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Research on Traditional Art Image Reconstruction Method Based on computer Vision Analysis 2

Research on Traditional Art Image Reconstruction Method Base...

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2nd IEEE international conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Supriya, M. Anvesh, Kuncham Muruganandham, B. Manasa Krishnan, K. Muthu, R. Murugan, K. Kpr Institute of Engineering and Technology Department of Ece India

ISBN: (纸本)9798350369960

In the framework of the digital era, the technology of image processing is one of the technologies that is being used increasingly often in all aspects of modern life. Image correction may be handled using algorithms based on computer vision, which can increase the correction's influence on the image as a whole. The conventional method of identifying structural systems collects data via the use of wired or wireless measuring systems. The process of establishing sensors and the equipment used for data collection is laborious and takes a lot of time. The process has two stages: the first is the extraction of the line drawing, and the second is the rendering of the line drawing. An edge detection approach that integrates low-level and middle-level visual information is used to extract the line drawing in the process of on-line drawing extraction. This method is used to extract the drawing. The edges are then simplified and linked in accordance with the computer vision theory. Additionally, the image processing technology is used as the research object in order to develop a scientific model for the distorted image. These steps are based on the findings of traditional edge detection. Image restoration can be helped along by filtering samples of the image and getting rid of any noise that is there. The fundamentals of computer vision and the technologies that are connected to it are broken down in detail, and the behavioral patterns of visual interaction are investigated. The image of Chinese traditional art serves both the role of art communication and as a medium and symbol for cultural communication. At the same time, it carries on the legacy of a fine traditional culture that has been passed down from generation to generation in China. The image processing technology that is based on computer vision algorithms provides a bigger number of benefits, in addition to a better degree of accuracy. © 2023 IEEE.

关键词： computer Vision feedback Image reconstruction Traditional art Visual analysis

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Comparative Analysis and Enhancement of FPGA and ASIC Performance in Targeted applications 2nd

Comparative Analysis and Enhancement of FPGA and ASIC Perfor...

引用

2nd international conference on Artificial Intelligence and Communication Technologies, ICAICT 2024

作者： Lou, Haozhe School of Integrated Circuits Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9789819600953

Within the disciplines of electronic engineering and computer science, the quest for cutting-edge integrated circuit design has become more acute, reflecting the burgeoning need for high-performance computing solutions. This investigation delves into the comparative analysis of field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs), scrutinizing their performance across a spectrum of application environments. The core of this study lies in discerning the contrasts between the two technologies in terms of design adaptability, operational velocity, energy conservation, and economic viability, alongside their consequent ramifications on practical applications. A hybrid research methodology is adopted, weaving together theoretical exposition with empirical investigations, including the application of performance evaluation models and the examination of real-world industrial case studies. Findings from the study reveal that FPGAs boast superior adaptability in design and lower costs in the initial phase of development. Such attributes render them particularly advantageous for scenarios that necessitate swift product evolution and are limited to small-scale manufacturing. Conversely, ASICs exhibit enhanced capabilities in executing intricate tasks, most notably in the realms of large-scale data computation and sophisticated graphics processing. Moreover, the paper ventures into strategies for amplifying the energy efficiency of FPGAs, considering advancements in development tools and microarchitectural refinements. The conclusive insights of the research articulate that FPGAs and ASICs each possess distinct operational domains and strengths. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： FPGA and ASIC Performance comparison Technical optimization

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Advancements in Image Synthesis with Progressive Generative Adversarial Networks

Advancements in Image Synthesis with Progressive Generative ...

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Computational Intelligence, Communication Technology and Networking (CICTN), international conference on

作者： Ajay Pal Singh Nirmalya Basu Parvez Rahi Bhawana Goyal Bharti Vikas Yadav Dept. of Computer Sc. and Engineering UIE Chandigarh University Mohali Punjab India Unnao Department of Technical Education Government Polytechnic Bighapur Uttar Praddesh India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

An overview of the use of Generative Adversarial Networks (GANs) in computer vision—image synthesis and manipulation—is given in this study. A generator and a discriminator are two complex neural networks that are trained in competition to form GANs. Owing to the formidable capabilities of deep neural networks and their adversarial training approach, GANs exhibit the ability to generate realistic and plausible images, thereby demonstrating remarkable prowess across various applications in the realm of image synthesis and manipulation. This survey paper delves into recent GAN-related research. Working on the progressive GANs model technique, the authors find out how capable it is compared to other GANs algorithms. Building an image synthesis Progressive Generative Adversarial Networks (ProGANs) is a complex process with several steps that work together to produce high-quality pictures.

关键词： Training Surveys computer vision Image synthesis Computational modeling computer graphics computer architecture Generative adversarial networks Generators Context modeling

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A Component-Based Event-Driven Architecture Design for Autonomous Flying Software

A Component-Based Event-Driven Architecture Design for Auton...

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Image Processing and computer applications (ICIPCA), IEEE international conference on

作者： Jianhua Wang Zhongze Zhou Haixin Yu Jingsong Li Chuan Li Qun Wang Software Department Beijing Institute of Control Engineering Beijing China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

Some satellites are designed to be capable of autonomous flight in order to be intelligent. However, many autonomous flight tasks need to be designed because of the complexity of satellite system, which brings heavy software development workload. A component-based event-driven architecture is proposed in this paper, which exacts software components from the complex system for reuse, and designs basic events for the event-driven architecture. This method simplifies the software development logic and significantly improves the development efficiency of autonomous flight software.

关键词： Satellites Image processing computer architecture computer applications Software Complexity theory Logic Complex systems Software development management

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Crack Detection on Brick Walls by Convolutional Neural Networks Using the Methods of Sub-dataset Generation and Matching 1

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1st international conference and 2nd international conference on Deep Learning theory and applications, DeLTA 2020 and DeLTA 2021

作者： Talukder, Mehedi Hasan Ota, Shuhei Takanokura, Masato Ishii, Nobuaki Department of Computer Science and Engineering Faculty of Engineering Mawlana Bhashani Science and Technology University Tangail Bangladesh Department of Industrial Engineering and Management Faculty of Engineering Kanagawa University Yokohama Japan

ISBN: (数字)9783031373206

ISBN: (纸本)9783031373190

The appearance of cracks is considered an initial sign of the deterioration of structures such as concrete and brick walls. Crack detection plays an important role in ensuring the safety and durability of structures. Conventionally, a maintenance engineer performs crack detection manually, which is laborious and time-consuming. Therefore, a systematic crack detection method is required. Among the existing crack detection methods, convolutional neural networks (CNNs) are more effective;however, CNNs often fail in the case of brick walls. There are several types of bricks, and some may appear to have cracks owing to their structure. Additionally, the joining points of bricks may appear as cracks;therefore, CNN fails. It is theorized that CNN performance can be improved if sub-datasets are generated based on the image attributes, and a proper sub-dataset is selected by matching the test image with the sub-datasets. In this study, sub-dataset generation and matching methods are proposed to improve the performance of crack detection in brick walls using CNN. CNN training is conducted with each sub-dataset generated by the proposed sub-dataset generation method, while crack detection is performed using a proper trained CNN that is selected using the proposed matching method. For numerical experiments, training datasets are first prepared by manual image cropping and rotation, after which the performance of crack detection is evaluated by cross-validation. Numerical experiments show that the proposed method improves crack detection in brick walls. This study will help to ensure the safety of structures as well as the safety of human life. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Crack detection

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DMB Video Quality Enhancement Using Header Syntax Repair 32

DMB Video Quality Enhancement Using Header Syntax Repair

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32nd international Telecommunication Networks and applications conference (ITNAC)

作者： Zepernick, Hans-Jurgen Iqbal, Muhammad Imran Khatibi, Siamak Duong, Trung Q. Jamil, Momin Esslinger, Rolf Blekinge Inst Technol S-37179 Karlskrona Sweden Queens Univ Belfast Belfast BT7 1NN Antrim North Ireland Axis Commun AB S-22369 Lund Sweden Harman Becker Automot Syst GmbH D-76307 Karlsbad Germany

ISBN: (纸本)9781665471039

This paper studies a header syntax repair approach for quality enhancement of digital video broadcasting (DMB) videos. A sensitivity analysis of the impact of transmission errors in different parts of the header of the underlying MPEG-2 transport stream packets on DMB video quality is provided. On this basis, a header syntax repair approach is presented using header masks and bounded minimum distance decoding of the headers of the received DMB packets. Objective and subjective quality assessment show a tremendous improvement in the quality of the header syntax repaired DMB video clips. The concepts of the header syntax repair approach proposed for packets of DMB video streams may also be adapted to the syntax of packet formats of other digital video standards.

关键词： computer graphics

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Application of Score Algorithm in Astronomy 2

Application of Score Algorithm in Astronomy

引用

2nd international conference on Applied Mathematics, Modeling and computer Simulation, AMMCS 2022

作者： Cai, Hongbing Fang, Hang Tian, Jiayi Xu, Jinsong Jiangsu Normal University Xuzhou221116 China

ISBN: (纸本)9781643683522

Since the seventeenth century, there have been many mathematicians to study the score algorithm. Until today, it is still a topic worth of studying. The theory of the fraction algorithm has an important role in mathematics, which is an important tool in the study of the number theory and linear equations. The fraction algorithm is associated with probability theory, progression recursion, function approximation, engineering technology, and computer science. The fraction algorithm has some classic applications, such as using the fraction algorithm to solve the indefinite form of first order equation, calculating the ancient calendar with the fraction algorithm, and using the score algorithm for password analysis. This paper mainly discusses the history, definition, nature, and specific applications of the fraction algorithm in astronomy. Although the systematic induction and arrangement about the concept of continued fraction is all from the West, the ancient Chinese scientists had grasped this mathematical method and already applied it to production practices such as calendar and solar terms. This article summarizes these astronomical achievements, and it also poses a look at the application of the continued fraction in modern society. © 2022 The authors and IOS Press.

关键词： Number theory

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Sentiment Analysis of Social Media Data using Fuzzy-Rough Set Classifier for the Prediction of the Presidential Election 2

Sentiment Analysis of Social Media Data using Fuzzy-Rough Se...

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2nd international conference on Advanced Research in Computing, ICARC 2022

作者： Perera, Suresha Karunanayaka, Kasun University of Moratuwa Department of Computer Science and Engineering Katubedda Sri Lanka University of Colombo School of Computing University of Colombo 7 Colombo Sri Lanka

ISBN: (纸本)9781665407410

As an interdisciplinary research field, sentiment analysis is one of the momentous applications in Natural Language Processing, for quantifying the emotional value in vast data in the form of text available in social media networks to gain an understanding of the attitudes, opinions, and emotions expressed. There is a great deal of literature on the various approaches to address sentiment analysis with social media and this research focuses on Machine Learning techniques with Twitter data analysis. Special attention is drawn towards the classifiers based on the Fuzzy Set and Rough Set approach which are two powerful mathematical components of computational intelligence with its new dimension involved in the field of sentiment analysis. However, there is a minimal number of review papers discussing rough-fuzzy classifier involvement in sentiment analysis and there is a plethora of work that must be done with text mining in natural language processing. The mission of this study is to develop a sentiment-based classifier using machine learning and fuzzy-rough set theory. Further, it carries automatic sentiment classification with Twitter corpus collected during September 1st and November 15th, 2019 (two months before the election) regarding the case study for the prediction of results at the presidential election 2019, Sri Lanka. The fuzzy rough classifier is developed using the Fuzzy Rough Nearest Neighbor algorithm. The accuracy of the fuzzy rough set-based classifier is higher compared to other classifiers. The actual results of the presidential election of 2019 are tally with the predicted results of the classifier. Therefore, the current state of the art for the prediction of political sentiment with microblogging is probable with the social media data as witnessed with this case study and this can be used in other cases as well. © 2022 IEEE.

关键词： Fuzzy sets

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Race Swing Prediction and Importance Analysis Based on LSTM Recurrent Neural Network and Random Forest Algorithm

Race Swing Prediction and Importance Analysis Based on LSTM ...

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Image Processing and computer applications (ICIPCA), IEEE international conference on

作者： Haorui Tan Maynooth International Engineering College Fuzhou University Fuzhou China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

Contest swings are influenced by multiple and complex factors, which makes accurate prediction a challenging task. This study aims to utilize the advanced LSTM recurrent neural network with the random forest algorithm to make predictions of race swings and analyze the related important factors in depth. The experimental results show that the LSTM recurrent neural network can effectively capture the swings occurring in the contest and the high accuracy of the model is confirmed through relevant metrics. In addition, the analytical results of the random forest model not only determine the importance of each factor to the fluctuation of the competition but also propose corresponding coping strategies, which provide an important reference basis for further coping with the fluctuation. These findings provide important empirical support for a deeper understanding of the complexity of race swings and the development of effects.

关键词： Measurement Recurrent neural networks Accuracy Fluctuations Image processing Forestry computer applications Prediction algorithms Complexity theory Long short term memory

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Acceptance of Chatbot based on Emotional Intelligence through Machine Learning Algorithm 2

Acceptance of Chatbot based on Emotional Intelligence throug...

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2nd international conference on Frontiers of Electronics, Information and Computation Technologies, ICFEICT 2022

作者： Rokaya, Akter Md Touhidul Islam, Shuvo Zhang, Haotian Sun, Liming Zhu, Ming Zhao, Lianjun School of Computer Science and Technology Shandong University of Technology Zibo China

ISBN: (数字)9781665454766

ISBN: (纸本)9781665454766

In Artificial Intelligence, machine learning involves analyzing data and algorithms to improve accuracy and make human life more comfortable. In recent years, Artificial Intelligence strategies have been successfully applied to a wide range of educational purposes, including chatbots. Chatbot is an Artificial Intelligence tool that helps to improve academic strategies through its automated and intelligent features which enable the educational industry to develop students' learning abilities. Hence, the current study's goal is to combine the technology acceptance model (TAM) and emotional intelligence (EI) theory to evaluate the elements influencing the adoption of chatbot applications by implementing the proposed theoretical model. The qualitative result was evaluated through a questionnaire survey and data was collected from international students who have already experienced using chatbot applications in their university. Here, to examine the data and comprehend the relationship between the study models, machine learning method was used. After the investigation, according to the study's findings, Simple Logistic, Iterative Classifier Optimizer, and LMT classification classifiers had higher accuracy in predicting users' intention to use chatbots than 97.95% of the other classification classifiers. It is believed that the findings of the research will provide direction for students to promote chatbots better within educational activities in the future. © 2022 IEEE.

关键词： Iterative methods

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