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检索条件"任意字段=2023 3rd International Conference on Detection Technology and Intelligence System, DTIS 2023"

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Research on Adaptive Canny-based detection Method for Print Overprint Deviation 3

Research on Adaptive Canny-based Detection Method for Print ...

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

作者： Huang, Mengtao Shang, Guanghui College of Electrical and Control Engineering Xi'an University of Science and Technology Shaanxi Xi'an China

ISBN: (纸本)9781510663473

In order to improve the detection accuracy and efficiency of overprinting, an overprint deviation detection method is proposed for the characteristics of "concentric circles" overprint logo logos with fixed radius and line width. Firstly, the edges are divided into foreground and background by edge enhancement and center-of-mass comparison to select the appropriate high and low thresholds;the image edge information is extracted by Canny operator and the outline is filtered according to the radius of the circle in the logo logos;finally, the circle center is confirmed by the least squares method, and the distance between the two circle centers is the overprint deviation. deviation, and the pixel deviation is converted to physical deviation by the size of the camera calibration. Comparing the data obtained by this method with the known values, the average error of measurement is all less than 0.01mm, which meets the national regulations for overprint accuracy in the printing industry, and the detection time and detection efficiency can meet the real-time requirements. © 2023 SPIE.

关键词： Efficiency

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Improved I-Log-SCMA Algorithm for Low Complexity detection 3

Improved I-Log-SCMA Algorithm for Low Complexity Detection

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3rd international conference on Machine Learning and Computer Application, ICMLCA 2022

作者： Liu, Fang Li, Chang Liu, Jian School of Information Science and Engineering Shenyang Ligong University Shenyang China

ISBN: (纸本)9781510664814

SCMA (sparse code multiple access) is a kind of wireless Communication technology, which is used to process the uplink portion of wireless communication and ensure a high data transmission rate and massive data connection at the age of information technology. The urgent need for SCMA technology is to address the issue that the user capacity of SCMA technology couldn't be balanced with the complexity of the detection algorithm. As for solving this, an improved low-complexity detection algorithm I-log-MPA was analyzed, which is based on the modification of the traditional algorithm in multi-user detection. It made up for the solving of the bit error performance of MAX-log-MPA algorithm and the problem of high complexity. The simulation results revealed that the I-log-MPA detection algorithm with lower complexity and lower bit error rate could effectively improve the performance of SCMA system. © 2023 SPIE.

关键词： Bit error rate

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A Critical Analysis of Applying Computer Vision In Building an Intelligent system 3

A Critical Analysis of Applying Computer Vision In Building ...

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Ballari, Syed Omar Srinivas, Angalkuditi Gupta, Manish Dhobal, Kiran Akabarkhan, Pathan Shahnavajkhan Reddy, Dasari Veera Guru Nanak Institutions Technical Campus Department of Civil Engineering Telangana Ibrahimpatnam501506 India Koneru Lakshmaiah Education Foundation Department of CSE India Lovely Professional University Phagwara India Uttaranchal University Uttaranchal Institute of Technology India Sankalchand Patel University Shri C.J. Patel College of Computer Studies Faculty of Computer Science India SR University School of Computer Science and Artificial Intelligence Telangana Warangal India

ISBN: (纸本)9798350399264

The terminology "computer vision"refers to the method that leverages technologies of intelligent systems such as artificial intelligence (AI) to enable computers to gather useful information from visual sources. The automated activities are demonstrated previously using computer vision understanding. The definition, examples, as well as uses of computer vision, are covered in this article. For computer vision to be totally successful there must be a huge collection. When they lack the knowledge required to execute the task at hand, these systems periodically discover trends, which cause this to occur. Hence, the research has evaluated the notion of computer vision in diverse fields of operations through the literature review as well as in the analysis and discussion portion of the study. Since the literature review and data analysis of the research is done through secondary sources, an imperative notion of review has been gathered and presented. Therefore, the significance of computer vision in assembling intelligent systems like AI and other new technologies has given discussed in the research. © 2023 IEEE.

关键词： Intelligent systems

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A Complex Road Target detection Algorithm Based on YOLOv5n-SBF 3

A Complex Road Target Detection Algorithm Based on YOLOv5n-S...

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2023 3rd international conference on Big Data, Artificial intelligence and Risk Management, ICBAR 2023

作者： Lin, Guoyang Xu, Huarong School of Computer and Information Engineering Xiamen University of Technology Fujian Xiamen361024 China

ISBN: (纸本)9798400716478

Missed detection is usually caused by variations in target scales, dense occlusion, and uneven illumination. To tackle the challenge of missed detection in road target detection during complex environments, an enhanced approach called YOLOv5n-SBF based on YOLOv5n has been proposed. Specifically, YOLOv5n-SBF replaces the backbone network of YOLOv5n with Swin Transformer structure and fuses features extracted from Swin Transformer Block and neck network, effectively solving the problem of missing detection and improving the ability to extract features from small targets. Furthermore, we add the BiFormer attention mechanism to the neck of YOLOv5n to capture global and local features, improving the model's performance in visual tasks. Extensive experiments have been conducted on two real-world datasets. The experimental results demonstrate that YOLOv5n-SBF exhibits superior detection efficiency compared to baseline models, and achieves 5.7 percentage points and 18.2 percentage points in mAP@0.5 scores on the public datasets of KITTI and UA-DETRAC, respectively. © 2023 ACM.

关键词： Roads and streets

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Third international conference on Computer technology, Information Engineering, and Electron Materials, CTIEEM 2023

Third International Conference on Computer Technology, Infor...

引用

3rd international conference on Computer technology, Information Engineering, and Electron Materials, CTIEEM 2023

ISBN: (纸本)9781510672925

The proceedings contain 26 papers. The topics discussed include: a Stuxnet-style malware propagation modeling study based on Tesla autonomous vehicles;radar emitter recognition method based on kernel extreme learning machine optimized by sparrow search algorithm;analyzing fusion plasma diagnostic images based on computer vision and deep learning;research on trust mechanism in wireless sensor networks;YOLOv7-based attention and improved feature fusion small object detection algorithm;research on control of single-phase photovoltaic energy storage grid-connected inverter;a civil unmanned aircraft intelligent control system based on multi-source sensor;and construction of quantitative prediction model of metal mineral resources based on big data mining.

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Investigating the Benefits of Machine Learning Algorithms for Text Classification 3

Investigating the Benefits of Machine Learning Algorithms fo...

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

作者： Gowrishankar, J. Vinithra Banu, T. Parikshit, N. Singh, Vandana Kalra, Hitesh Sahoo, Girija Shankar Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Ramnagar562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350319125

This paper affords a research into using gadget studying algorithms for textual content category duties, with a focal point on understanding the importance of these algorithms and their ability to enhance the accuracy of textual content classification. it's miles located that, while conventional techniques, which include rule based models and hand-engineered features, can attain first-class outcomes, there are compelling motives to explore the capability of device getting to know algorithms to further improve the accuracy and performance of textual content class. The paper discusses the 3 maximum famous gadget gaining knowledge of algorithms for this project: the NaÏve Bayes classifier, help Vector Machines, and synthetic Neural Networks, and presents a top level view of the latest research findings that demonstrate the prevalence of these algorithms over traditional methods. The paper additionally presents an outline of the distinctive approaches for introducing era into text type, and discusses modern-day strategies for implementing and deploying those algorithms. Finally, the paper outlines ability areas for destiny research associated with information the results of system studying algorithms for this mission, and suggests viable instructions for exploration. © 2023 IEEE.

关键词： Classification (of information)

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AI Technological Interference in Court Proceedings: Right to Fair Trial Decision 3

AI Technological Interference in Court Proceedings: Right to...

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3rd international conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Kumar, Santosh Joshi, Kapil Singh, Sumeshwar Anandaram, Harishchander Sindhu, Kawerinder Singh Mahariya, Satish Kumar Kaushik, Vishal Sharda School of Basic Sciences and Research Sharda University Department of Mathematics UP Greater Noida India Uttaranchal Institute of Technology Uttaranchal University Department of Cse Dehradun India Graphic Era Hill University Department of Computer Science and Engineering Uttarakhand Dehradun India Amrita School of Artificial Intelligence Centre for Computational Engineering and Networking Coimbatore India Uttaranchal University Dehradun India Gsss Mahawa Neemkathana Rajasthan Sikar India School of Computer Science Upes India

ISBN: (纸本)9798350330724

The given study focuses on the influence of artificial intelligence (AI) on adjudicatory procedures mostly on observance of such right to an impartial trial in several law-related fields with respect to existing decisions. The consideration of such substance of the right to an impartial trial serves as the beginning stage for the debate, with a special focus on the autonomy and impartiality of the judiciary. Following that, the article analyses the prospect of minimizing the individual role in court processes in charge of making decisions using information technologies. This paper analyses the admissibility of using AI tools in the judiciary and contains considerations on ethical aspects of AI application in judicial proceedings and whether an AI system can take over the role of a decision-maker in judicial proceedings, thereby replacing or supporting the judge. The paper with a view of its legal compliance, non-discrimination, transparency, and efficiency of legal proceedings. The study employs the method of analyzing the law in force and investigating theories of law, taking into account the critical analysis of the literature at the decision level. © 2023 IEEE.

关键词： Decision making

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State of Art of School Education in Rural Areas of Yavatmal District in the State of Maharashtra in India Based on a Real Survey 3

State of Art of School Education in Rural Areas of Yavatmal ...

引用

3rd international conference on Innovative Sustainable Computational Technologies, CISCT 2023

作者： Batghare, Kalpana Dixit, Anil Kumar Memoria, Minakshi Saxena, Sager Bilgaye, Manish Law College Dehradun Research Scholar Uttaranchal University Dehradun India Law College Dehradun Faculty of Uttaranchal University Dehradun India Uttaranchal Institute of Technology Faculty of Uttaranchal University Dehradun India SRH Berlin University of Applied Sciences Mechatronics and IT Department Berlin Germany

ISBN: (纸本)9798350303360

The paper aims to present the real current situation of the state of education being provided by various schools in rural areas of the central Indian district of Yavatmal in the state of Maharashtra situated in India. Also, the paper is an attempt to analyze the data using simple analytical tools from an artificial intelligence perspective to predict various parameters indicating the future shape and direction of education is going to in these rural parts of mainland India. The study is based on real survey data collected by visiting numerous schools after receiving written permission from the Block Development Officer of Tehsil Yavatmal. The initial emphasis was on girl education but has been generalized to boys as well because of the coeducation system. The process involved talks on the state of the art of education and collection of data from respective heads of the school followed by interviews with schoolteachers, nonteaching staff, and students. The study is represented in the form of graphs, inferences, and observations on the complicated way ahead, for education to reach these deprived large chunks of people, who think that their future is their children and education is the only key responsible for new light to come to their lives. The paper includes the developmental stages Indian education passed through from pre-independence to recent times. © 2023 IEEE.

关键词： Artificial intelligence

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An Intelligent defect detection method in solar cells via IDATLGAN 3

An Intelligent defect detection method in solar cells via ID...

引用

3rd international conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2023

作者： Pang, Bo Bu, Henan Hu, Changzhou School of Mechanical Engineering Jiangsu University of Science and Technology Jiangsu Zhenjiang212100 China

ISBN: (数字)9781510667617

ISBN: (纸本)9781510667600

Intelligent defect detection is a key section of the PDCA comprehensive quality management in the solar cells production. deep learning-based models for its powerful capacity of extracting features has successfully applied to defect detection tasks. Nevertheless, the deep learning-based models is susceptible to these problems such as insufficient labelled data and class imbalance, which deteriorates the performance of the deep models. What's worse, the new unknown defects without labels in the target domain tend to be recognized as the unknown defects in the source domain. To solve these problems, a novel method named IDATLGAN is proposed. Experimental results show that the proposed model outperforms the DCNN model in feature extraction ability and fulfil the transfer tasks even when faced with new unknown defects without labels. © 2023 SPIE.

关键词： Solar cells

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Study on Improved YOLOv7-based Algorithm for Detecting Crack Defects in Ancient Buildings 24

Study on Improved YOLOv7-based Algorithm for Detecting Crack...

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3rd international conference on Computer, Artificial intelligence and Control Engineering, CAICE 2024

作者： Fang, Tianke Hui, Zhenxing Rey, William P Xie, Zhiying Yang, Aihua He, Yuanrong School of Information Technology Mapua University Manila1200 Philippines Big Data Institute of Digital Natural Disaster Monitoring in Fujian Xiamen University of Technology Xiamen Fujian361024 China School of Computing and Information Engineering Xiamen University of Technology Xiamen Fujian361024 China School of Information Media Zhangzhou Vocational College of Science and Technology Zhangzhou Fujian363200 China Hunan Key Laboratory of Remote Sensing Monitoring of Ecological Environment Dongting Lake Area Changsha Hunan410004 China

ISBN: (纸本)9798400716942

In the protection and restoration work of ancient buildings, the detection and analysis of the cracks and defects of the exterior walls of ancient buildings is a crucial task. In this paper, an improved YOLOv7 algorithm is proposed to detect the defects of ancient external walls, aiming to achieve efficient and accurate detection of the defects of ancient external walls. The method involves preprocessing the image using a rectangle clipping algorithm, graying the image using the maximum method, and denoising the image with a median filter. Next, the image is labeled using the LabelImg tool, and the data is split into training, validation, and test sets. During model training, a CBAM-Net module is inserted after several CBS modules in the backbone network, the GIOU loss function is replaced by CIOU, and feature task extraction is performed. The realized attention mechanism is added to the Yolov7 model. The results show that the mAP value of crack detection after the improved algorithm reaches 81.2%. In contrast to the initial YOLOv7 algorithm, the precision of the model has been boosted to 87.2%, exhibiting a 6.0% enhancement in accuracy and an 85.2% improvement in recall rate. The improved YOLOv7 crack detection algorithm reduces network calculation and improves crack classification and recognition ability. This approach is crucial in safeguarding ancient buildings as it enables varying levels of maintenance depending on the severity of cracks. © 2024 ACM.

关键词： Attention mechanism Deep learning Defect detection Image processing YOLOv7

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