检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Li, Feiran Xu, Qianqian Bao, Shilong Yang, Zhiyong Cong, Runmin Cao, Xiaochun Huang, Qingming Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Institute of Information Science Beijing Jiaotong University Beijing China School of Control Science and Engineering Shandong University Jinan China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Cyber Science and Tech. Sun Yat-Sen University Shenzhen Campus China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

This paper explores the size-invariance of evaluation metrics in Salient Object Detection (SOD), especially when multiple targets of diverse sizes co-exist in the same image. We observe that current metrics are size-sensitive, where larger objects are focused, and smaller ones tend to be ignored. We argue that the evaluation should be size-invariant because bias based on size is unjustified without additional semantic information. In pursuit of this, we propose a generic approach that evaluates each salient object separately and then combines the results, effectively alleviating the imbalance. We further develop an optimization framework tailored to this goal, achieving considerable improvements in detecting objects of different sizes. Theoretically, we provide evidence supporting the validity of our new metrics and present the generalization analysis of SOD. Extensive experiments demonstrate the effectiveness of our method. The code is available at https://***/Ferry-Li/SI-SOD. Copyright © 2024, The Authors. 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

Design and 3D Printing of Lower Limb Prosthetic Socket *

Design and 3D Printing of Lower Limb Prosthetic Socket *

引用

IEEE International Conference on Cyborg and Bionic systems (CBS)

作者： Sheng Li Bin Xie Ye Chen Xinyu Wu Guoxin Fang Yan Zhang Fei Gao Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Shien-Ming Wu School of Intelligent Engineering South China University of Technology Guangzhou China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China State Key Laboratory of Powder Metallurgy Central South University Changsha Hunan China

ISBN: (数字)9798350388039

ISBN: (纸本)9798350388046

The prosthetic socket is a crucial interface connecting the residual limb to the prosthetic device, significantly affecting force transmission and wearer comfort. This work presents a comprehensive framework for design, simulation, and fabrication of the prosthetic socket. A 3D model of the residual limb, including the skeleton model and skin contour, is reconstructed from CT scan data. Using this model, the prosthetic socket and liner are designed based on biomechanical principles. The interaction force between the residual limb and the prosthetic socket and liner is simulated via finite element analysis (FEA) when the body weight of a below-knee amputee exerts on the prosthetic socket. Finally, the prosthetic socket and residual limb are fabricated using additive manufacturing (AM) technology, and a soft prosthetic liner is made of ethylene-vinyl-acetate (EVA) polymer. Clinical trials on a below-knee amputee were conducted to preliminarily test the prosthetic socket’s performance.

关键词： Limbs Solid modeling Sockets Biological system modeling Force Three-dimensional printing Skin Data models Finite element analysis Prosthetics

来源：评论

学校读者我要写书评

暂无评论

An Obstacles Avoidance Algorithm Based on Improved Artificial Potential Field

An Obstacles Avoidance Algorithm Based on Improved Artificia...

引用

IEEE International Conference on Mechatronics and Automation

作者： Si Xi Lu En Li Rui Guo School of Artificial Intelligence University of Chinese Academy of Sciences No.19(A) Yuquan Road Beijing China The State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Science 95 East ZhongGuanCun Road Beijing China State Grid Shandong Electric Power Company Jinan China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

Obstacle avoidance is one of the most important issue in the motion planning and control of robot. There are many algorithms to avoid obstacles, but obstacle avoidance algorithm for manipulator is needed consider not only end effector, but also all links of manipulator. In terms of real-time and speed of all system, the algorithm also should be easy as possible. In this paper, an algorithm based on the improved artificial potential field is proposed to solve the problem of the local optimum. The idea of improvement is to find a path by fitting curve with target point and critical oscillating points. There is also a comparison in this paper with planning a path by tangent line. The conclusion proves that the path is much smoother by the algorithm based on improved artificial potential field in this paper. Furthermore, the problem of judder on the trajectory of traditional artificial potential field is also solved in this paper by an improved repulsive potential field function. Finally, the algorithm is proved by planning a smooth path for obstacle avoidance on manipulator: KinovaGen3 in MATLAB.

关键词： Mechatronics Fitting End effectors Real-time systems Planning Trajectory Collision avoidance

来源：评论

学校读者我要写书评

暂无评论

Gvi: Guideable Visual Interpretation on Medical Tomographic Images to Improve the Performance of Deep Network

SSRN

引用

SSRN 2024年

作者： Liu, Hui Wei, Fan Yan, Lixin Wang, Sushan Jia, Chongfu Zhang, Lina Peng, Jiansheng Xu, Yi School of Control Science and Engineering Dalian University of Technology Dalian China Liaoning Key Laboratory of Integrated Circuit and Biomedical Electronic System Dalian China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China Department of Cardiovascular Radiology The First Affiliated Hospital of Dalian Medical University Dalian China Department of Radiology The First Affiliated Hospital of Dalian Medical University Dalian China Department of Artificial Intelligence and Manufacturing Hechi University Hechi China

In medical image analysis, the demand for interpretable deep neural networks is rapidly growing. However, a major challenge is that most existing interpretative methods are applied after training, leading to a lack of integration with the model's learning process. As a result, these methods often fail to highlight regions within complex medical images critical for decision-making, such as abnormal tissues or lesions, which are essential for accurate diagnoses and treatment planning. This paper introduces Guided Visual Interpretation (GVI), a framework designed to enhance both the performance and interpretability of deep networks. Building on a deep network model with image-level labels, GVI incorporates a small amount of pixel-level annotations combined with attention mechanisms. These mechanisms facilitate visual interpretation through forward propagation, directing the model's focus to the most relevant regions. By aligning the network's decision-making with human cognitive processes, GVI improves interpretability. In our study, an attention layer was added after the convolutional layers of a pre-trained classification network. GVI is trained using a hybrid supervision approach that integrates pixel-level annotations with a large amount of image-level data. Experimental results on both private and public datasets show that GVI generates visual explanations consistent with human decision-making principles and achieves superior classification accuracy compared to traditional methods. These findings highlight GVI's potential to improve interpretability and diagnostic performance in critical fields like medical imaging. © 2024, The Authors. All rights reserved.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

Transformer-Based Fusion of RGB and Depth Images for Terrain Recognition

引用

Procedia Computer Science 2024年 250卷 22-29页

作者： Hui Chen Chunjie Chen Zhuo Wang Fangliang Yang Heng Pan Xinyu Wu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen 518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human–Machine Intelligence-Synergy Systems Shenzhen 518055 China

This research aims to explore key issues in the field of walking robots and exoskeletons. By using a depth camera to record human walking data in different terrains and employing RGB and depth information for image classification, our approach utilizes both early fusion and late fusion methods to explore their impact on terrain classification. This approach achieved fast and accurate performance in recognizing terrain. We captured data for walking upstairs, downstairs, upward ramps, downward ramps and level ground and used the vision transformer for data fusion. This work compares the performance of unimodal RGB model, unimodal deep model, Pre-Fusion model and Post-Fusion model in terms of accuracy, recall and processing frequency, with accuracies of 0.954, 0.934, 0.976, and 0.976, respectively. The results show that the Post-Fusion model slightly outperforms the Pre-Fusion model in terms of accuracy and recall with more reliable classification performance. To understand the attention mechanism better, we've been visualizing the weights of the model, observing how different attention heads may capture different features of the data from various dimensional perspectives. The visualization helps in interpreting the model's focus and how it distinguishes between features of different nature, such as color texture and spatial depth. These findings can inform the ongoing refinement of terrain classification systems for applications in robotics and autonomous navigation.

关键词： Multimodal fusion terrain recognition vision transformer depth camera

来源：评论

学校读者我要写书评

暂无评论

Acoustic and Kinematic Examination of Dysarthria in Cantonese Patients of Parkinson’s Disease

Acoustic and Kinematic Examination of Dysarthria in Cantones...

引用

International Symposium on Chinese Spoken Language Processing

作者： Yue Sun Manwa L. Ng Chongyuan Lian Lan Wang Feng Yang Nan Yan College of Big Data and Information Engineering Guizhou University Guiyang China Speech Science Laboratory University of Hong Kong Hong Kong China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Department of Speech Therapy Shenzhen Children’s Hospital Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Instimtes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781538656280;9781538656273

Hypokinetic dysarthria is one of the core symptoms of Parkinson's disease, characterized by reduced loudness, slurred speech and distorted consonant productions. Dopaminergic medication for Parkinson's disease (PD) has been proven to be effective in treating limb and gross motor movement problems. However, the literature sees contradictory findings regarding dopaminergic effects on speech problems associated with PD. Previous perceptual and acoustic studies of PD hypokinetic dysarthria mostly involved heterogeneous population and variations of speech tasks which complicated data interpretation. Also, the lack of kinematic data limited our understanding of the details of articulation errors associated with PD, as well as the medication effects. Electromagnetic articulography (EMA) enabled the examination of PD articulatory patterns with high degree of accuracy and safety. The aim of the present study was to address these inconsistencies by providing an integrative description of basic kinematic and acoustic parameters of speech production about the dopaminergic effect on early PD speech by using EMA. The results revealed a significant improvement of articulatory function on dopaminergic effects for PD speech, evidenced by increased vowel space, the velocity and accelerated velocity initiation and coordination of articulation during bilabial or alveolar productions.

关键词： Kinematics Acoustics Auditory system Sun Parameter extraction Schedules Lips

来源：评论

学校读者我要写书评

暂无评论

Joint Association, Beamforming, and Resource Allocation for Multi-IRS Enabled MU-MISO systems With RSMA

arXiv

引用

arXiv 2024年

作者： Wang, Chunjie Zhang, Xuhui Xing, Huijun Xue, Liang Wang, Shuqiang Shen, Yanyan Yang, Bo Guan, Xinping Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China School of Information and Electrical Engineering Hebei University of Engineering Handan056038 China Hebei Key Laboratory of Security and Protection Information Sensing and Processing Handan056038 China Shenzhen Future Network of Intelligence Institute The School of Science and Engineering The Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Guangdong Shenzhen518172 China Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom Shenzhen Future Network of Intelligence Institute The Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Guangdong Shenzhen518172 China Department of Automation The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China

Intelligent reflecting surface (IRS) and rate-splitting multiple access (RSMA) technologies are at the forefront of enhancing spectrum and energy efficiency in the next generation multi-antenna communication systems. This paper explores a RSMA system with multiple IRSs, and proposes two purpose-driven scheduling schemes, i.e., the exhaustive IRS-aided (EIA) and opportunistic IRS-aided (OIA) schemes. The aim is to optimize the system weighted energy efficiency (EE) under the above two schemes, respectively. Specifically, the Dinkelbach, branch and bound, successive convex approximation, and the semidefinite relaxation methods are exploited within the alternating optimization framework to obtain effective solutions to the considered problems. The numerical findings indicate that the EIA scheme exhibits better performance compared to the OIA scheme in diverse scenarios when considering the weighted EE, and the proposed algorithm demonstrates superior performance in comparison to the baseline algorithms. Copyright © 2024, The Authors. All rights reserved.

关键词： Beamforming

来源：评论

学校读者我要写书评

暂无评论

UAV-Enabled Data Collection for IoT Networks via Rainbow Learning

arXiv

引用

arXiv 2024年

作者： Jiao, Yingchao Zhang, Xuhui Liu, Wenchao Wu, Yinyu Ren, Jinke Shen, Yanyan Yang, Bo Guan, Xinping Chinese Academy of Sciences Guangdong518055 China The University of Chinese Academy of Sciences Beijing100049 China The Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Guangdong Shenzhen518172 China The SIAT Chinese Academy of Sciences Guangdong518055 China The Department of Automation The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China

Unmanned aerial vehicles (UAVs) assisted Internet of things (IoT) systems have become an important part of future wireless communications. To achieve higher communication rate, the joint design of UAV trajectory and resource allocation is crucial. This letter considers a scenario where a multi-antenna UAV is dispatched to simultaneously collect data from multiple ground IoT nodes (GNs) within a time interval. To improve the sum data collection (SDC) volume, i.e., the total data volume transmitted by the GNs, the UAV trajectory, the UAV receive beamforming, the scheduling of the GNs, and the transmit power of the GNs are jointly optimized. Since the problem is non-convex and the optimization variables are highly coupled, it is hard to solve using traditional optimization methods. To find a near-optimal solution, a double-loop structured optimization-driven deep reinforcement learning (DRL) algorithm and a fully DRL-based algorithm are proposed to solve the problem effectively. Simulation results verify that the proposed algorithms outperform two benchmarks with significant improvement in SDC volumes. Copyright © 2024, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Adversarial Learning Network for Recovering Rppg Signals from Low-Resolution Images for Remote Heart Rate Measurement

SSRN

引用

SSRN 2024年

作者： Zhai, Dezhao Chen, Wei Li, Qinwei Yu, Ming Wu, Hang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Systems Engineering Institute Academy of Military Sciences People's Liberation Army Tianjin300161 China Tianjin Key Laboratory for Advanced Signal Processing Civil Aviation University of China Tianjin300300 China School of Artificial Intelligence Nankai University Tianjin300381 China

Remote Photoplethysmography (rPPG) is a non-contact method for measuring heart rate (HR) through facial video, which has significant research value and application potential. However, in long-distance vital sign measurement tasks, the low resolution of facial images and insufficient pixels in the facial region severely degrade the quality of the rPPG signals, leading to a sharp decline in HR accuracy. To address this issue, this paper proposes an adversarial learning network for recovering rPPG signals from low-resolution images (ALRSL-HR). First, arbitrary resolution face images are fed into multi-channel network to extract rPPG signal features capturing rich rPPG information, generating rPPG feature blocks, and temporally aggregating for richer feature representation. These features are then inputted into the backbone network to generate adversarial examples of rPPG signals of varying qualities. Finally, a two-stage adversarial loss function is employed to enable the low-quality rPPG signals to learn the periodic characteristics of high-quality rPPG signals, recover the low-quality signals, and narrow the quality gap between rPPG signals from low-resolution images. Extensive experiments were conducted in this paper to validate the effectiveness of our model on the public COHFACE, UBFC-Phys and UBFC-rPPG datasets. The results of the experiments demonstrate that the proposed ALRSL-HR model can effectively recover degraded rPPG signals from low-resolution images. © 2024, The Authors. All rights reserved.

关键词： Photoplethysmography

来源：评论

学校读者我要写书评

暂无评论

Self-triggered control of heterogeneous multiagent systems with input saturation

Self-triggered control of heterogeneous multiagent systems w...

引用

Chinese control Conference (CCC)

作者： Shengli Du Di Wu Yongfeng Gao Xu Li Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing P. R. China School of Control Science and Engineering Dalian University of Technology Dalian P. R. China School of Aeronautics and Astronautics Dalian University of Technology Dalian P. R. China

This paper is concerned with the semi-global output synchronization problem of a heterogeneous network under self-triggered control. A distributed self-triggered control scheme in which only local information is used to compute the triggering instants is proposed. In addition, the Zeno behavior can be excluded in the designed scheme. By adopting the low-gain technique, it is shown that the input saturation nonlinearity can be avoided if the parameter of the parameterized feedback gain is chosen small enough. The algorithm for implementing the self-triggered rule is also presented in the paper.

关键词： Multi-agent systems Synchronization Eigenvalues and eigenfunctions control systems Laplace equations Symmetric matrices Riccati equations

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：