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Corresponding an Audio-processing Transformer to EEG Brain Activity Induced by Naturalistic Audio-visual Video Stimuli

Corresponding an Audio-Processing Transformer to EEG Brain A...

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7th International conference on Artificial Intelligence in information and communication, ICAIIC 2025

作者： Kurashige, Hiroki Kaneko, Jun Institute of Advanced Biosciences Tokai University Tokyo Japan School of Information Telecommunication Engineering Tokai University Tokyo Japan

ISBN: (纸本)9798331507022

We attempted to relate EEG brain activities evoked by naturalistic audio-visual video stimuli to the outputs of an audio-processing Transformer induced by audio inputs extracted from the same stimuli. We found a good correspondence, especially in low-frequency brain activity. This is complementary to a previous study that showed good correspondence between high-frequency brain activity and a movie-processing Transformer. These suggest that combining audio- and movie-processing Transformers and using them as a brain simulator is promising. That is, by utilizing this, it should be possible to synthesize audio-visual video stimuli that can intervene in a variety of brain activities and functions. © 2025 IEEE.

关键词： Deep neural networks

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Hardware Implementation of Machine Vision System for Component Detection 7th

Hardware Implementation of Machine Vision System for Compone...

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7th International conference on Emerging Research in Computing, information, communication and Applications, ERCICA 2022

作者： Smruthi, P. Prajna, K.B. John, Jibin G. Pasha, Aslam Taj VLSI and Embedded Systems Nitte Meenakshi Institute of Technology Bengaluru India Department of Electronics and Communication Nitte Meenakshi Institute of Technology Bengaluru India Research and Technology Development Group ACE Designers Ltd Bengaluru India

ISBN: (纸本)9789811954818

Inspection of components using machine vision technologies provides solution for quality and process control. This technique is used in various applications such as automotive, pharmaceutical, food and beverage, electronics, packages, process control and special application. The basic idea is to use machine vision technology in the industries to improve the production quality, reduce the scrap product due to non-conformity by controlling the manufacturing process through machine vision and also to prevent the value addition for scrap product in the subsequent stage of manufacturing process. Thus, designing and developing a machine vision system for component identification used the image processing algorithm. Inside the component, small circles which are of 0.5 diameter are detected using Hough circle detection. Graphical user interface was developed for visual representation of the image processing. The training model of the system is developed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Graphical user interfaces

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A Novel led spherical visual display system and its image geometric correction method 1

A Novel led spherical visual display system and its image ge...

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1st International conference on Artificial Intelligence and Human-Computer Interaction, ArtInHCI 2023

作者： Zeng, Yixiong Dai, Jianxi Xu, Bo Qiu, Kun School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu610054 China

ISBN: (纸本)9781643685083

visual display systems have wide-ranging applications in training simulators, serving as comprehensive systems that expand the display field of view by seamlessly combining multiple display units. This paper introduces an innovative spherical display system based on LED technology, designed to achieve close-proximity real-image display within a spherical enclosure. Additionally, we propose a channel division method tailored for this novel LED spherical display to enable efficient display driving. To address geometric distortion issues that arise when rendering flat graphics on a spherical surface, we present a geometric correction method specially designed for LED spherical displays, providing a comprehensive explanation of its theoretical principles and correction process. Experimental results demonstrate that with the implementation of our proposed channel division and geometric correction methods, the number of driving channels for the LED spherical display is reduced, image cropping is minimized, and there is no need for image fusion processing. Corrected images exhibit no distortion, and channel alignment remains continuous without any displacement. This method offers a straightforward operation, requires minimal parameter settings, and is easily implementable, providing a solid foundation for the widespread application of LED spherical vision display systems the future. © 2024 The Authors.

关键词： Light emitting diodes

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communication Theory Teaching Methods Using Multimedia Technologies and Application Packages

Communication Theory Teaching Methods Using Multimedia Techn...

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2022 Systems of Signals Generating and processing in the Field of on Board communications, SOSG 2022

作者： Poborchaya, N.E. Kudryashova, A.Y. Adzhemov, A.S. Moscow Technical University of Communication and Informatics Moscow Russia

ISBN: (纸本)9781665406352

In the modern world, the use of innovative tools for distance and multimedia learning is relevant in connection with the digital transformation of the world. Future technicians should not only learn the theory of any technical discipline, but also be able to apply the knowledge gained in practice. Given the popularity of information technology, any technical specialist should learn the basics of programming and creating simulation models for further research and technical development. In this regard, the article proposes a method of teaching the course "General Theory of communication"and related disciplines using multimedia (presentation) technologies with audio accompaniment and animation, as well as using the "MATLAB"software for laboratory work. Descriptions and software implementation of laboratory works on the topic "M-QAM signal processing in a system with MIMO and a direct conversion receiver"and visual information about the lecture course are presented. © 2022 IEEE.

关键词： Teaching

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The Improved Algorithm Of Image Enhancement Based on Optical Fourier Transformation

The Improved Algorithm Of Image Enhancement Based on Optical...

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2022 International conference on Computing, communication, Perception and Quantum Technology, CCPQT 2022

作者： Huang, Yaoqun Zhang, Qijing School of Electronics and Information Engineering Heilongjiang University of Science and Technology Harbin China

ISBN: (数字)9781665470209

ISBN: (纸本)9781665470209

Image enhancement is an important part of image information processing, image manipulation enhanced algorithm plays an important role in improving image quality, it involves all aspects of human life and social production. Because of the conditions of the scene, the visual effects and quality of images are often unable to meet the requirements, their quality is poor, this requires image enhancement technology to improve human visual effect, improve image quality. Compared with the deep learning method of big data, the traditional image manipulation enhanced algorithm does not need a larger number of learning samples, and has a small amount of calculation and fast processing speed, and is still the main way of image manipulation enhanced algorithm at present. This essay takes optical processing as a breakthrough point, the image manipulation enhanced algorithm is improved based on the principle of Abbe's image, and the High frequency image signal is enhanced by Unsharp Masking, the low frequency images are enhanced by Contrast Limited Adaptive Histogram Equalization. Finally, the high frequency and low frequency images are fused by weighted wavelet to achieve multi-dimensional enhancement of the image, obtain more detailed information of the image, and improve the image quality significantly. © 2022 IEEE.

关键词： Image enhancement

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Deep Learning Technique for Computer Vision-Based Pose Estimation for Augmented Reality 3rd

Deep Learning Technique for Computer Vision-Based Pose Estim...

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3rd International conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2023

作者： Palanimeera, J. Ponmozhi, K. Jyothi, Kanagaraj Dargar, Shashi Kant Birla, Shilpi Department of Computer Applications Sathyabama Institute of Science and Technology Chennai India Department of Computer Applications Kalasalingam Academy of Research and Education Krishnan Kovil Tamil Nadu Virudhunagar India Department of Biotechnology Kalasalingam Academy of Research and Education Krishnan Kovil Tamil Nadu Virudhunagar India Department of Electronics and Communication Engineering Kalasalingam Academy of Research and Education Krishnan Kovil Tamil Nadu Virudhunagar India Department of Electronics and Communication Engineering Manipal University Jaipur Rajasthan Jaipur India

ISBN: (纸本)9789819784288

Pose estimation approaches of open pose were suggested. Pose estimation in real-time is a difficult research subject with many computer vision applications. Pose estimation applications are Human Activity Estimation, Motion Transfer and Augmented Reality, Training Robots, Motion Tracking for Consoles, and Human Fall Detection. This paper describes the Augmented Reality (AR) of pose estimation. AR is an enhanced version of the real physical world that is achieved through the use of digital visual elements, sound, or other sensory stimuli delivered via technology. One interesting use for obtaining the Open-Pose discovered important locations in each pose is in the field of augmented reality. A technique for 3D model overlays on an image using pose key point information that is presented in this study. To extract crucial information from the data, the fully convolutional networks deep learning technique is used. The technique used in this work comprises the real-time intersection of the picture plane with the intended 3D model and accurate model orientation based on the key point data. The performance will greatly depend on the Graphics processing Unit specifications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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Referential communication in Heterogeneous Communities of Pre-trained visual Deep Networks 22

Referential Communication in Heterogeneous Communities of Pr...

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22nd International conference on Autonomous Agents and Multiagent Systems, AAMAS 2023

作者： Mahaut, Matéo Franzon, Francesca Dessì, Roberto Baroni, Marco Universitat Pompeu Fabra Barcelona Spain Meta AI Barcelona Spain ICREA Barcelona Spain

As large pre-trained image-processing neural networks are being embedded in autonomous agents such as self-driving cars or robots, the question arises of how such systems can communicate with each other about the surrounding world, despite their different architectures and training regimes. As a first step in this direction, we explore the task of referential communication in a community of state-of-the-art pre-trained visual networks, showing that they can develop a shared protocol to refer to a target image among a set of candidates. Such shared protocol, induced in a self-supervised way, can to some extent be used to communicate about previously unseen object categories. Finally, we show that a new neural network can learn the shared protocol developed in a community with remarkable ease, and the process of integrating a new agent into a community more stably succeeds when the original community includes a larger set of heterogeneous networks. © 2023 International Foundation for Autonomous Agents and Multiagent Systems (***). All rights reserved.

关键词： Autonomous agents

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The Application of Machine Learning to Natural Language processing: Modern Advances in the Study of Human Language

The Application of Machine Learning to Natural Language Proc...

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2024 International conference on Cybernation and Computation, CYBERCOM 2024

作者： Kumar, S. Pradeep Diwakar, Meenakshi Jaishika, S. Arthi, P. Pandi, V. Samuthira Shobana, D. Vel Tech Rangarajan Dr. Sagunthala RandD Institute of Science and Technology Department of Information Technology Avadi Chennai India Panimalar Engineering College Department of IT Chennai India Aarupadai Veedu Institute of Science and Technology Department of Electronics and Communication Engineering Avadi Chennai India GRT Institute of Engineering and Technology Department of ECE Tiruttani India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Tamil Nadu Chennai India Rajalakshmi Engineering College Department of Mechatronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331542344

The field of natural language processing (NLP) is that of artificial intelligence and computer science, which investigates how computers influence human language. Speech recognition, translation, and sentiment analysis have all been improved because to the application of machine learning in natural language processing. It has become more difficult for computers to comprehend, interpret, and synthesize human language. Recent developments in machine learning for natural language processing (NLP) have centered on the creation and implementation of intricate algorithms and models that assist machines in deciphering and producing human language in a more speedy and effective manner. First, we will go over the fundamentals of natural language processing and machine learning. NLP will continue to develop, passing through rule-based systems, statistical models, and most recently, deep learning. Having a strong understanding of context, semantics, and syntax, these models make it possible to develop increasingly complex applications for language analysis. In this paper, the confines and restrictions that are associated with NLP machine learning approaches are discussed. An example of a problem is the necessity for computational resources, as well as interpretability and data bias. When we talk about continuing efforts to address these problems, we talk about things like research into transfer learning and few-shot learning, as well as the development of models that are more efficient and resilient. Our final discussion examines natural language processing research's future. Multimodal data (text, audio, and visual) and interactive and customizable NLP systems are conceivable. To conclude, the study emphasizes machine learning's revolutionary impact on human language research and applications. Further innovation and growth in this area are possible. © 2024 IEEE.

关键词： Semantics

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visual communication Design of Image Multidimensional visualization Fusion System Based on Machine Learning 2

Visual Communication Design of Image Multidimensional Visual...

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2nd Asia-Pacific conference on communications Technology and Computer Science, ACCTCS 2022

作者： Ni, Xueyan Zhang, Ruhua Art College Changchun University Changchun130022 China

ISBN: (纸本)9781665400343

With the advent of the era of big data, people are exposed to a variety of data information every day. With the rise of high technology in the computer industry, data models are becoming more and more complex and changeable. Therefore, it is necessary to combine visualization technology with machine learning technology to process data more efficiently. With the development of computer processing software and related technologies, computer image processing software is widely used in modern film and television, advertising, games, software, and commercial activities for image design and visual communication design. The works designed by this design method have strong appeal and clear features, which can easily leave a deep impression on the viewer. At the same time, the art works designed by this design method are more innovative, which also has positive and profound significance for creators. However, most researchers currently focus on the optimization of the machine learning algorithm itself, but ignore the visual communication design of the image multi-dimensional visualization fusion system based on machine learning, and cannot intuitively see the operation process of the design. Therefore, this article focuses on the analysis of the current state of research in the field of visualization related to machine learning technology. © 2022 IEEE.

关键词： visualization

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Comparative study of latent-sensitive processing of heterogeneous data in an experimental platform for 3D video holographic communication 5

Comparative study of latent-sensitive processing of heteroge...

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5th Global conference on Wireless and Optical Technologies (GCWOT)

作者： Petkov, Nikola Christoff, Nicole Manolova, Agata Tonchev, Krasimir Poulkov, Vladimir Tech Univ Sofia Fac Telecommun Sofia Bulgaria

ISBN: (纸本)9781665471053

Holographic communication is a complete humancomputer-machine interface that combines augmented reality and virtual reality telepresence to create real-life digital scans and realistic 3D avatars of subjects that are displayed in a mixed reality environment and used for real-time communication and interaction between remote users. The latency that exists while relaying the realistic impression of presence in a remote location to a local human user is impeding the acceptability of immersive telepresence systems. Motion sickness, caused by the misalignment between the user's motion and the visual response, is one of the main reasons for the slow adoption of these systems. In this paper we explore two use case scenarios to measure the calculated transmission time of heterogeneous data, including key points of the 3D model of the body, face or hands, so as to meet the limitations of bandwidth and latency in current and future networks. Depending on the way the information is transmitted and received, the speed of transmission and the amount of information, as well as other important factors, different modes of operation for the proposed experimental platform are considered, allowing it to be flexible by adapting to the available resources.

关键词： holographic communication augmented reality immersive telepresence systems holograms latency

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