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检索条件"任意字段=IEEE Information Visualization Conference/IEEE Visualization Conference"

共 53955 条记录，以下是161-170 订阅

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Adversarial Feature Disentanglement Framework for Voice Pathology Detection

Adversarial Feature Disentanglement Framework for Voice Path...

引用

International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yifan Xiong Dongyue Guo Lipeng Shen Wei Mo Hui Yang Yi Lin College of Computer Science Sichuan University Chengdu China Department of Otorhinolaryngology-Head & Neck Surgery West China Hospital Sichuan University Chengdu China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Voice pathology detection plays an important role in diagnosis and medical intervention. Existing methods suffer from inferior performance with limited and imbalanced training samples since the pathological information is coupled with other linguistic and paralinguistic attributes. In this work, a novel adversarial feature disentanglement framework is proposed to achieve the voice pathology detection task by extracting task-oriented features and optimizing feature space. Specifically, to suppress noise features in the coupled representations, an adversarial feature disentanglement mechanism is proposed to decouple pathological and non-pathological information, in which a mutual information discriminator is introduced to prevent information leakage. A classification and contrastive learning (CCL) module is designed to cluster intra-class embeddings in high-dimensional space. Experiments on the open-source SVD and FEMH datasets demonstrate that the proposed model outperforms other competitive baselines, achieving 87.94% and 92.06% accuracy, respectively. The visualization also validates the effectiveness in distinguishing pathological and non-pathological features.

关键词： Training Measurement Pathology visualization Noise Contrastive learning Feature extraction Speech processing Mutual information Medical diagnostic imaging

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A Problem-Driven Approach to XR in Education: Teaching Non-Euclidean Geometries Through Virtual Reality

A Problem-Driven Approach to XR in Education: Teaching Non-E...

引用

Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), ieee conference on

作者： Maé MavRomatis Ronan Gaugne Rémi Coulon Valérie Gouranton Univ Rennes INSA Rennes Inria CNRS IRISA France Univ Rennes Inria CNRS IRISA France IMB UMR 5584 CNRS Université de Bourgogne Dijon

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Immersive technologies are increasingly used in education, offering unique benefits in fields like mathematics that require spatial understanding. These tools enable learners to interact with virtual environments, providing hands-on experiences that enhance comprehension and retention of abstract concepts. This is particularly valuable in areas like non-Euclidean geometries, which are difficult to visualize using traditional methods. This paper explores our research on using virtual reality to teach non-Euclidean geometries, highlighting both the benefits and challenges.

关键词： Geometry visualization Three-dimensional displays conferences Virtual environments Educational technology User interfaces information age Cognition Planning

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Enhanced Crop Yield Predictions Amid Climate Change to Improve Agriculture With SwinTrans-Att Based Model

Enhanced Crop Yield Predictions Amid Climate Change to Impro...

引用

2025 International conference on Visual Analytics and Data visualization, ICVADV 2025

作者： Gowsic, K. Ashwini, A. Sankar, M. Arul Balamurugan, R. Mahendra Engineering College Department of Computer Science and Engineering Namakkal Tamilnadu Mallasamudram India Mahendra Engineering College Department of Information Technology Mallasamudram TamilNadu Namakkal India

ISBN: (纸本)9798331521394

Harvest prediction is crucial to global, national, and local farming decisions. Soil, climate, environmental conditions, and crop characteristics affect harvest forecasts. Crop sensing, monitoring, management information systems, and variable rate technologies enable precision agriculture to enhance crop output and quality while minimizing environmental impact. The suggested method involves preprocessing, feature selection, and model training. Preprocessing normalizes input variables using min-max scaling to preserve distributions. Feature selection considers irrigation, land use, fertilizer application, and weather, which affect agricultural productivity. To trained the model with SwinTrans-Att, which handles complex agricultural data. The SwinTrans-Att model outperformed CNN and SVM with an average accuracy of 93.61%. This highlights its power for precision farming and crop management decisions. This study found that preprocessing, feature selection, and advanced modeling increase crop yield estimates. Precision agriculture's revolutionary potential to boost production and sustainability is shown © 2025 ieee.

关键词： Precision agriculture

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Natural Language Processing-Driven Learning Platform for Personalized Education

Natural Language Processing-Driven Learning Platform for Per...

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2025 International conference on Visual Analytics and Data visualization, ICVADV 2025

作者： Subitsha, R.S. Vetrivel, M. Shrimaulik, N. Saravanan, K. K.S.Rangasamy College of Technology Department of Information Technology Tamil Nadu Tiruchengode India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521394

The NLP-driven Learning Platform for Personalized Education will revolutionize educational experiences through the integration of Artificial Intelligence in improved adaptive learning. Other than typical systems, this platform powered by adaptive learning models, sentiment analysis, and gamification creates personalized instruction that best aligns with each student's cognitive and emotional state. For instance, the platform makes use of NLP models in the forms of Rasa for dialogue management and TensorFlow for adaptive algorithms [2];it measures learning patterns, emotional signals, and progress for its system of adjusting difficulty levels, feedback, and engagement. Preliminary test results indicate that this system can improve academic outcomes and increase student satisfaction through enhanced interactivity and support [4]. This paper covers the design, implementation, and expected impacts of such an innovative approach to the educational landscape, particularly in view of the Education 4.0 and 5.0 frameworks that are turning more personalized and adaptive. © 2025 ieee.

关键词： Sentiment analysis

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A Classification Method of Magnetic Flux Leakage Signal for Internal and External Wall Defects in Seamless Steel Pipes Based on Spectrogram and Support Vector Machine

A Classification Method of Magnetic Flux Leakage Signal for ...

引用

ieee information Technology and Mechatronics Engineering conference (ITOEC)

作者： Chen Bin School of Information Technology Anhui Vocational College of City Management Hefei China

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

Magnetic flux leakage non-destructive testing is an important method for comprehensive inspection of seamless steel pipes. Distinguishing the signals formed by internal and external wall defects is a significant issue in this method. This study proposes a new approach, which first converts the magnetic flux leakage signal obtained by the sensors into a spectrogram and calculates its gray level co-occurrence matrix. Then, it calculates the energy, entropy, and correlation at four different angles of the matrix. The mean and standard deviation of these quantities are used as the characteristic values of the defect signal. Combining with support vector machine technology, an identification model for the signals of internal and external wall defects is established. The model processes the test signal to achieve automatic defect classification. Experimental results show that this method can effectively identify and classify defect signals with high accuracy.

关键词： Support vector machines visualization Magnetic flux leakage Accuracy Sensor phenomena and characterization Steel Matrix converters Spectrogram Standards Testing

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Real Time Eavesdropping Attack Detection by Multivariate Correlation Analysis

Real Time Eavesdropping Attack Detection by Multivariate Cor...

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2025 International conference on Visual Analytics and Data visualization, ICVADV 2025

作者： Mukilan, T. Sairam, C.M. Tamilarasan, J. Mohanraj, K.C. K.S.Rangasamy College of Technology Department of Information Technology Tiruchengode India

ISBN: (纸本)9798331521394

Using the multivariate correlation analysis technique, Frothy Disturbance Intrusion Detection Systems (FIDSs) can be crucial in identifying and stopping security threats. Understanding the importance of Frothy Disturbance Intrusion Detection Systems (FIDSs) in protecting various internet-connected domains, we concentrate on modifying traditional intrusion detection techniques for the environment, which has limitations like memory and battery life. In this study, we create a lightweight attack detection technique using the Multivariate Correlation Analysis algorithm and a supervised machine learning-based FIDS. Using a combination of two or three complex characteristics, we illustrate through simulations how effective the suggested Multivariate Correlation Analysis-based FIDS classifier is, exhibiting good performance in terms of detection time and classification accuracy. This strategy has the potential to improve application security by effectively meeting the unique limitations and specifications of intrusion detection in situations with limited resources. © 2025 ieee.

关键词： Network intrusion

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I Hear, See, Speak & Do: Bringing Multimodal information Processing to Intelligent Virtual Agents for Natural Human-AI Communication

I Hear, See, Speak & Do: Bringing Multimodal Information Pro...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), ieee conference on

作者： Ke Li Fariba Mostajeran Sebastian Rings Lucie Kruse Susanne Schmidt Michael Arz Erik Wolf Frank Steinicke Human-Computer Interaction University of Hamburg HIT Lab NZ University of Canterbury

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

In this demo paper, we present an Extended Reality (XR) framework providing a streamlined workflow for creating and interacting with intelligent virtual agents (IVAs) with multimodal information processing capabilities using commercially available artificial intelligence (AI) tools and cloud services such as large language and vision models. The system supports (i) the integration of high-quality, customizable virtual 3D human models for visual representations of IVAs and (ii) multimodal communication with generative AI-driven IVAs in immersive XR, featuring realistic human behavior simulations. Our demo showcases the enormous potential and vast design space of embodied IVAs for various XR applications.

关键词： Solid modeling visualization Three-dimensional displays Extended reality Metaverse information processing User interfaces Systems support Haptic interfaces Artificial intelligence

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Foveated VR Rendering System for Large 3D Meshes

Foveated VR Rendering System for Large 3D Meshes

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), ieee conference on

作者： Huadong Zhang Chao Peng School of Interactive Games and Media Rochester Institute of Technology USA

Rendering of a complex scene on a Quest Pro, showing left and right eye views. The scene includes partial Moana Island, and the David and Lucy models, composed of 95,967,582 triangles and 48,487,571 vertices, and rend... 详细信息

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

关键词： Solid modeling visualization Three-dimensional displays Graphics processing units Focusing Virtual reality User interfaces Rendering (computer graphics) Resource management Load modeling

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New method to assess enhanced image quality based on luminance

New method to assess enhanced image quality based on luminan...

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ieee information Technology and Mechatronics Engineering conference (ITOEC)

作者： Lichuan Zhang Longyi Ye Yuhong Liu Department of Biomedical Engineering College of Health and Intelligent Engineering Chengdu Medical College Chengdu China

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

This paper proposed a new method to assess enhanced image quality based on luminance, studied the relationship between image luminance and image quality and the experiments proved the trend of image quality and image luminance under different visual conditions. Firstly, the image quality method to assess the enhanced image was established, then in order to get accurate results, we adopted two different luminance adjustment methods to study the relationship of the luminance and image quality assessment. Finally, the relationship between the image quality and the luminance was experimentally verified. Results shows that the image quality method can directly apply to assess the image quality and the relationship of the image quality and the luminance is a convex and non-linear function. According to the new method proposed in this study, we can use the relationship of the image quality and the luminance to adjust the luminance and achieve the best visual image quality and the research result will lay the foundation of image quality assessment.

关键词： Image quality Hands visualization Mechatronics Lighting Medical services Market research Cameras information technology Lenses

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Leveraging Visual Language information for Enhanced Person Re-Identification: A Robust Framework for Real-World Applications

Leveraging Visual Language Information for Enhanced Person R...

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ieee International conference on Consumer Electronics (ICCE)

作者： Seunghee Han Dasol Jeong Hasil Park Jiwon Park Hyebean Lee Joonki Paik Department of Image Chung-Ang University Seoul Korea Department of Artificial Intelligence Chung-Ang University Seoul Korea

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Recently, performance improvements through vision-language learning have gained significant attention in the field of image re-identification (ReID). In particular, the CLIP-ReID [1] achieved enhanced visual representations by introducing learnable text token sets for each identity. However, existing approaches have not fully exploited fine-grained part-specific features of the human body, which are crucial when applying person re-identification technology in real-world scenarios where partial occlusions or other factors might affect accuracy. To address this limitation, we propose a novel framework that incorporates body part-specific learnable text tokens, leveraging visual language information related to specific body regions. This approach is essential for mitigating the impact of occlusions and enhancing the robustness of ReID systems in practical settings. The process of applying visual language information through CLIP-ReID involves several stages. First, body part regions are identified and segmented within the image. Next, visual features specific to these regions are extracted and mapped to corresponding text tokens that describe these features in natural language. Finally, these text tokens are integrated with the image features to create a more comprehensive representation that captures both visual and semantic aspects, improving the discrimination of individuals based on specific anatomical features. Experimental results not only using the MSMT17 [2] and Market-1501 [3] datasets but also from a real-world scenario involving 11 CCTV cameras installed on the campus of Chung-Ang University demonstrated that the proposed method significantly outperformed existing models. This confirms the effectiveness of vision-language learning that utilizes segmented body part information in the image re-identification task.

关键词： Deformable models visualization Image segmentation Deformation Semantics Natural languages Data visualization Feature extraction Robustness Identification of persons

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