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Application of Intelligent image recognition and Digital Media Art in the Inheritance of Black Pottery Intangible Cultural Heritage

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ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING 2024年第6期23卷 1-15页

作者： Yin, Jie Dezhou Univ Fine Arts Coll Dezhou 253023 Shandong Peoples R China

With the development of science and technology, intelligent image recognition and digital media art are gradually applied to the inheritance of intangible cultural heritage. In the inheritance of black pottery, intelligent image recognition can help identify the authenticity and age of black pottery, and digital media art can inject new vitality into black pottery culture. Digital media, which combines digitalization and mediaization, breaks down the limitations of traditional media and provides ideological and technical guarantees for the reconstruction, dissemination, and promotion of intangible cultural heritage protection. image recognition technology is no longer limited to the auxiliary detection of images;on the contrary, it has become a recording and collection tool. With the promotion and development of science and technology, it can be more widely shared and disseminated in time and space. In this article, the traditional machine learning algorithm and the intelligent learning algorithm are compared in image recognition, and the image information recognition rate, the number of iterations, the training time, and the information loss rate are compared in four aspects. The results have found that, compared with the traditional learning algorithm, the number of iterations of the intelligent learning algorithm is reduced by 20%, the training time is reduced by 40%, the information loss rate is reduced by 6.3%, and the recognition accuracy rate is improved by 6.1%, which showed that under the current technology, intangible cultural heritage can be better inherited, and Chinese culture can be better promoted, so that more people can understand and join in the protection of intangible cultural heritage.

关键词： Cultural heritage intangible cultural heritage: digital media art image recognition technology convolutional neural network cultural heritage

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Research on the visual quality evaluation indicators of water washed stone surface

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STRUCTURAL CONCRETE 2025年第0期

作者： Zhao, Hui Zhang, Li China Water Resources & Hydropower Sixth Engn Bur Shenyang Peoples R China North China Univ Water Resources & Elect Power Sch Water Conservancy Zhengzhou 450045 Peoples R China

The water-washed stone surface layer is frequently employed in ecological walkways and other settings. However, ensuring the uniformity of aggregate exposure in the water-washed surface layer during construction is challenging, with few quantifiable evaluation indicators available. This article leverages image recognition technology, integrating hardware and software, to develop a portable device for recognizing aggregates in the water-washed stone surface layer. This device facilitates image acquisition, processing, and feature extraction of the surface layer. Statistical theory is then applied to analyze the results, aiming to quantify the uniformity of exposed aggregates. The proposed method suggests that the relative spacing of exposed aggregates should fall within a 95% confidence interval based on normal distribution characteristics, specifically between 0.8 and 1.1 times the diameter of the aggregates, for a uniformly distributed surface. This configuration is believed to optimize the visibility of the water-washed stone surface layer. The system significantly enhances the efficiency and quality of the washed stone surface layer, demonstrating substantial potential for further development and implementation.

关键词： aggregate exposure aggregate gradation image recognition technology particle morphology washed stone surface layer

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Effectiveness Analysis of Entrepreneurial Legal Risk Prevention Based on Multi-Modal Deep Learning Model

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ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING 2024年第6期23卷 1-16页

作者： Li, Tianhua Qu, Shaowei Univ Sci & Technol Beijing Inst Educ Econ & Management 30 Xueyuan Rd Beijing 100083 Peoples R China

With the emergence of the upsurge of entrepreneurship, entrepreneurs are increasingly concerned about legal risks. In the process of entrepreneurship, legal risk is the biggest hidden danger of entrepreneurial en-terprises. The prevention and avoidance of legal risks is a long and arduous process, and not all risks can be identified and avoided in time. The deep learning method has brought great changes to the fields of speech recognition, image recognition and natural language processing. The tasks in these fields only involve single-mode input, but more recent applications need to involve multi-mode intelligence. Multimodal deep learning mainly includes three aspects: multimodal learning representation, multimodal signal fusion and multimodal application. Through the research on the legal risks in recent years, this paper believed that there are many legal problems in the development of entrepreneurial enterprises, including contract disputes, trade secret disputes, trademark infringement disputes, copyright infringement disputes, and so on. This paper aimed to study the problem of Legal Risks of Entrepreneurship (LRE) that entrepreneurs are concerned about, and proposed a new solution from the perspective of image recognition technology. 486 entrepreneurs were inves-tigated by questionnaire. In the process of entrepreneurship, 87.04% of entrepreneurs encountered legal risks, and they would turn to lawyers for help, which is a better way. However, in most cases, entrepreneurs are exposed to LRE because of their insufficient understanding of economic law, so they solve it through lawyers. However, if a lawyer is hired, the cost would be very high, which would bring great economic pressure to the enterprise. Only 17.90% of entrepreneurs would safeguard their legitimate rights and interests through their own knowledge and legal weapons without resorting to lawyers. It can be seen that entrepreneurs have relatively low practical ability in the use of LRE, and their le

关键词： Venture Legal Risk image recognition technology risk prevention arti-ficial neural network multimodal deep learning model

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Development of anti-segregation device and uniformity evaluation for all-bamboo aggregate concrete

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CONSTRUCTION AND BUILDING MATERIALS 2024年 425卷

作者： Chen, Xiang Zhu, Hongzhou Yang, Xuyuan Huang, Chunxiang Chongqing Jiaotong Univ Sch Civil Engn 66 Scholast Ave E Chongqing 400074 Peoples R China Chongqing Jiaotong Univ Natl & Local Joint Engn Lab Transportat & Civil En Chongqing 400074 Peoples R China

With the global focus on low-carbon and sustainable development, the extensive consumption of non-renewable resources such as sand and stone aggregates by cement concrete has raised widespread concerns. Therefore, using bamboo aggregates to replace crushed stone in the preparation of concrete is an effective path. The issue of homogeneity caused by the lightweight characteristics of all-bamboo aggregate concrete (BAC) has not been fully evaluated and researched. The non-uniformity of concrete is a key factor affecting its mechanical properties and service life. Firstly, an apparatus and method suitable for evaluating the anti-segregation property of BAC are proposed, using the coefficient of variation of mass (Cvm) as an indicator for assessing anti-segregation. For hardened concrete, image recognition technology is employed to assess the distribution uniformity of coarse aggregates and to analyze the mechanism of their spatial distribution. Research indicates that the developed evaluation device can effectively assess the anti-segregation performance of BAC. An appropriate amount of warm wheel glue admixture, smaller particle size of bamboo aggregates, and a suitable water-cement ratio are crucial for enhancing anti-segregation. Based on the analysis of the movement characteristics of aggregates, it is pointed out that BAC needs to adopt a top-down vibration method during the molding process. Moreover, with a reasonable mix design, the uniformity of BAC can be superior to that of ordinary concrete. A quality variation coefficient of no more than 9.5% is proposed as an evaluation indicator for anti-segregation performance. This study provides scientific basis for addressing the uniformity and stability issues that may arise in the practical application of BAC. In the future, further research is needed on the development of automated and intelligent evaluation devices for quality control of BAC.

关键词： Bamboo aggregate concrete Uniformity evaluation Anti-segregation device Coefficient of variation image recognition technology

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VIS-MM: a novel map-matching algorithm with semantic fusion from vehicle-borne images

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INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 2023年第5期37卷 1069-1098页

作者： Li, Bozhao Wang, Mengqi Cai, Zhongliang Su, Shiliang Kang, Mengjun Wuhan Univ Sch Resource & Environm Sci Wuhan Peoples R China Wuhan Univ Key Lab Geog Informat Syst Minist Educ Wuhan Peoples R China

Conventional map-matching (MM) algorithms take blind eyes to the complexity in realistic traffic conditions and hence present significant limitations in distinguishing the detailed driving paths of vehicles within complex urban road networks. The popularity of vehicle-borne cameras and advances in image recognition technologies provide an opportunity to remedy the gap through integrating vehicle-borne image semantic information with MM algorithms. Following this logic, this article proposes a novel MM algorithm with semantic fusion from vehicle-borne images (VIS-MM) suited to the parallel road scenes. First, a multipath output algorithm is developed using the hidden Markov model to obtain candidate paths. Second, image recognition techniques are employed to extract vehicle-borne image semantics. Finally, the entropy weight method is performed to determine the most promising driving path among the candidate paths. The experimental results show that semantic fusion from vehicle-borne images contributes to a significant improvement of accuracy from 66.18% to 99.88% against the parallel road scenes. The proposed map-matching algorithm can be applied into the fields of unmanned autonomous navigation and crowdsourcing updating of high-definition maps.

关键词： Map-matching algorithm vehicle-borne image semantics image recognition technology hidden Markov model entropy weight method

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Automatic Evaluation of Atomization Effect of Fiber Materials Based On image recognition

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Procedia Computer Science 2025年 261卷 12-19页

作者： Jing Zeng Jianfeng Chen Jiamin Lei Jiacheng Ou Process Research Institute Technology Center of China Tobacco Guangdong industrial Co. Ltd Guangzhou China Tobacco Processing Workship Guangzhou Cigarette Factory of China Tobacco Guangdong Industrial Co. Ltd Guangzhou China Product Research Institute Technology Center of China Tobacco Guangdong industrial Co. Ltd Guangzhou China

In order to improve the efficiency and accuracy of the evaluation of the atomization effect of the filament dosing material, image recognition technology combined with a high-resolution industrial camera was used to analyze the multi-dimensional data of atomization particle size distribution, spray coverage and uniformity. The results show that under the conditions of 5% material concentration and 3 MPa spray pressure, the average particle size is 50.3 μm, the coverage area reaches 120.8 cm², the uniformity of atomization reaches 96.5%, and the system evaluation accuracy can be maintained at more than 99%. The system effectively supports process optimization and production quality control, shows high stability and adaptability, and lays a technical foundation for the intelligent upgrading of filament dosing.

关键词： image recognition technology Atomization Effect Filament Making Charging

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Design of an autonomous remote control hovercraft with image recognition technology

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INDIAN JOURNAL OF ENGINEERING AND MATERIALS SCIENCES 2013年第3期20卷 183-190页

作者： Wang, Chun-Chieh Lee, Ting-En Chien Kuo Technol Univ Dept Elect Engn Changhua 500 Taiwan Natl Yunlin Univ Sci & Technol Grad Sch Engn Sci & Technol Yunlin 640 Taiwan

This study mainly focuses on the design of an autonomous remote control (RC) hovercraft. In the control design of hovercraft, we apply a fuzzy gain scheduled integral scheme to deal with the uncertainties of nonlinear system. In the implement system, the BASIC Stamp micro-controller is applied as control center to perform tasks. In addition, the ultrasonic sensor is used for providing the function of obstacle avoidance, and the Camera installed on hovercraft is able to catch the immediate image. With the application of image recognition technology, the developed RC hovercraft possesses the capability of recognition and navigation. The experimental results indicate that based on the proposed method the RC hovercraft can be autonomously navigated to the target.

关键词： RC hovercraft Autonomous control Fuzzy gain scheduled BASIC Stamp Obstacle avoidance image recognition technology

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Design of Digital Museum System based on AR and ORB Optimization Algorithm

Design of Digital Museum System based on AR and ORB Optimiza...

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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Ji, Meihan Fu, Yi Shenyang Jianzhu University School of Design and Art Shenyang China

ISBN: (纸本)9798350313413

Aiming at the problems of high cost and narrow popularization of existing augmented reality technology, which is not suitable for most museum exhibitions, the study introduces the feature point detection idea of binary robust invariant scalable key point algorithm to improve the matching recognition algorithm based on natural features of images. The study found that the matching time of the improved matching recognition algorithm is below 1s and the matching accuracy rate is above 90%. The augmented reality system based on the improved matching recognition algorithm can successfully recognize the exhibits with the recognition distance less than 80cm and the recognition characteristics blocked by 50%, and can efficiently establish the corresponding three-dimensional model of the exhibits in the digital museum. To sum up, the improved matching recognition algorithm proposed in this paper is robust and has certain application value in the exhibition of digital museum exhibits. © 2023 IEEE.

关键词： accelerated segment test feature algorithm augmented reality technology digital museum gray centroid method image recognition technology

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Research on the Application of Deep Learning Algorithm in Face Expression recognition

Research on the Application of Deep Learning Algorithm in Fa...

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2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Luo, Yanling Huang, Longhui Wuhan Technology and Business University Wuhan430065 China

ISBN: (纸本)9798350308167

recognition technology is a kind of extensive technology applied by AI technology, which mainly uses expressions and related data for face recognition. The key points in face recognition technology need intelligent algorithm ***, this paper proposes an intelligent technology of face recognition, which analyzes its expressions. First, collect expression data, then compare expressions according to expression formats and samples, and carry out the actual *** recognition can find the actual expressions of different people and make judgments based on them. The research results show that face recognition can better analyze actions and expressions, and provide technology for related *** recognition technology can be widely used. © 2023 IEEE.

关键词： deep learning algorithms facial expression recognition image recognition technology

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Judgment and optimization of video image recognition in obstacle detection in intelligent vehicle

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2020年第0期136卷 106406-000页

作者： Li, Qing He, Tao Fu, Guodong Beijing Informat Sci & Technol Univ Intelligent Control Inst Beijing Peoples R China Shenzhen Inst Informat Technol Shenzhen Peoples R China Beijing Dewei Chuangying Technol Co Ltd Beijing Peoples R China

The objective is to solve the problem of image recognition in intelligent vehicles and optimize the judgment of obstacles and the planning of subsequent routes of intelligent vehicles. Methods: The machine vision technology is used to collect images of relevant road segments, process these images with graying and binarization methods, and simulate the proposed method to observe its effect through data collection. Through the analysis of continuous direct-through driving after encountering the obstacles, it is found that the intelligent vehicles have small traveling errors once the routes are identified and planned. In addition, the error in the x-direction is no more than 0.006 m, while the error in the y-direction is no more than 0.003 m. The recognition effect of the vehicle has reached the expected result. Through the analysis of turning and rotary driving after encountering the obstacles, it is found that after the intelligent vehicles have identified the obstacles and planned the routes, a sudden change in the amplitude of the curve during the turn is caused. In addition, during the turning driving, the error in the x-direction is no more than 0.02 m, while the error in the y-direction is no more than 0.05 m. During the rotary driving, the error in the x-direction is no more than 0.03 m, while the error in the y-direction is not more than 0.04 m. The error variation range is also within the allowable error range. Through the research in this paper, it is found that the error of intelligent vehicle is within the allowable range and achieves the expected effect. Although there are some shortcomings in the experimental process, it can still provide an experimental basis for obstruction detection and route planning of intelligent vehicles in the later stage. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Intelligent vehicle image recognition technology Machine vision technology Obstruction detection technology

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