检索结果-内蒙古大学图书馆

IEEE Transactions on Artificial intelligence 2021年第5期2卷 424-436页

作者： Li, Guoxin Li, Zhijun Li, Junjun Liu, Yueyue Qiao, Hong The Department of Automation University of Science and Technology of China Hefei230026 China The Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230026 China The School of Automation Science and Engineering South China University of Technology Guangzhou511442 China The State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Science Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The Center for Excellence in Brain Science and Intelligence Technology Institute of Neuroscience Chinese Academy of Science Shanghai200031 China

Upper limb loss has significant effects on the individual's quality of life. Artificial prosthetic limbs as an alternative to the lost limb are designed to allow amputees to regain motor function. Motion classification via extracted surface electromyogram (sEMG) signals is widely utilized to realize a friendly human-robot interface in the control of the prosthesis. However, limited classification of discrete motion patterns from sEMG prevents intuitive motor control. Thus, instead of using discrete patterns, decoding the human intention continuously from sEMG would significantly benefit the prosthesis control. In this article, we propose a muscle-synergy-based intention decoding and motion planning that can model a broad set of complex upper limb movements as a combination of motor primitives. A novel muscle activation-to-force mapping model is developed to detect muscular effort of the healthy side to drive the affected side. A neural-network-approximation-based controller is developed for the bionic neuroprosthetic arm to execute the movement. Operational experiments with prosthetic movement control were performed on four healthy participants and an upper limb amputee participant. Results of controlling prosthetic arm (0.94 ± 0.02 of R2 in the horizontal reaching tasks and 0.95 ± 0.01 in the vertical reaching tasks for the healthy subjects, 0.95 and 0.97 for the amputee) demonstrate that our control method could successfully capture human movement intention and effectively control the movement of prosthesis. Impact Statement-Powered robotic prostheses have enabled individuals with limb amputations to regain motor function via motion intention decoding from extracting surface electromyogram signals. Most research works have provided human-robot interaction through motion classification obtained from pattern recognition using surface electromyogram signals and simple movement control. However, decoding the human intent continuously from surface electromyogram is con

关键词： Matrix algebra

来源：评论

学校读者我要写书评

暂无评论

Fast Coding Mode Prediction for Intra Prediction in VVC SCC

Fast Coding Mode Prediction for Intra Prediction in VVC SCC

引用

IEEE International Conference on Image Processing

作者： Dayong Wang Junyi Yu Xin Lu Frederic Dufaux Hongwei Guo Hui Guo Ce Zhu Chongqing Key Laboratory on Big Data for Bio Intelligence Chongqing University of Posts and Telecommunications Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Faculty of Computing Engineering and Media (CEM) De Montfort University Université Paris-Saclay CNRS CentraleSupélec Laboratoire des signaux et systèmes School of Engineering Honghe University Mengzi Yunnan China University of Electronic Science and Technology of China

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Currently, screen content video applications are increasingly widespread in our daily lives. The latest Screen Content Coding (SCC) standard, known as Versatile Video Coding (VVC) SCC, employs screen content Coding Modes (CMs) selection. While VVC SCC achieves high coding efficiency, its coding complexity poses a significant obstacle to the further widespread adoption of screen content video. Hence, it is crucial to enhance the coding speed of VVC SCC. In this paper, we propose a fast mode and splitting decision for Intra prediction in VVC SCC. Specifically, we initially exploit deep learning techniques to predict content types for all CUs. Subsequently, we examine CM distributions of different content types to predict candidate CMs for CUs. We then introduce early skip and early terminate CM decisions for different content types of CUs to further eliminate unlikely CMs. Finally, we develop Block-based Differential Pulse-Code Modulation (BDPCM) early termination to improve coding speed. Experimental results demonstrate that the proposed algorithm can improve coding speed by $34.95 \%$ on average while maintaining almost the same coding efficiency.

关键词： Video coding Deep learning Image coding Modulation Prediction algorithms Complexity theory Copper

来源：评论

学校读者我要写书评

暂无评论

DriveRP: RAG and Prompt Engineering Embodied Parallel Driving in Cyber-Physical-Social Spaces

DriveRP: RAG and Prompt Engineering Embodied Parallel Drivin...

引用

Digital Twins and Parallel intelligence (DTPI), IEEE International Conference on

作者： Jun Huang Hao Ma Tengchao Zhang Fei Lin Siji Ma Xiao Wang Fei-Yue Wang Faculty of Innovation Engineering Macau University of Science and Technology Macau China School of Artificial Intelligence Anhui University Hefei China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

In recent years, numerous technological advancements in Artificial Generative intelligences (AGIs) have demonstrated significant potential to transform the intelligence acquisition mechanisms in connected autonomous vehicles (CAVs). Integrating technologies like ChatGPT into CAVs can enhance human-machine interactions. However, the emergence of such new traffic entities may introduce unforeseen hallucinations and complex risks that surpass our current understanding. To address these challenges, Retrieval-Augmented Generation (RAG) and prompt engineering technologies are being explored to enhance the reliability and safety of autonomous driving systems. RAG retrieves relevant contextual information, such as driving experiences and real-time road network status, from external databases to ensure that foundation models have access to accurate and timely data for informed decision-making. Prompt engineering optimizes the performance of large language models in autonomous driving systems by designing and refining prompts that guide the models’ responses, thereby improving their relevance and accuracy in various driving scenarios. Together, these technologies enhance the robustness and trustworthiness of autonomous driving systems. This paper proposes DriveRP, a framework that integrates RAG and prompt engineering within the Descriptive-Predictive-Prescriptive intelligence framework of Parallel Driving theory. DriveRP aims to enhance the safety and interpretability of autonomous vehicle trajectory planning, decision-making, and motion control, ultimately achieving the "6S" goals. Grounded in Digital Twins and Metaverse-embodied parallel driving theory, DriveRP provides the infrastructure and foundational intelligence for parallel driving with Multi-modal Large Lange Models(MLLMs). Additionally, the paper discusses future trends and potential research directions, focusing on the "6S" goals of parallel driving: Smart, Safe, Secure, Sensitive, Sustainable, and Serviceable.

关键词： Accuracy Trajectory planning Decision making Transportation Transforms Safety Digital twins Prompt engineering Motion control Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Exposure-NeuS: Multi-View Head Reconstruction Using Exposure-Distorted Data

Exposure-NeuS: Multi-View Head Reconstruction Using Exposure...

引用

Complex Systems and Intelligent Science (CSIS-IAC), International Annual Conference on

作者： Zhanliang Cheng Bo Peng Ning An School of Data Science University of Science and Technology of China Hefei China School of Mathematical Science University of Science and Technology of China Hefei China Research Institute of Mine Artificial Intelligence China Coal Research Institute Beijing China State Key Laboratory of Intelligent Coal Mining and Strata Control Beijing China

ISBN: (数字)9798331504755

ISBN: (纸本)9798331504762

We propose Exposure-NeuS, a high fidelity human head reconstruction method from multi-view images, even from exposure-distorted images. Previous methods either did not reconstruct with sufficient accuracy, such as failing to reconstruct hair, or resulted in artifacts or holes in the reconstructed results due to exposure in the input data. To solve these challenging problems, we improve the original fine sampling of the model by using piecewise power function sampling to obtain sampling points closer to the real surface. And we develop a prior latent code to implicitly model factors such as environment and exposure. Experiments show that we eliminate or reduce the erroneous facial depressions and hair holes that occur in the baseline method during reconstruction. Released code is provided as follows:https://***/zhanliangOO/***

关键词： Hair Surface reconstruction Head Codes Reconstruction algorithms Rendering (computer graphics) Depression Digital humans Complex systems Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Research on virtual human swarm football collaboration technology based on reinforcement learning

Research on virtual human swarm football collaboration techn...

引用

IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Xiaoshan Mo Bin Hu Caixu Xu Yuling Yang Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China Faculty of Arts and Humanities Macao University of Science and Technology Macao China

Reinforcement learning is used in many applications in artificial intelligence fields such as computer vision and environmental contextualized decision-making scenarios; virtual human swarms provide research directions for multi-intelligent body collaboration and environmental field detection in multi-intelligent body swarms. Football is a group sport, which is characterized by its holistic nature, confrontation, versatility, and ease of implementation, as well as the characteristics of both individual intelligence and group intelligence, and is a typical application scenario for multi-intelligence collaboration. This paper takes football as the research object to study the team collaboration problem and team gaming problem of the virtual human swarm in a specific environment and solves the cooperation and competition relationship between intelligence with reinforcement learning of multi-intelligence training.

关键词： Training Computer vision Decision making Collaboration Reinforcement learning Ubiquitous computing Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Distributed multi-timescale algorithm for nonconvex optimization problem: A control perspective

引用

Neural Networks 2025年 186卷 107257页

作者： Shi, Xiasheng Liu, Jian Sun, Changyin School of Artificial Intelligence Anhui University Hefei230106 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Automation Southeast University Nanjing210096 China

The distributed nonconvex constrained optimization problem with equality and inequality constraints is researched in this paper, where the objective function and the function for constraints are all nonconvex. To solve this problem from a control perspective, a virtual reference-based convex penalty function is added to the augmented Lagrangian function. Then, based on the primal–dual technique, a two-timescale distributed approach is designed based on the consensus scheme. The slower subsystem aims to ensure the optimality, and the faster subsystem intends to guarantee the stability. Finally, three cases are presented to illustrate the approach's effectiveness. © 2025 Elsevier Ltd

关键词： Consensus algorithm

来源：评论

学校读者我要写书评

暂无评论

A Subspace Sparsity Driven Knowledge Transfer Strategy for Dynamic Constrained Multiobjective Optimization

引用

IEEE Transactions on Evolutionary Computation 2025年

作者： Chen, Guoyu Guo, Yinan Li, Changhe Wang, Feng Gong, Dunwei Yuan, Liang Anhui University of Science and Technology School of Artificial Intelligence Hefei231131 China State Key Laboratory of Intelligent Coal Mining and Strata Control Beijing100013 China China University of Mining and Technology School of Mechanical and Electrical Engineering Beijing100083 China State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mine Huainan232001 China Wuhan University School of Computer Science Wuhan430072 China Qingdao University of Science and Technology School of Information Science and Technology Qingdao266061 China Anhui University of Science and Technology School of Safety Science and Engineering Huainan232001 China

Dynamic constrained multiobjective optimization problems (DCMOPs) require algorithms to quickly track the feasible Pareto optima under dynamic environments. The existing dynamic constrained multiobjective evolutionary algorithms (DCMOEAs) normally focus on the convergence speed, but cannot well guarantee distribution. To address this issue, a subspace sparsity driven knowledge transfer strategy based DCMOEA is developed in this article, called SSDKT. First, reference points are introduced to partition objective space into multiple subspaces. Subsequently, the feasibility of each subspace is determined by the distribution of all historical feasible optimal solutions in it, and defined as the sparsity of subspace. A predictor based on the gated recurrent unit (GRU) network is further constructed to estimate the sparsity under the future environment. Once a new environment appears, a subspace transfer strategy is designed to generate an initial population. In each feasible subspace, the GRU-based prediction method is developed and competed with Kalman filter to generate the initial solution under the new environment. Based on the predicted solution of the nearest feasible neighbor, a potential initial individual in each infeasible subspace is produced by transferring the corresponding knowledge. The experimental results on various benchmarks verify that, compared with several state-of-the-art DCMOEAs, the proposed algorithm achieves the most competitive performance in solving DCMOPs. © 1997-2012 IEEE.

关键词： Constrained optimization

来源：评论

学校读者我要写书评

暂无评论

Behavioral Intervention with Eye-Use Monitoring to Delay Myopia Onset and Progression in Children: A Cluster Randomized Trial

引用

Ophthalmology 2025年第6期132卷 701-712页

作者： Hu, Yuanyuan Yu, Mingkun Han, Xiaotong Congdon, Nathan Wu, Ziyun Liu, Jianping Liu, Zhaolan Huo, Huanhuan Song, Jike He, Mingguang Bi, Hongsheng Affiliated Eye Hospital of Shandong University of Traditional Chinese Medicine Shandong Academy of Eye Disease Prevention and Therapy Shandong Provincial Key Laboratory of Integrated Traditional Chinese and Western Medicine for Prevention and Therapy of Ocular Diseases Shandong Provincial Clinical Medical Research Center of Optometry and Children Visual Impairment Prevention and Control Shandong Engineering Technology Research Center of Visual Intelligence Shandong Institute of Children Health and Myopia Prevention and Control Shandong China Shandong University of Traditional Chinese Medicine Shandong China State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center SunYat-sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangdong Provincial Clinical Research Center for Ocular Diseases Guangzhou China Centre for Public Health Queen's University Belfast Belfast United Kingdom Ophthalmology and Optometry Medical School Shandong University of Traditional Chinese Medicine Shandong China Affiliated Yongchuan Hospital of Chongqing Medical University Chongqing China Centre for Evidence Based Chinese Medicine Beijing University of Chinese Medicine Beijing China Research Centre for SHARP Vision The Hong Kong Polytechnic University Hong Kong

Purpose: To assess the efficacy of a behavioral intervention using Eye-Use Monitoring technology to delay the onset and progression of myopia in children. Design: A prospective, cluster-randomized, parallel-groups, examiner-masked, clinical trial (Chinese Clinical Trial Registry, ChiCTR2100052101). Participants: A total of 413 children from grades 2 to 4 in Shandong, China, from October 2021 to December 2023 were randomized by class into 3 groups: reminder and feedback (6 classes, 156 children), reminder-only (5 classes, 147 children), and control (3 classes, 110 children). Children with prior myopia control interventions, significant eye conditions, or a history of eye diseases were excluded. Methods: The reminder-only group received simultaneous vibration alerts for prolonged near work, close proximity, head tilt, or inadequate lighting. The reminder and feedback group received these alerts plus behavioral feedback, including praise, rewards, and weekly reports. The control group received no intervention. The intervention lasted 49 weeks, followed by a 49-week observation period without intervention. Main Outcome Measures: The primary outcome was the mean change in cycloplegic spherical equivalent (SE) at 49 weeks. Secondary outcomes included changes in axial length (AL), myopia incidence, rates of rapid myopic shift, participant compliance, and eye-use behaviors. Results: At 49 weeks, changes in SE and AL were least in the reminder and feedback group (SE: 0.52 ± 0.35 diopters [D] vs. 0.59 ± 0.43 D vs. 0.73 ± 0.48 D, AL: 0.30 ± 0.14 mm vs. 0.33 ± 0.16 mm vs. 0.40 ± 0.20 mm, in reminder and feedback group, reminder only group, and control group, respectively, both P < 0.001). Myopia incidence was lowest in the reminder and feedback group (13.3% vs. 21.6% vs. 27.8%, in reminder and feedback group, reminder only group, and control group, respectively, P < 0.05). However, differences diminished by the 98-week follow-up. Conclusions: This study demonstrated that the co

关键词： Children Cluster randomized controlled trials Eye-use behaviors Myopia Spherical equivalent

来源：评论

学校读者我要写书评

暂无评论

A New Dynamic Routing Network for Monocular Depth Estimation 12

A New Dynamic Routing Network for Monocular Depth Estimation

引用

12th International Conference on CYBER technology in Automation, control, and Intelligent Systems, CYBER 2022

作者： Luo, Zhehao Luo, Sijin Liang, Guoyuan Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Province Shenzhen China University of Chinese Academy of Sciences Beijing China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences Guangdong Province Shenzhen China Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Province Shenzhen China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Depth estimation is an essential task for understanding the geometry of 3D scenes. Compared with multi-view-based methods, monocular depth estimation is more challenging for the requirement of integrating not only global information but also local cues from various parts. Recently, numerous Convolutional Neural Networks (CNNs) based approaches relying on pre-defined static architectures have been reported. Although many of them have achieved remarkable improvements in accuracy, there remains problem with the generality of the static model when it comes to diverse scenes. In this paper, a novel deep network with dynamic routing architecture is proposed with a dynamically adjustable structure with respect to different inputs, therefore leading to not only improvements on both accuracy and generality but also decrease of the model parameters. Extensive experiments of monocular depth estimation have been conducted on two well-known challenging datasets (i.e., NYUD-v2 and Make3D) as well as the mixed dataset, and have verified the effectiveness of the proposed dynamic framework. © 2022 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Attention Mechanism and Detection Box Information Based Real-time Multi-Object Vehicle Detection

引用

Journal of Computing and Information technology 2022年第4期30卷 239-256页

作者： Wu, Hao Wu, Wei Sun, Xiaoyan Zhong, Jin Cao, Fengyun School of Computer Science and Technology Hefei Normal University Hefei China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Universities Joint Key Laboratory of Photoelectric Detection Science and Technology in Anhui Province Hefei China Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention Hefei China School of Economics and Trade Anhui Business and Technology College Hefei China

Ensuring both the accuracy of vehicle target detection and meeting real-time requirements is crucial in traffic videos. The YOLOv5s target detection frame-work, known for its accuracy and efficiency, has at-tracted attention in academic circles. However, there are still some features that can be optimized. First of all, the detection subnet of the YOLOv5s framework cannot smoothly convert complex feature maps into relatively sparse target prediction boxes. To solve this, we integrate a self-attention-based gating mechanism into the detection subnet, forming the YOLOv5s-SAG network. Secondly, the loss function of CIoU used by YOLOv5s pays insufficient attention to the overlap-ping area of the detection frame, which can be used as metric for measuring target detection effectiveness. We add the loss term of area ratio to CIoU to further improve the modeling ability. Finally, the current multi-class Non-Maximum Suppression algorithm can cause high overlap of multi-class detection frames. To improve it, we propose a multi-class CS-NMS algorithm based on category suppression. Experimental results show an approximately 8% improvement in the mAP50 index on the UA-DETRAC dataset compared with YOLOv5s. The proposed algorithm also achieves better detection results compared to mainstream target detection algorithms and meets the real-time requirements of traffic video analysis. © 2022, university of Zagreb Faculty of Electrical Engineering and Computing. All rights reserved.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：