were chosen. To optimize the back propagation neural network algorithm for partial discharge pattern recognition, a genetic algorithm was employed. © The Institution of Engineering & Technology 2023.

关键词： Partial discharges

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Artificial intelligence Technique for Rice Seed Disease and Quality Assessment 3

Artificial Intelligence Technique for Rice Seed Disease and ...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Hassan, B. Nazia Somashekara, M.T. Government First Grade College Vijayanagar Department of Computer Science Karnataka Vijayanagar India Bangalore University Department of Computer Science and Applications Karnataka Bangalore India

ISBN: (纸本)9798350319125

Ensuring high-quality rice seeds is vital for agricultural productivity. This research explores existing methods for assessing rice seed quality, land suitability, and seed disease in rice. A survey of the literature reveals a diverse range of techniques used for these purposes. In particular, this study delves into the application of machine learning (ML) classifiers and deep learning (DL) techniques for assessing the rice seed quality. This paper, exhaustively covers all major work based on ML and DL techniques. Through extensive analysis, the research assesses these methods in terms of accuracy, precision, recall, F1-score, error rates, and the kappa coefficient. The results demonstrate that both ML and DL exhibit superior performance, showcasing their potential for enhancing rice seed quality assessment and disease detection. This research contributes valuable insights into the application of advanced technologies in agriculture, with implications for improving crop yield and food security. This paper serves as aid for researchers working in this area. © 2023 IEEE.

关键词： Computer Vision Deep Learning machine Learning Rice Seed Quality

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Artificial intelligence of Patients Management for Injured Patient and Robotic assisted Physiotherapy Rehabilitation 3

Artificial Intelligence of Patients Management for Injured P...

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3rd international conference for Innovation in Technology, INOCON 2024

作者： Padmaavathy, P.A. Thilagavathi, J. Selvi, K. Ramachandran, G. Kumar, G. Suresh Reddy, D.V. Lokeswar Justin, B.V. Febiyola Karpagam Academy of Higher Education Department of Management Coimbatore India Arjun College of Technology Department of Ai & Ds Coimbatore India Department of Management Studies Chennai77 India Ece Vinayaka Mission's Kirupananda Variyar Engineering College Salem India Andhra Pradesh Pulivendula516390 India St. Peter's Institute of Higher Education and Research Department of Biochemistry Avadi Chennai600054 India

ISBN: (纸本)9798350381931

It has been observed that technology has shown to be extremely helpful in the healthcare industry. Numerous apps that facilitate patient and physician lives are being developed. Artificial intelligence, machine learning, and virtual reality are among the most widely used technology in therapeutic applications. With the help of apps like this medical technology, health professionals are acquiring the tools they need to give patients in need the kind of care and assistance they need. Additionally, it lessens the burdens of clinicians and provides the ability to manage more customers than before. As injury care, physical strength, body functionality, and total body activity have improved in recent decades along with engagement in body movement research as opposed to drug use and surgery the necessity for physical therapy has increased. Along with the necessity for rehab centers and physiotherapists, the surge in physical activity has increased the requirement for physiotherapy. Physiotherapists now have a helpful workload aid in the form of medical technology. Smart workouts are dependable and inspiring activities that lower the risk of injury and strengthen the muscle-bone system. Unconscious movements have the potential to injure a person's body or impede the growth of exercise. The goal of this study is to examine both orthopedic patients and athletes. The primary focus is performing the exercise correctly according to the specified plan within the constraints of the individual, thanks to the designed algorithm and equipment. The system notifies a user when they complete the necessary movement to the desired degree while wearing an elbow or knee brace, depending on the intended application and the program designed by a doctor or trainer. © 2024 IEEE.

关键词： Robotics

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Optimizing Resource Management and Data Security in Cloud Computing Environments 3

Optimizing Resource Management and Data Security in Cloud Co...

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3rd international conference for Advancement in Technology, ICONAT 2024

作者： Shri, S.Jothi Karthiyayini, G. Vignesh, L.S. Upender, Talluri Shobana, D. Patra, Ladi Sandip Kumar Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Ramco Institute of Technology Department of CSE Tamil Nadu Rajapalayam India Nadar Saraswathi College of Engineering and Technology Department of Artificial Intelligence and Data Science Theni India CMR College of Engineering and Technology Medchal Department of CSE Telangana Hyderabad India Rajalakshmi Engineering College Department of Mechatronics Engineering Chennai India MLR Institute of Technology Department of ECE Hyderabad India

ISBN: (纸本)9798350354171

The quick uptake of cloud computing has completely changed how companies run since it offers flexible and scalable resources that promote productivity and creativity. However, the dynamic and complex nature of cloud environments presents significant challenges in optimizing resource management and ensuring robust data security. This paper investigates advanced strategies and methodologies for enhancing resource allocation, virtualization, and scheduling to maximize performance and cost-efficiency in cloud infrastructures. Key techniques explored include dynamic scaling, load balancing, VM migration, containerization, and cost-effective resource usage through spot and reserved instances. The important facets of cloud computing data security, such as encryption, identity and access management (IAM), data loss prevention (DLP), and intrusion detection and prevention systems (IDPS), are also covered in tandem by this research. The study offers novel approaches for reducing security threats and guaranteeing data integrity by fusing cutting-edge technology like blockchain and machine intelligence. The comprehensive analysis aims to provide actionable insights and practical recommendations for IT professionals and organizations striving to optimize their cloud computing operations. By balancing resource management efficiency with stringent security measures, this research contributes to the development of a more secure and efficient cloud ecosystem. The results emphasise the significance of a comprehensive strategy for managing cloud systems, where data security and performance optimisation work together to provide durable and sustainable cloud computing environments. © 2024 IEEE.

关键词： Cloud security

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Robust Phishing URL Classification Using FastText Character Embeddings and Hybrid Deep Learning 3

Robust Phishing URL Classification Using FastText Character ...

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3rd IEEE international conference on Robotics, Automation, Artificial-intelligence and Internet-of-Things, RAAICON 2024

作者： Al-Sakib, Abdullah Limon, Zishad Hossain Sakib, Anamul Pranto, Md Nuruzzaman Islam, Md Ariful Sultana, Shayma Ahmed, Md. Redwan Rahman, Shafiur Westcliff University Dept. of Information Technology CA92614 United States Westcliff University Dept. of Computer Science CA92614 United States International American University Dept. of Business Administration CA90010 United States International American University Dept. of Management Information System CA90010 United States East West University Dept. of Computer Science and Engineering Dhaka1212 Bangladesh Daffodil International University Dept. of Software Engineering Dhaka1216 Bangladesh

ISBN: (纸本)9798331534400

Phishing attacks are a major cybersecurity threat that resulted in over 1.2 million incidents in the first half of 2020. These attacks caused substantial financial losses and posed risks to individuals and organizations. Being able to identify fraudulent websites is crucial in order to effectively address these potential risks. This study introduces a novel method for detecting phishing URLs by using word and character embeddings to capture complex URL patterns. We used a dataset of 80,000 URLs, including 50,000 legitimate ones and 30,000 phishing instances, and applied thorough preprocessing techniques. We utilized word embeddings in FastText to handle unseen words, with the added advantage of n-gram representations. Additionally, we captured character-level features through dense character embeddings. We trained several machine learning and deep learning models, and one model, the Convolutional Bidirectional LSTM (CBiLSTM), stood out with an accuracy of 99.01% and an F1-score of 99.08%. Furthermore, we made a thorough comparison with the most advanced techniques available, and our findings demonstrated clear superiority over previous research. This study presents an effective approach for classifying phishing URLs, providing a valuable tool to combat fraud and protect against identity theft, thereby helping to minimize the financial and emotional harm experienced by victims. © 2024 IEEE.

关键词： Phishing

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Research on the Construction of Visual Virtual Reality Platform for Chinese pattern Design 3

Research on the Construction of Visual Virtual Reality Platf...

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3rd international conference on Artificial intelligence and Computer Engineering, ICAICE 2022

作者： Gao, Pin Bian, Hongming Bao, Ying Department of Artistic Design Shenyang Jianzhu University Shenyang China

ISBN: (纸本)9781510663473

Chinese pattern design has not only witnessed the history of more than 5,000 years in China, but also impacted the aesthetic cognition of the East in the West. Chinese patterns have been beautiful since ancient times. In the past, it was created by the wisdom and hard work of the Chinese people, and now it should be inherited by the wisdom and hard work of the Chinese people. For the visualization platform of Chinese pattern design, better construction and improvement are needed. Therefore, in order to visualize information and achieve better results, if the memory occupancy is too high, the operation effect of the platform will be reduced. In order to improve the operation effect of the visualization platform, the construction of visual virtual reality platform of Chinese pattern design is proposed. Based on B/S mode, the software structure is established, and specific analysis is carried out, and the functional plate and visual effect design are improved. Through hardware and software design, the visual virtual reality platform of Chinese pattern design is constructed. © 2023 SPIE.

关键词： Virtual reality

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3rd international conference on Applied Mathematics, Modeling and Computer Simulation, AMMCS 2023

作者： Liu, Zhe School of Computer Sciences Universiti Sains Malaysia Penang11800 Malaysia

ISBN: (纸本)9781643684581

Pythagorean fuzzy sets (PFSs) are a versatile tool for handling uncertain problems and have proven effective in practical applications. However, many existing Pythagorean fuzzy similarity measures have counter-intuitive situations, making it challenging to measure the similarity or difference between PFSs accurately. To address this issue, we propose two similarity measures for PFSs inspired by the Tanimoto similarity measure. We also explore the properties of the proposed measures and provide several numerical examples to illustrate their superior performance in processing fuzzy information from PFSs. Finally, we demonstrate the applicability of the proposed measures in solving pattern recognition problem. © 2023 The Authors.

关键词： Fuzzy sets

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Artificial intelligence video production platform based on user experience perspective 3

Artificial intelligence video production platform based on u...

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3rd international conference on machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT2023

作者： Liang, Dan Changchun Institute of Technology Jilin Changchun130000 China

From the perspective of user experience, the artificial intelligence video production platform has received widespread attention. The platform can provide video producers with many intelligent services, improving video production efficiency and quality. In this study, the basic concepts of the artificial intelligence video production platform were analyzed, and then from the perspective of user experience, the implementation method of the platform was proposed. Finally, the platform was tested. Through research, an artificial intelligence video production platform has been implemented, and the videos produced by the platform basically match the user's needs, so it can bring a good experience to the user. © 2023 The Authors. Published by Elsevier B.V.

关键词： Artificial intelligence

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