检索结果-内蒙古大学图书馆

IEEE International Conference on Robotics and Automation (ICRA)

作者： Wenhua Wu Guangming Wang Jiquan Zhong Hesheng Wang Zhe Liu MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Insititute of Medical Robotics Shanghai Jiao Tong University Shanghai China

Depth estimation is one of the most important tasks in scene understanding. In the existing joint self-supervised learning approaches of depth-pose estimation, depth estimation and pose estimation networks are independent of each other. They only use the adjacent image frames for pose estimation and lack the use of the estimated geometric information. To enhance the depth-pose association, we propose a monocular multi-frame unsupervised depth estimation framework, named PLPE-Depth. There are a depth estimation network and two pose estimation networks with image input and pseudo-LiDAR input. The main idea of our approach is to use the pseudo-LiDAR reconstructed from the depth map to estimate the pose of adjacent frames. We propose depth re-estimation with a better pose between the image pose and the pseudo-LiDAR pose to improve the accuracy of estimation. Besides, we improve the reconstruction loss and design a pseudo-LiDAR pose enhancement loss to facilitate the joint learning. Our approach enhances the use of the estimated depth information and strengthens the coupling between depth estimation and pose estimation. Experiments on the KITTI dataset show that our depth estimation achieves state-of-the-art performance at low resolution. Our source codes will be released on https://***/IRMVLabIPLPE-Depth.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Multi-Kernel Principal Component Analysis Method for Quality-Related Fault Detection

A Multi-Kernel Principal Component Analysis Method for Quali...

引用

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Lingxia Mu Biyu Lei Ding Liu School of Automation and Information Engineering Xi’an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China

ISBN: (纸本)9781665465373

In this paper, a multi-kernel principal component analysis (MKPCA) method for quality-related fault detection is proposed. The initial space is firstly mapped to a new space. The correlated information between the new space and output quality is then obtained by the kernel function. Meanwhile, with consideration of the advantage of global function and local function, a weight factor which combines them together is introduced to construct a multi-kernel function. In this way, the algorithm achieves better learning ability. The new space is projected to two mutually orthogonal subspaces, i.e., quality-related part and quality-unrelated part. In each subspace, fault information is expressed by different statistical indicators. The numerical example is presented to evaluate the performance of the MKPCA. The results show better reliability and high fault detection rate through proper spatial decomposition and kernel function construction.

关键词： Correlation Automation Fault detection Feature extraction Eigenvalues and eigenfunctions Reliability Matrix decomposition

来源：评论

学校读者我要写书评

暂无评论

Anti-occlusion Object Tracking Algorithm using Response Template Fusion and Combined Features

Anti-occlusion Object Tracking Algorithm using Response Temp...

引用

Chinese control and Decision Conference, CCDC

作者： Jing Wang Yuan Wei Yisong Liu Weichao Huang Ming Hu Faculty of Printing Packaging Engineerring And Digital Media Technology Xi’an University of Technology Xi’an China Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China

The kernel correlation filtering algorithm cannot judge the occlusion by itself when the object is occluded by foreign objects, and the tracking performance is greatly affected. Aiming at this problem, this paper proposes an anti-occlusion object tracking algorithm that fuses response templates and combined features. The peak sidelobe ratio (PSR) is used to determine whether the object is occluded. When the object is partially occluded, a combined feature representation object model is introduced to enhance robustness, and a multi-response template with anti-occlusion performance is constructed to improve the performance of the object when it is occluded by foreign objects. The problem of reducing the available information, thereby improving algorithm performance. Experiments in the OTB-100 data set can prove that the success rate and accuracy of the algorithm have competitive results compared with the comparison algorithms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design of Lifting Mechanism of Transfer Robot for the Elderly

Design of Lifting Mechanism of Transfer Robot for the Elderl...

引用

2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022

作者： Yang, Jing Song, Zhen Wu, Ruikai Wang, Jingchuan Dalian Polytechnic University China Min. of Educ. of China Shanghai Eng. Res. Ctr. of Intelligent Contr. and Mgmt. Inst. of Med. Robotics Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

With the intensification of the aging trend, the promotion of the design of aging facilities is conducive to improving the livelihood and welfare of the elderly and is of great significance to promoting the comprehensive, coordinated and sustainable development of the cause of aging. The transfer concept of the robot designed in this article is to enable the elderly and the disabled who are living at home to complete the actions of standing, transferring, and sitting like normal people. In view of the lack of analysis of the user's own body state in the current transfer assist equipment in the design process, the robot's lifting mechanism is optimized from the perspective of biomechanics, and finally the optimal size parameter combination of the robot's lifting mechanism is obtained. © 2022 IEEE.

关键词： Machine design

来源：评论

学校读者我要写书评

暂无评论

Oxidation Mechanism and Toxicity Evolution of Linalool,a Typical Indoor Volatile Chemical Product

引用

Environment & Health 2024年第7期2卷 486-498页

作者： Zihao Fu Song Guo Ying Yu Hong-Bin Xie Shiyu Li Daqi Lv Putian Zhou Kai Song Zheng Chen Rui Tan Kun Hu Ruizhe Shen Maosheng Yao Min Hu State Key Joint Laboratory of Environmental Simulation and Pollution Control International Joint Laboratory for Regional Pollution ControlMinistry of Education(IJRC)College of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing 210044China Key Laboratory of Industrial Ecology and Environmental Engineering(Ministry of Education) School of Environmental Science and TechnologyDalian University of TechnologyDalian 116024China Institute for Atmospheric and Earth System Research/Physics Faculty of ScienceUniversity of HelsinkiP.O.Box 64FIN-00014 HelsinkiFinland

Linalool,a high-reactivity volatile chemical product(VCP)commonly found in cleaning products and disinfectants,is increasingly recognized as an emerging contaminant,especially in indoor *** the gas-phase oxidation mechanism of linalool is crucial for assessing its impact on atmospheric chemistry and human *** quantum chemical calculations and computational toxicology simulations,we investigated the atmospheric transformation and toxicity evolution of linalool under low and high NO/HO_(2)·levels,representing indoor and outdoor *** findings reveal that linalool can undergo the novel mechanisms involving concerted peroxy(RO_(2)·)and alkoxy radical(RO·)modulated autoxidation,particularly emphasizing the importance of cyclization reactions *** expands the widely known RO_(2)·-dominated H-shift-driven autoxidation and proposes a generalized autoxidation mechanism that leads to the formation of low-volatility secondary organic aerosol(SOA)*** analysis shows that over half of transformation products(TPs)exhibited higher carcinogenicity and respiratory toxicity compared to *** also propose time-dependent toxic effects of TPs to assess their long-term *** results indicate that the strong indoor emission coupled with slow consumption rates lead to significant health risks under an indoor *** results highlight complex indoor air chemistry and health concerns regarding persistent toxic products during indoor cleaning,which involves the use of linalool or other VCPs.

关键词： volatile chemical products(VCPs) peroxy radicals(RO_(2)·) atmospheric autoxidation secondary organic aerosol(SOA) computational toxicology

来源：评论

学校读者我要写书评

暂无评论

Self-Supervised Depth Estimation Based on the Consistency of Synthetic-real Image Prediction

Self-Supervised Depth Estimation Based on the Consistency of...

引用

International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Wei Tong Yubing Gao Edmond Q. Wu Li-Min Zhu School of Mechanical Engineering Nanjing University of Science and Technology Jiangsu China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

Learning-based multi-view stereo aims to restore the real scene from multiple images with overlapping areas. The mainstream self-supervised MVS method trains the model based on the assumption that spatial points from different perspectives share the same color information. To further suppress the interference from specular reflection and illumination noise, this work proposes a self-supervised MVS network based on the consistency of synthetic-real image prediction. The network first applies the coarse-to-fine manner to gradually refine the depth map, and the source images are projected to the reference view to generate the synthesized reference image. Then the synthesized image with real source images are re-input into the network to form a cycled network, and the consistency constraint of the prediction results of the two periods is introduced to improve the color anti-interference of the self- supervised MVS model. The comprehensive experiments on the public dataset show that the proposed work can further improve the reconstruction performance of the benchmark model, which verifies the effectiveness of the proposed work.

关键词：

来源：评论

学校读者我要写书评

暂无评论

PI2-CMA Based Trajectory Planning Method for the Tractor-Trailer Vehicle

PI2-CMA Based Trajectory Planning Method for the Tractor-Tra...

引用

Pattern Recognition and Artificial Intelligence (PRAI), International Conference on

作者： You Wang Zehao Wang Jingchuan Wang Rui Guo Peng Xiao Institute of Medical Robotics and Department of Automation Ministry of Education Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai China State Grid Intelligence Technology CO. LTD

The motion primitive-based state lattice trajectory planning method has been widely used in the field of trajectory planning. However, due to the limitations of the search space and resolution of motion primitives, and the lack of consideration of scenario information during offline generation of motion primitives, the tractor-trailer vehicles can easily fall into "jackknife phenomenon" when making large pose adjustments in narrow scenarios, which brings dilemma for trajectory planning. In this paper, a trajectory planning algorithm is proposed based on a general model of tractor-trailer vehicle, which combines global planning and local optimization. The method first generates a series of motion primitives, including forward and backward driving conditions, and then an A ∗ based global state lattice planner is used to obtain a planning result, which is imported as the initial solution into the local trajectory optimizer based on PI 2 − CMA (Path Integral Policy Improvement with Covariance Matrix Adaptation) algorithm and dynamic potential method. Experiments show that this method significantly improves the performance in the obstacle avoidance, "jackknife phenomenon" avoidance and curvature compared to traditional motion primitive-based state lattice planning methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Robust Multi-AGV Cooperative Path Planning Method Considering Spatiotemporal Distance 5

A Robust Multi-AGV Cooperative Path Planning Method Consider...

引用

5th International Conference on Computer Engineering and Intelligent control, ICCEIC 2024

作者： Chen, Maolin Chen, Songhang Lian, Mingchang School of Advanced Manufacturing Fuzhou University Quanzhou China Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences Fuzhou China Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System Quanzhou China Fujian College University of Chinese Academy of Sciences Fuzhou China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou China

ISBN: (纸本)9798331507992

With the widespread application of Automated Guided Vehicles (AGVs) in warehousing and logistics systems, the optimization of multi-AGV path planning has become a critical issue. Current methods primarily focus on minimizing operating time and energy consumption but often overlook spatiotemporal distances between paths, leading to frequent path conflicts and interferences in the system. This paper proposes a neural network based time window estimation model, designed to generate time windows that better align with dynamic environments. Based on this model, we introduce a collaborative multi-AGV path planning method that optimizes spatiotemporal distances between paths. Compared to the Conflict-Based Search (CBS) method, this approach significantly improves the spatiotemporal distance between AGVs during task execution, enhancing the robustness of AGV clusters while only marginally increasing time costs. © 2024 IEEE.

关键词： Automatic guided vehicles

来源：评论

学校读者我要写书评

暂无评论

Fake News Detection Across Multiple Domains Using Fuzzy Association Rules 24th

Fake News Detection Across Multiple Domains Using Fuzzy Asso...

引用

24th International Conference on Algorithms and Architectures for Parallel processing, ICA3PP 2024

作者： Xu, Xiaofeng Zhang, Weisha Huang, Yuanyuan Lu, Hongyu Lu, Jiazhong School of Cybersecurity Xin Gu Industrial College Chengdu University of Information Technology Chengdu610225 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China SUGON Industrial Control and Security Center Chengdu610225 China School of Foreign Languages University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9789819615247

The detection of fake news is not confined to a single domain, and due to domain transfer, the reliance on detection methods specific to a single domain becomes inadequate when dealing with multi-domain issues. When a multi-domain detection occurs, labels from one domain focus exclusively on the news characteristics of that particular domain, ignoring the possibility that part of the news may include functions from more than one domain. To address these challenges, we propose a multi-domain fake news detection model based on fuzzy rules, incorporating a fuzzy mechanism and an optimization module for fuzzy association rules. In this model, we first introduce a fuzzy mechanism that applies fuzzy processing to domains through neural networks, constructing fuzzy domain labels for each news domain. Subsequently, we incorporate fuzzy association rules to extract a broader range of sample features, thereby enhancing detection effectiveness. Experiments conducted on a fake news dataset demonstrate that our model achieves commendable detection performance with a relatively low training cost, reaching an F1 score of over 97.13% for sample detection. This model successfully overcomes the limitations of single-domain detection in fake news identification and improves the precision of feature extraction through fuzzy rules, showing superior performance in handling multi-domain fake news detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： fake news detection fuzzy rules multi-domain social media

来源：评论

学校读者我要写书评

暂无评论

CC-Net: Consistency Learning Combined with Contrastive Learning for Kidney Ultrasound Segmentation

CC-Net: Consistency Learning Combined with Contrastive Learn...

引用

IEEE International Conference on systems, Man and Cybernetics

作者： Yang Luo Jun Liu Mengqian Ding School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Due to the scarcity of medical images with labels and the fact that medical image data is not easily accessible. Kidney ultrasound (KUS) images have speckle noise, low image quality, acoustic shadows, and other reasons, which pose significant challenges to the kidney ultrasound image segmentation task. To solve the above two problems, a novel consistency learning and contrastive learning-based kidney ultrasound image segmentation method (CC-Net) has been proposed. Specifically, the student-teacher model was adopted as the semi-supervised learning framework and uncertainty estimation was introduced. The Consensus Uncertainty Map (CUM) strategy was proposed to generate segmentation results for the teacher model when calculating uncertainty. To solve the problems of acoustic shadows and low image quality in kidney ultrasound images, a kidney ultrasound image data augmentation method (KUS-AUG) and a convolutional block (KUS-CONV) tailored to the characteristics of kidney ultrasound images were proposed. In addition, contrastive learning was implemented to enhance the encoder's ability to learn more semantic information, due to its inherent advantage in learning data distribution. Finally, a series of experiments were conducted on the ultrasound image dataset and the method achieved the best performance.

关键词： Image quality Image segmentation Ultrasonic imaging Uncertainty Noise Contrastive learning Semisupervised learning Acoustics Kidney Biomedical imaging

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：