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检索条件"任意字段=Conference on Visual Information Processing and Communication VI"

共 3485 条记录，以下是1-10 订阅

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Computer graphics and image processing techniques based on visual communication design 4

Computer graphics and image processing techniques based on v...

引用

4th International conference on Computer vision, Application, and Algorithm, CVAA 2024

作者： Chen, Zhaoguo College of Arts Shandong Agricultural Engineering University Shandong Province Jinan250103 China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

To fully harness the capabilities of computer graphics and image processing technologies and elevate the quality of visual communication design, this paper presents a comprehensive suite of innovative methodologies. Firstly, the fundamental principles of primary colors are utilized to formulate a series of vector functions, facilitating the precise calculation of error distances and the establishment of an intricate visual communication zoning model. Subsequently, through the exhaustive extraction of pertinent feature information from graphics and images, we achieve the scientific encoding of coefficient-constrained features and determine the corresponding hyperplanes to acquire the relevant parameters for visual communication. Eventually, the implementation of advanced design image expression algorithms markedly enhances the effectiveness of visual communication image representation. The empirical findings reveal that these visual communication design methods exhibit remarkable reliability and feasibility, effectively boosting image recognition accuracy across four distinct image categories with varying levels of complexity, thereby yielding exceptional visual communication outcomes. © 2025 SPIE.

关键词： Design visual communications visualization Computer graphics Image processing Image storage Color Image segmentation Image enhancement

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Fully Optical Integrated Mixture-of-Experts System 24

Fully Optical Integrated Mixture-of-Experts System

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4th International conference on Signal processing and communication Technology, SPCT 2024

作者： Li, Chen Shandong Massive Information Technology Research Institute Shandong Jinan China

ISBN: (纸本)9798400710636

A fully optically integrated Mixture-of-Experts (MoE) system is introduced to address the explosive growth in computational power demands in the development of artificial intelligence technologies. Here, we highlights the potential of optical computing in solving communication challenges for MoE models and proposes a fully optically integrated MoE system. This system integrates on-chip subwavelength diffraction units (SWU) as expert models and uses Mach-Zehnder interferometers (MZI) as gating and tuning modules to achieve system integration. The system not only solves the technical issue of on-chip training difficulty in existing optical diffraction computing models but also overcomes the performance limitations of optical interference computing models. By combining the advantages of both, it enhances the performance of optical computing models and the scalability of optical systems. Finally, the article validates the feasibility of the system in visual tasks through simulation experiments and demonstrates the simulation results of signal input and output using MZI, proving the feasibility of the scheme. © 2024 Copyright held by the owner/author(s).

关键词： Mach-Zehnder interferometers

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SmartCML: A visual Modeling Language to Enhance the Comprehensibility of Smart Contract Implementations 17th

SmartCML: A Visual Modeling Language to Enhance the Compre...

引用

17th IFIP 8.1 Working conference on the Practice of Enterprise Modeling, PoEM 2024

作者： Curty, Simon Fill, Hans-Georg Digitalization and Information Systems Group University of Fribourg Bd de Pérolles 90 Fribourg1700 Switzerland

ISBN: (纸本)9783031779077

One of the most notable capabilities of blockchain technology, exemplified by the Ethereum platform, is the decentralized execution of deterministic code, commonly referred to as smart contracts. This can be employed to develop business services that capitalize on the unique properties of blockchain technology, including the ability to maintain immutable, transparent, and persistent records on a distributed ledger. Nevertheless, even experts may find the process of writing smart contracts challenging. In addition to cost, optimization, and security concerns, it is essential to ensure that the smart contracts align with the business case and the associated rules. To address this issue, we propose SmartCML, a domain-specific visual modeling language to draft smart contracts, with the primary objective of facilitating the communication of the codified information among relevant stakeholders. The modeling language has been implemented using the ADOxx metamodeling platform. Smart contract models can then be transformed into fully functional code for the Ethereum virtual machine. The application of the modeling language is demonstrated with the help of two use cases. © IFIP International Federation for information processing 2025.

关键词： Smart contract

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Research on Multi-class Fine Motor Intention Recognition of Hands 24

Research on Multi-class Fine Motor Intention Recognition of ...

引用

4th International conference on Signal processing and communication Technology, SPCT 2024

作者： Yang, Yang Yan, Bian Miao, Sun Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin Vocational and Technical Normal University Tianjin China

ISBN: (纸本)9798400710636

To address the problem of poor precision of fine motor intention recognition, which is difficult to apply to the field of neural rehabilitation, this paper designed a bilateral motor imagery (MI) paradigm using dynamic visual imagery: There were four kinds of motor intentions: left hand to finger, left hand to grip, right hand to finger, right hand to grip. Time-frequency map, brain topographic map and R2 coefficient were used to analyze the divisibility features among different categories. FBCSP (filter bank - common space model) and SVM (support vector machine) models were used to classify the fine motor intentions among various categories. The research results prove that the event-related desynchronization (ERD) features of multiple types of fine motor intentions in the same part are separable under the dynamic visual auxiliary stimulus paradigm. The average recognition accuracy of 4 types of fine motor intentions of 12 subjects can reach 63.7±3.67%, which is significantly higher than the random probability of 4 types. The experimental results show that the proposed method can effectively distinguish multiple types of fine motor intentions in the same part, and provide a new way for its application in the field of neurological rehabilitation. © 2024 Copyright held by the owner/author(s).

关键词： Neurons

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Morse Code Encryption: Securing visual information with Morse Transform 5th

Morse Code Encryption: Securing Visual Information with Mors...

引用

5th International conference on Data Science, Machine Learning and Applications

作者： Prashanthi, Bh Sai, A. Nikhil Datta Sravan, A. Joganandha Sai Sohan, M. Rohit, G. Gokaraju Rangaraju Inst Engn & Technol Comp Sci & Engn Hyderabad India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

Leveraging cutting-edge eye-tracking technology and machine learning algorithms, a real-time, non-invasive solution that empowers individuals with motor disabilities, allowing them to communicate seamlessly through natural eye movements. The project encompasses a comprehensive pipeline, starting with the collection of precise eye movement data using state-of-the-art eye-tracking hardware. It employs sophisticated image processing techniques to preprocess the acquired data, filtering out noise and detecting blink patterns accurately. This computer vision project not only showcases the potential of eye blink detection for text-based communication but also highlights the importance of innovative solutions that empower individuals with physical limitations to interact with technology effortlessly. Our recommended approach is continually used to test the effects of light and the distance between a user's eyes and a mobile device to assess the exact position, according to test results, offers 90% general exactness and 100% recognition accuracy for a distance of 15 cm with a false light.

关键词： Blink Detection Morse Code Eye movement Tracking openCV

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Deep Learning for Speech Separation: A Comprehensive Review 3rd

Deep Learning for Speech Separation: A Comprehensive Review

引用

3rd International conference on Advances in information and communication Technology, ICTA 2024

作者： Thi, Duyen Nguyen Tan, Ha Minh Phung, Trung-Nghia Vu, Duc-Quang Thai Nguyen University of Information and Communication Technology Thai Nguyen Viet Nam Faculty of Information Technology Nguyen Tat Thanh University Ho Chi Minh City Viet Nam Department of Computer Science and Information Systems Thai Nguyen University of Education Thai Nguyen Viet Nam

ISBN: (纸本)9783031809422

Integrating deep learning in speech separation has revolutionized audio signal processing, impacting fields like speech recognition, audio-visual content creation, telecommunication, hearing aid technologies, etc. In time-frequency domain separation, models leverage amplitude and phase information while the waveform is used for training in the time-domain speech separation model. An emerging approach uses complex values, capturing intricate audio nuances for improved performance. Modern models prioritize speaker-independent separation, adapting to dynamic or unknown speaker identities. Their ability to simultaneously separate multiple speakers is crucial for applications like conference calls, overlapping dialogues, and surveillance. This review explores deep models in speech separation, offering insights into the time domain, and time-frequency domain strategies. We outline the current state of models and state-of-the-art learning methods for audio segmentation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Frequency domain analysis

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Optimization of UWB-Based Indoor Positioning Algorithm and Design of Positioning System 24

Optimization of UWB-Based Indoor Positioning Algorithm and D...

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4th International conference on Signal processing and communication Technology, SPCT 2024

作者： Hu, Yingkun Zhuang, Yihui Zhang, Yingbin Zhang, Dongbo School of Computer and Information Engineering Guangdong Polytechnic of Industry & Commerce Guangdong Guangzhou China

ISBN: (纸本)9798400710636

Considering the varying advantages, disadvantages, and implementation difficulties of current indoor positioning algorithms, this paper conducts a comparative analysis of common UWB ranging methods. The Two-Way Ranging (TWR) algorithm significantly improves ranging accuracy compared to the One-Way Ranging (OWR) approach. An optimized bi-directional TWR algorithm is proposed, in which the tag only needs to send a single Poll message, reducing ranging time and tag power consumption. To address measurement errors, where the trilateration circles may not intersect at a single point, the least squares method is employed to linearize and optimize the equations. A real-time indoor positioning system is designed, incorporating the optimized bi-directional TWR algorithm and trilateration algorithm. The software workflows for the tags and base stations are developed, and the system visualizes the distances from the tag to four base stations in the upper computer software, along with the derived position coordinates (X, Y, Z). The system achieves static errors within 0.05–0.06 meters, demonstrating its high accuracy for indoor real-time positioning. © 2024 Copyright held by the owner/author(s).

关键词： Least squares approximations

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Design and Implementation of Overseas communication Path for Chinese Corporate Image Based on Multimodal Discourse Analysis with Machine Learning Algorithm 24

Design and Implementation of Overseas Communication Path for...

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3rd International conference on Artificial Intelligence and Intelligent information processing, AIIIP 2024

作者： Lin, Jiling Lei, Fei Liu, Weiliang School of Foreign languages Guangdong University of Science & Technology Guangdong Dongguan China School of Finance and Economics Guangdong University of Science & Technology Guangdong Dongguan China Huizhou Modern Vocational Technology School Guangdong Huizhou China

ISBN: (纸本)9798400707308

In an increasingly globalized economy, the communication of corporate image plays a pivotal role in shaping perceptions and fostering relationships with international stakeholders. This study explores the design and implementation of effective overseas communication strategies for Chinese corporations, leveraging multimodal discourse analysis and machine learning algorithms. By synthesizing quantitative and qualitative data, we analyze various communication modalities—including visual, textual, and auditory elements—utilized in corporate branding across different cultural contexts. Employing machine learning techniques, we identify patterns and insights from vast datasets, enabling a nuanced understanding of how multimodal elements influence audience reception and engagement. Our findings reveal key factors that contribute to successful corporate image dissemination and highlight the importance of cultural sensitivity in communication strategies. The research provides a framework for Chinese corporations to enhance their global presence by integrating data-driven insights into their communication practices, ultimately fostering a more favorable corporate image and stronger international relationships. This study not only contributes to the field of corporate communication but also offers practical implications for practitioners seeking to navigate the complexities of multicultural environments in an era of rapid technological advancement. © 2024 Copyright held by the owner/author(s).

关键词： Machine Learning Algorithms

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Research on fine recognition method of electric power equipment safety hazards based on visual processing

Research on fine recognition method of electric power equipm...

引用

2024 International conference on Computer vision and Image processing, CviP 2024

作者： Huo, Yongbo Pang, Bingyao Yang, Xizai Yang, Le Lin, Yiming State Grid Shaanxi Electric Power Co. Ltd. Information and Communication Company Xi’an710048 China School of Electrical Engineering Xi’an University of Technology Xi’an710048 China

ISBN: (纸本)9781510688384

With the further research of deep learning, power companies have gradually eliminated the prevention and control by manual inspection, and have adopted deep learning to identify the safety hazards of power equipment, and to detect the defects of power equipment more accurately and quickly. Firstly, this paper introduces the significant drawbacks of traditional power equipment identification methods in the field of power equipment identification, and then illuminates the advantages of deep learning in the field of power equipment, which leads to the YOLOv7 algorithm used in this study, and then provides a detailed introduction of the theory and concepts of the algorithm. Second, this paper constructs a dataset applicable to the identification of safety hazards in electrical equipment, and uses this dataset to train and test the YOLOv7 algorithm. Finally, by analyzing the experimental results, it is concluded that the algorithm has a high accuracy character and robustness in the method of identifying safety hazards of electrical equipment. This study provides a practical and feasible technical route and theoretical foundation for solving the problem of safety hidden hazard detection of electrical equipment using YOLOv7 algorithm. © 2025 SPIE.

关键词： Power transmission lines

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Fourth International conference on Computer vision, Application, and Algorithm, CVAA 2024

Fourth International Conference on Computer Vision, Applicat...

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4th International conference on Computer vision, Application, and Algorithm, CVAA 2024

ISBN: (纸本)9781510687615

The proceedings contain 122 papers. The topics discussed include: DFrFT-ES model for emotion recognition based on fractional Fourier transform of EEG signals;research on traffic sign recognition under complex meteorological conditions;diffusion-augmented learning for long-tail recognition;apple leaf scab recognition using CNN and transfer learning;container image management in cloud-edge environments: an image deletion method based on layer affinity;computer graphics and image processing techniques based on visual communication design;dynamic fusion and non-negative matrix factorization-based multi-view clustering method;convolutional recurrent neural network-based EEG signal classification in motor imagery;and sentiment classification of MOOC courses by merging local context focus and bi-directional gated recurrent unit.

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