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

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Two-dimensional visualization of Spatial Sounds to Assess Object Localization Using a Navigation Aiding Device

Two-dimensional Visualization of Spatial Sounds to Assess Ob...

引用

2023 International conference on Systems and Technologies of the Digital HealthCare, STDH 2023

作者： Palogiannidis, Dimitrios Saint Petersburg State Electrotechnical University 'Leti' Department of Biotechnical Systems Saint Petersburg Russia

ISBN: (纸本)9798350315226

The severity of visual impairment has drawn attention in recent decades. The visually impaired are no longer neglected, as consistent attempts have been made to improve their quality of life, both with conventional and technologically advanced devices. Humans can use echolocation, a technique that many mammals use to determine the distance from obstacles. The principle on which echolocation is based is the Head Related Transfer Function (HRTF). The contents of this report are a direct continuation of the development of a patented spatial sound navigation system for visually impaired individuals using commercially available hardware. The device scanned the environment and generated beeps of variable amplitude and frequency, depending on the distance of the objects surrounding the user. This report describes a method of three-dimensional sound analysis using the Python programming language to evaluate the effectiveness of HRTF for spatial sound generation in humans during navigation. © 2023 ieee.

关键词： Python

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Universal Adversarial Attack Against 3D Object Tracking 23

Universal Adversarial Attack Against 3D Object Tracking

引用

23rd ieee International conference on High Performance Computing and Communications, 7th ieee International conference on Data Science and Systems, 19th ieee International conference on Smart City and 7th ieee International conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Cheng, Riran Sang, Nan Zhou, Yinyuan Wang, Xupeng School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781665494571

3D object tracking has great potential applications in computing intensive cyber-physical systems, particularly auto-nomic driving. However, Object tracking based on deep neural networks is vulnerable to adversarial examples. Previous works generate adversarial examples by applying perturbations to samples, which suffer from the generation of an individual adversarial perturbation for each sample. Algorithms have been proposed to generate a universal adversarial perturbation, which is one single perturbation able to make classifiers misclassify most images. In this paper, we propose the universal adversarial attack method against 3D object tracking. This method gen-erates adversarial samples by applying a universal adversarial perturbation to tracking templates, leading to the deviation of the predictions from the ground truth. A novel objective function, which combines confidence loss, direction loss and distance loss, generates an atomic perturbation for each tracking template. By aggregating these atomic perturbations, the universal adversarial perturbation can be derived. Experiments conducted on the KITTI dataset show that the proposed method can effectively reduce the performance of 3D object tracking. © 2021 ieee.

关键词： Deep learning visualization Three-dimensional displays Perturbation methods Neural networks Cyber-physical systems Linear programming

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Vision Transformers for X-ray Diffraction Patterns Analysis

Vision Transformers for X-ray Diffraction Patterns Analysis

引用

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

作者： Titouan Simonnet Mame Diarra Fall Sylvain Grangeon Bruno Galerne Institut Denis Poisson Université d’Orléans Université de Tours CNRS France BRGM Orléans Cedex 2 France Institut Universitaire de France (IUF)

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Understanding materials properties depends largely on the ability to determine its components, and in particular its mineral phases. Powder X-ray diffraction (XRD) is a powerful tool for such purposes. This paper presents a Transformer-based vision model (ViT) for mineral phase identification, and proportion inference to quantify the mineral phases present in a material. Our analysis shows that the tokenization strategy is a critical step for XRD pattern analysis. The results obtained for both tasks are excellent and more robust than those obtained with a CNN. The proposed approach also makes it possible to introduce visualization tools for signal analysis, to better understand how information flows through the model and how data is classified or quantified.

关键词： Analytical models visualization X-ray scattering Translation Data visualization X-ray diffraction Transformers Data models Minerals Pattern analysis

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Insulator Aiming Using Multi-Feature Fusion-Based Visual Servo Control for Washing Drone 39

Insulator Aiming Using Multi-Feature Fusion-Based Visual Ser...

引用

ieee International conference on Robotics and Automation (ICRA)

作者： Di, Jian Chen, Shaofeng Wang, Xinghu Zhang, Hepeng Ji, Haibo Univ Sci & Technol China Dept Automat Hefei Peoples R China

ISBN: (纸本)9781728196817

Insulator visual aiming is difficult for washing drone due to the complex washing environment, strong disturbance, lack of debugging environment, and other factors. Conventional visual servo control methods often fail to consider these complex factors adequately and fall short in reliable insulator visual aiming. To address these problems, we propose a novel multi-feature fusion-based drone visual servo control method for accurate insulator visual aiming. A multi-feature fusion neural network (MFFNet) is proposed to map the different input modalities into an embedding space spanned by the learned deep features. Suitable control commands are generated by the simple combination of learned deep features. These deep features represent the intrinsic structural properties of the insulator and the motion pattern of the drones. Particularly, our method is trained purely in simulation and transferred to a real drone directly. Moreover, accurate visual aiming is guaranteed even in strong disturbance environments. Simulation and experimental results verify the high accurate insulator aiming, anti-disturbance, and sim-to-real transfer capabilities of the proposed method. Video:https://***/Ptlajzvp46A.

关键词： Training visualization Image segmentation Neural networks Aerospace electronics Insulators Reliability

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Machine Learning Applied to Star-Galaxy-QSO Classification and Data visualization 5

Machine Learning Applied to Star-Galaxy-QSO Classification a...

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5th International conference on Pattern Recognition and Artificial Intelligence, PRAI 2022

作者： Ji, Xiang Wu, Yadong Zhang, Yuling Zhang, Han Zhang, Weihan Zhang, Wei Li, Yi Jiang, Liyuan Sichuan University of Science and Engineering School of Computer Science and Engineering Yibin China

ISBN: (数字)9781665499163

ISBN: (纸本)9781665499163

With the continuous development of modern astronomical observation methods, the sky survey data obtained through observation has increased exponentially, and machine learning has gradually replaced traditional scientific computing methods with its powerful computing power in the big data environment. In view of the problems of low classification accuracy, poor classification efficiency and few classification types in the current astronomical spectrum classification work, this study added sub-classification to the original classification benchmark and compared the performance of different machine learning algorithms in the classification problem in detail. Visual presentation of data improves the intuitiveness of data. In this study, one hundred thousand LAMOST DR6 spectral data were used for training, and different machine learning algorithms were used to evaluate the performance of various classifiers, and then correlation analysis was used to greatly improve the classification accuracy of specific categories on the basis of the original research, making the classification accuracy of galaxies and QSO is higher than 98%, which proves the validity of this research. Finally, various attributes of the classified celestial objects are displayed through visualization methods. © 2022 ieee.

关键词： Classification (of information)

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Bias-tunable broadband light-emitting/detecting devices based on the III-V nanowires on Si-substrate

Bias-tunable broadband light-emitting/detecting devices base...

引用

ieee Photonics conference (IPC)

作者： Huabin Yu Muhammad Hunain Memon Zhixiang Gao Yang Kang Yuanmin Luo Wei Chen Haiding Sun School of Microelectronics University of Science and Technology of China Hefei China

ISBN: (数字)9798350361957

ISBN: (纸本)9798350361964

We report a bias-controlled, superior dual-functional broadband light detecting and emitting diode enabled by constructing the III-IV-based nanowires on Si-platform. Based on the multifunctional features of the devices, we further employed them in various optoelectronic systems, demonstrating outstanding applications in DUV/NIR visualization systems.

关键词： visualization Switches Heterojunctions Silicon Hardware Nanowires Broadband communication III-V semiconductor materials Photonics Narrowband

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Imagery Analysis and Virtual visualization of Chinese Folk Song Hua'er 3

Imagery Analysis and Virtual Visualization of Chinese Folk S...

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3rd International conference on Education, Knowledge and information Management, ICEKIM 2022

作者： Xu, Yan Tang, QianQian Beijing Language and Culture University Blcu School of Information Science Beijing China

ISBN: (纸本)9781665416665

As an intangible cultural heritage, Hua'er is a type of folk song which is popular in Northwest China. Traditional researches of Chinese folk songs mainly use qualitative methods, which lack a quantitative perspective. In this paper, digital and computational methods are introduced into the research of Hua'er. Firstly, data mining methods are employed in analyzing the imagery of Hua'er in this research, and it is found that male and female images are often associated with different types of images. Secondly, a characteristic digital resource library of Hua'er has been constructed via virtual reality methods. This work is of great significance for the preservation and dissemination of the folk song Hua'er. © 2022 ieee.

关键词： Data mining

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Data analytics tools by alarms visualization and artificial intelligence applied in industrial monitoring

Data analytics tools by alarms visualization and artificial ...

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ieee IFAC International conference on Automation (ICA) / 24th Congress of the Chilean-Association-of-Automatic-Control (ACCA)

作者： Garces, Hugo O. Morales, Eduardo Espinosa, Eduardo Cabrera, Hans Rojas, Alejandro J. Arias, Luis Rivera, Paulo Carvajal, Gonzalo Fuentes, Andres Univ Catolica Santisima Dept Ingn Informat Concepcion Chile Univ Catolica Santisima Dept Ingn Elect Concepcion Chile Univ Concepcion Dept Ingn Elect Concepcion Chile Univ Tecn Federico Santa Maria Dept Elect Valparaiso Chile Univ Tecn Federico Santa Maria Dept Ind Valparaiso Chile

ISBN: (纸本)9781665401272

In process industries, the availability of large volumes of data is not directly related to the extraction of valuable information or process monitoring with good performance. Usually, data is directly visualized as tables or tendency graphics, being not used properly. This paper presents the design of process monitoring by considering the design of alarms visualization plots which provides useful information in a unique plot, combined with soft sensor design used for the prediction of critical variables which defines the process operational performance. Examples of two cases with real industrial data are provided to demonstrate the effectiveness and utility of these methods.

关键词： Analytics Artificial Intelligence Big Data Modeling Process monitoring

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R³LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package 39

R<SUP>3</SUP>LIVE: A Robust, Real-time, RGB-colored, LiDAR-I...

引用

ieee International conference on Robotics and Automation (ICRA)

作者： Lin, Jiarong Zhang, Fu

ISBN: (纸本)9781728196817

In this paper, we propose a novel LiDAR-InertialVisual sensor fusion framework termed R-3 LIVE, which takes advantage of measurement of LiDAR, inertial, and visual sensors to achieve robust and accurate state estimation. R3 LIVE consists of two subsystems, a LiDAR-Inertial odometry (LIO) and a Visual-Inertial odometry (VIO). The LIO subsystem (FAST-LIO) utilizes the measurements from LiDAR and inertial sensors and builds the geometric structure (i.e., the positions of 3D points) of the map. The VIO subsystem uses the data of Visual-Inertial sensors and renders the map's texture (i.e., the color of 3D points). More specifically, the VIO subsystem fuses the visual data directly and effectively by minimizing the frame-to-map photometric error. The proposed system R-3 LIVE is developed based on our previous work R-2 LIVE, with a completely different VIO architecture design. The overall system is able to reconstruct the precise, dense, 3D, RGBcolored maps of the surrounding environment in real-time (see our attached video(1)). Our experiments show that the resultant system achieves higher robustness and accuracy in state estimation than its current counterparts. To share our findings and make contributions to the community, we open source R3 LIVE on our Github(2).

关键词： visualization Three-dimensional displays Laser radar Streaming media Sensor fusion Robot sensing systems Real-time systems

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Identification of Sphere of Influence of single and multiple DG Units through Visualisation in Distribution Networks

Identification of Sphere of Influence of single and multiple...

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2022 ieee Global conference on Computing, Power and Communication Technologies, GlobConPT 2022

作者： Nigar, Yasmin Agalgaonkar, Ashish. P. Muttaqi, Kashem M. School of Electrical Computer and Telecommunications Engineering University of Wollongong NSW2522 Australia

ISBN: (数字)9781665493659

ISBN: (纸本)9781665493659

The world is transitioning to utilise distributed generation (DG) to reduce social, economic and environmental effects. As DG penetration is increasing, the need of determining the associated impacts on distribution networks is vital. This paper proposes a concept around sphere of influence of single and multiple DG units through line current analysis and Sankey visualisation. The advantage of the proposed method is it acts as a visual lens to study the network and take necessary actions based on the outcomes. The proposed method is tested using 33 bus distribution network and visualisation is carried out using python library. © 2022 ieee.

关键词： visualization

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