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检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

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Learning Joint Twist Rotation for 3D Human Pose Estimation from a Single Image 16

Learning Joint Twist Rotation for 3D Human Pose Estimation f...

引用

16th international Joint conference on computer vision, Imaging and computer Graphics Theory and Applications (VISIGRAPP) / 16th international conference on computer vision Theory and Applications (VISAPP)

作者： Nakatsuka, Chihiro Xu, Jianfeng Tasaka, Kazuyuki KDDI Res Inc Saitama Japan

ISBN: (纸本)9789897584886

We consider monocular 3D human pose estimation with joint rotation representations because they are more expressive than joint location representations and better suited to some applications such as CG character control and human motion analysis in sports or surveillance. Previous approaches have encountered difficulties when estimating joint rotations with actual twist rotation around limbs. We present a novel approach to estimating joint rotations with actual twist rotations from a single image by handling joint rotations separately decomposed into swing and twist rotations. To extract twist rotations from an image, we emphasize the joint appearances and use them effectively in our model. Our model estimates the twist angles with an average radian error of 0.14, and we show that estimation of twist rotations achieves a more precise 3D human pose.

关键词： 3D Human Pose Estimation Learning Joint Twist Rotation Swing-twist Decomposition

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Towards Deep Learning-Based Classification of Multiple Gestures using Sonomyography for Prosthetic control Applications

Towards Deep Learning-Based Classification of Multiple Gestu...

引用

Electrical, computer, Communications and Mechatronics Engineering (ICECCME), international conference on

作者： S. Manikandan A. S. Prasad Biswarup Mukherjee Pradeeba Sridar Centre for Biomedical Engineering Indian Institute of Technology Delhi Delhi India Department of Mechanical Engineering Indian Institute of Technology Delhi Delhi India

Intuitive control of multi articulated prosthetic devices remains a challenge due to inherent shortcomings in surface electromyography-based control modalities. As a result, sonomyography or ultrasound imaging-based methods of muscle activity sensing and control of bionics devices have emerged as an attractive alternative to traditional myoelectric control methodologies. However, most sonomyography-based techniques involve extraction and analysis of image features from B-mode ultrasound images to predict gestures. Additionally, ultrasound probe shift during the experiment has a detrimental effect on prediction accuracies. Therefore, to address these challenges we develop a deep-learning-based method to automatically identify four hand gestures: hand open, power grasp, index pointing, and tripod. Hand orientation variations were included by performing lateral and transverse hand movement, wrist supination, and pronation. We fine-tuned four deep-learning models (AlexNet, ResNet18, DarkNet19, and VGG16) using 4000 2D ultrasound images of forearm muscle deformation. Results show that a fine-tuned VGG16 outperformed other architectures by achieving 98.7 % cross-validation accuracy.

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LiDAR-Based 3D Reconstruction for Robotic Pipelines Inspection 11

LiDAR-Based 3D Reconstruction for Robotic Pipelines Inspecti...

引用

11th international conference on Geographical Information Systems Theory, Applications and Management, GISTAM 2025

作者： Kawka, Monika Sara Grammatikopoulos, Lazaros Kalisperakis, Ilias Stentoumis, Christos Michail Mela 21 Athens Greece Department of Surveying and Geoinformatics Engineering University of West Attica Agiou Spiridonos 28 Egaleo Greece

ISBN: (纸本)9789897587412

Robotic platforms have transformed pipe inspection from routine checks into an automatic data-driven process. Such robotic systems often integrate computer vision technology to collect and analyze inspection data in an automated and efficient way and offer additional capabilities such as 3D reconstruction of pipes and precise measurement of deformations (e.g., dents, buckling). This work presents an initial case study of a robotic inspection system equipped with LiDAR and camera sensors capable of performing automatic pipeline inspections. This proof-of-concept study is dedicated to the 3D reconstruction of the pipeline using LiDAR data collected during inspections. Reconstruction accuracy is evaluated by computing the RMSE for pipe surface reconstruction and the deviation from the reference diameter of a single pipe in a controlled laboratory setting. Reconstruction results reach an accuracy higher than 2cm based on computed RMSE and a precision higher than 0.5cm in pipe diameter estimation. The current implementation is limited to the inspection of matte and non-reflective pipes. Still, it offers a straightforward and scalable solution for various industrial sectors. Future work will incorporate camera data to integrate color mapping into the 3D reconstruction model and detect potential defects and deformations in a pipe. © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Industrial robots

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Battery Health Management Based on Digital Twin Technology

Battery Health Management Based on Digital Twin Technology

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Energy and Power Engineering, control Engineering (EPECE), international conference on

作者： Li Li Can Li Can Chen Yang Li Ying Wang Xuelian Yang Dongchang Li State Grid Information & Telecommunication Branch Beijing China Beijing Kedong Electric Power Control System Co. Ltd Beijing China

ISBN: (数字)9798350366099

ISBN: (纸本)9798350366105

As the infrastructure of the computer room, the battery has an urgent need for digitization and unification, and the digital twin technology can support the digital operation of various services in the power communication network. This paper introduces a battery health management system based on digital twin technology. The system has the functions of standardized modeling, battery position relationship display and battery health management. The system uses the digital twin technology to complete the digital conversion of the battery system, improves the service life of the battery, improves the monitoring mode of the battery, and further reduces the workload of the operation and maintenance personnel. It is expected to play an important role in the future computer room.

关键词： Training Power engineering Computational modeling Physical layer Data models Batteries Digital twins

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E2SIFT: Neuromorphic SIFT via Direct Feature Pyramid Recovery from Events

E2SIFT: Neuromorphic SIFT via Direct Feature Pyramid Recover...

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IEEE international conference on Image Processing

作者： Chris Henry Paras Maharjan Zhu Li George York Department of Computer Science and Electrical Engineering University of Missouri–Kansas City Academy Center for UAS Research United States Air Force Academy

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

In recent years, event cameras have achieved significant attention due to their advantages over conventional cameras. Event cameras have high dynamic range, no motion blur, and high temporal resolution. Contrary to traditional cameras which generate intensity frames, event cameras output a stream of asynchronous events based on brightness change. There is extensive ongoing research on performing computer vision tasks like object detection, classification, etc via the event camera. However, due to the unconventional output format of the event camera, it is difficult to perform computer vision tasks directly on the event stream. Mostly, works reconstruct the intensity image from the event stream and then perform such tasks. An important and crucial task is feature detection and description. Scale-invariant feature transform (SIFT) is a widely-used scale-invariant keypoint detector and descriptor that is invariant to transformations like scale, rotation, noise, and illumination. In this work, given an event voxel, we directly generate the LoG pyramid for SIFT keypoint detection. We fit a 3rd-degree polynomial and calculate the polynomial roots to compute the scale-space extrema response for SIFT keypoint detection. Since the extrema computation is performed after LoG thresholding, the solution is computationally less expensive. Experimental results validate the effectiveness of our system.

关键词： Thresholding (Imaging) Neuromorphics Detectors Transforms Streaming media vision sensors Cameras

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Optimization Algorithm for Centralized control System of conference Equipment Based on Artificial Intelligence

Optimization Algorithm for Centralized Control System of Con...

引用

Artificial Intelligence and Autonomous Robot Systems (AIARS), international conference on

作者： Chao Yuan Hengjie Liu Xiuzhen Jiang Lianzhen Zheng Ziqi Zhao State Grid Laiwu Power Supply Company Jinan Shandong China

ISBN: (数字)9798350376173

ISBN: (纸本)9798350376180

With the rapid growth of technology, the era of network information has led to an increasing demand for communication among people, and the means of communication have also undergone earth shaking changes. To meet the various forms of international and domestic conference exchange needs, major enterprises around the world have introduced various advanced multimedia intelligent conference equipment and created various forms of conference halls. However, with the continuous growth of mainstream multimedia conferences, equipment maintenance issues, human-computer interaction issues, and resource utilization issues have gradually become prominent, becoming key factors that constrain conference efficiency and experience. In order to effectively address these challenges, this article proposes an optimization algorithm for a centralized control system of conference equipment based on artificial intelligence (AI). This algorithm utilizes advanced technologies such as deep learning (DL) and the Internet of Things (loT) to achieve automatic recognition, configuration, status monitoring, and intelligent scheduling of conference equipment. By collecting and analyzing device and user data in real-time, algorithms can automatically optimize device settings, improve human-computer interaction efficiency, and allocate device resources reasonably to ensure the smooth progress of meetings. The experimental results show that the algorithm can significantly improve the management efficiency and user experience of conference equipment.

关键词： Human computer interaction Earth User experience Scheduling Real-time systems Maintenance Resource management Optimization Monitoring Centralized control

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Review on Transfer Learning for Convolutional Neural Network 3

Review on Transfer Learning for Convolutional Neural Network

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3rd international conference on Advances in Computing, Communication control and Networking, ICAC3N 2021

作者： Kaur, Rajdeep Kumar, Rakesh Gupta, Meenu Chandigarh University Computer Science and Engineering Department Gharuan India

ISBN: (纸本)9781665438117

Convolutional neural network (CNN) has recently received much interest from researchers as an image classification technique. CNN requires a lot of data to train a model from scratch, but in some application areas data is limited which results in an overfitting problem. This study focuses on current research publications that employ Transfer Learning (TL) to overcome the problem of limited data to train the CNN model. TL is a machine learning approach in which the knowledge of the pre-trained model is reused to solve the other problem. Further, this paper presents a review of pre-trained models such as AlexNet, VGG, ResNet, GoogleNet which are used in image classification tasks in different application areas. Two main TL strategies are discussed, first Feature Extractor in which all layers of the pre-trained model are frozen and second Fine-Tuning in which some of the layers are frozen and some are trainable. This review paper focuses on the concepts related to TL and TL strategies used to train the new task models with the help of pre-trained models. © 2021 IEEE.

关键词： Convolutional neural networks

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An Interdisciplinary Perspective on Mis/Disinformation control

An Interdisciplinary Perspective on Mis/Disinformation Contr...

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Electrical, computer, Communications and Mechatronics Engineering (ICECCME), international conference on

作者： Kevin Matthe Caramancion Mathematics Statistics and Computer Science Department University of Wisconsin–Stout Menomonie Wisconsin United States

Existing studies from a wide breadth of fields surrounding fake news and their controls are mostly siloed from proposals from other domains. This design yields a limited perspective on mis/disinformation controls resulting in an incomplete and ineffective approach. In this work, we employ a two-part qualitative method to solicit opinions regarding their perspective in building solutions to mis/disinformation. We assembled a seven-member assembly of experts from various fields: computer and information sciences, artificial intelligence, cybersecurity, laws and policies, psychology, telecommunication, and education. They participated in a US Supreme Court style study design, namely focus group discussions and Delphi opinion collection, to recommend an interdisciplinary solution to the phenomenon of fake news. Findings indicate that user education and social media awareness should sit at the center of every solution to fortify the cognitive ability of humans against cyber deception. Future forms of mistruths will evolve, made possible by AI, and their respective solutions should too. The classic fortification dimension, however, even in the future solutions should be the human ability to discern legitimate news from falsehoods.

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A 3D/2D Coronary Artery Registration Method Based on Deep Reinforcement Learning

A 3D/2D Coronary Artery Registration Method Based on Deep Re...

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computer, control and Robotics (ICCCR), international conference on

作者： Jun Yan Zhuang Fu Zeyu Fu Yisheng Guan School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China School of Electromechanical Engineering Guangdong University of Technology Guangzhou China

At present, vascular interventional surgery mainly depends on the conventional coronary angiography (CCA) and coronary computed tomography angiography (CCTA). However, due to various reasons such as different imaging principles and different operation methods, both CCA and CCTA imaging technologies can only be used separately. In order to integrate the two kinds of medical image information, medical image registration technologies based on artificial intelligence have emerged. In this paper, we propose a 3D/2D coronary artery registration method based on the combination of feature and deep reinforcement learning. Based on the centerline feature, we perform a projection transformation to unify the dimensions between two modes, then design a deep reinforcement learning algorithm, complete the mapping of the state space by convolutional neural network (CNN), discretize the actions of the agent, and use the Euclidean distance to define the reward function for fine coronary artery registration. The method is used for experiments with clinical CCA and CCTA data sets, and compared with other registration algorithms. The results show that the registration error rate of the proposed method is lower than that of other algorithms, it has strong accuracy and robustness, and can handle the registration problems of complex vascular segments.

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Design of near-infrared photoelectric thin film devices based on Macleod software

Design of near-infrared photoelectric thin film devices base...

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Power Electronics, computer Applications (ICPECA), IEEE international conference on

作者： Ying Zhao Changchun College of Electronic Technology Changchun China

With the development of modern optics, the application of infrared optical system is increasing day by day, and more and more optical devices require the working band in the near infrared region, which makes the development of high-performance infrared transmittance film become an important part of optical research. In this paper, an antireflective film with transmittance higher than 99% at 400-800nm was designed on K9 glass by using the software of film system design. According to the theoretical basis of optical film, the reflectivity of antireflection film is obtained by analyzing the admittance function of antireflection film. Using TiO 2 as the coating material with high refractive index and SiO 2 as the coating material with low refractive index, the near-infrared antireflection film with T≥99% was designed, and the total thickness of the film layer was 1660.07nm. The design results meet the requirements of technical indicators.

关键词： Surface cleaning Glass Optical variables control Surface roughness Software Rough surfaces Optical films

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