检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

24,537 篇 会议
162 篇 期刊文献
56 册 图书
1 篇 学位论文
1 篇 科技报告

馆藏范围

24,757 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

10,118 篇 工学
- 6,328 篇 控制科学与工程
- 4,098 篇 计算机科学与技术...
- 2,652 篇 软件工程
- 2,145 篇 电气工程
- 1,863 篇 机械工程
- 1,144 篇 仪器科学与技术
- 735 篇 信息与通信工程
- 587 篇 生物工程
- 473 篇 生物医学工程（可授...
- 426 篇 光学工程
- 402 篇 力学（可授工学、理...
- 388 篇 电子科学与技术（可...
- 262 篇 化学工程与技术
- 250 篇 材料科学与工程（可...
- 250 篇 交通运输工程
- 244 篇 动力工程及工程热...
- 214 篇 土木工程
- 202 篇 建筑学
- 181 篇 安全科学与工程
3,068 篇 理学
- 1,763 篇 数学
- 903 篇 物理学
- 643 篇 生物学
- 582 篇 统计学（可授理学、...
- 482 篇 系统科学
- 229 篇 化学
1,223 篇 管理学
- 958 篇 管理科学与工程(可...
- 310 篇 工商管理
- 306 篇 图书情报与档案管...
328 篇 医学
- 287 篇 临床医学
- 205 篇 基础医学(可授医学...
122 篇 经济学
106 篇 法学
87 篇 农学
53 篇 教育学
27 篇 文学
16 篇 军事学
13 篇 艺术学
1 篇 哲学

主题

2,475 篇 predictive model...
1,994 篇 robots
1,825 篇 robotics and aut...
1,735 篇 computational mo...
1,713 篇 automation
1,645 篇 data models
1,581 篇 robot sensing sy...
1,488 篇 analytical model...
1,401 篇 adaptation model...
1,379 篇 training
1,164 篇 accuracy
1,141 篇 mathematical mod...
1,099 篇 trajectory
1,046 篇 mobile robots
914 篇 feature extracti...
840 篇 robustness
838 篇 robot kinematics
793 篇 control systems
718 篇 solid modeling
700 篇 uncertainty

机构

179 篇 university of ch...
143 篇 school of artifi...
111 篇 robotics institu...
87 篇 school of automa...
84 篇 institute of aut...
72 篇 shenyang institu...
70 篇 institutes for r...
68 篇 the robotics ins...
68 篇 school of electr...
63 篇 state key labora...
61 篇 school of mechat...
49 篇 department of au...
49 篇 department of au...
48 篇 state key labora...
46 篇 school of automa...
44 篇 school of mechan...
42 篇 robotics institu...
39 篇 school of automa...
32 篇 school of automa...
29 篇 carnegie mellon ...

作者

37 篇 secchi cristian
34 篇 yuechao wang
32 篇 yun-hui liu
31 篇 cristian secchi
29 篇 shugen ma
28 篇 lining sun
24 篇 xiang li
22 篇 jian wang
22 篇 jianda han
22 篇 fabio ramos
20 篇 xinyu wu
20 篇 wu xinyu
20 篇 daniela rus
19 篇 tomizuka masayos...
19 篇 wei li
19 篇 levine sergey
18 篇 c. laugier
18 篇 jie zhao
18 篇 chen chen
18 篇 dinesh manocha

语言

24,428 篇 英文
245 篇 其他
92 篇 中文
2 篇 西班牙文
1 篇 俄文

检索条件"任意字段=International Conference on Methods and Models in Automation and Robotics"

共 24757 条记录，以下是4781-4790 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Networks 24th

Cost-Efficient Multi-Objective Design of Miniaturized Microw...

引用

24th international conference on Computational Science (ICCS)

作者： Koziel, Slawomir Pietrenko-Dabrowska, Anna Leifsson, Leifur Reykjavik Univ Engn Optimizat & Modeling Ctr Dept Engn Menntavegur 1 IS-102 Reykjavik Iceland Gdansk Univ Technol Fac Elect Telecommun & Informat Narutowicza 11-12 PL-80233 Gdansk Poland Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47907 USA

ISBN: (纸本)9783031637742;9783031637759

Designing microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when executed with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective MO technique for microwave passive components utilizing a machine learning (ML) framework with artificial neural network (ANN) surrogates as the primary prediction tool. In this approach, multiple candidate solutions are extracted from the Pareto set via optimization using a multi-objective evolutionary algorithm (MOEA) applied to the current ANN model. These solutions expand the dataset of available (EM-simulated) parameter vectors and refine the surrogate model iteratively. To enhance computational efficiency, we employ variable-resolution EM models. Tested on two microstrip circuits, our methodology competes effectively against several surrogate-based approaches. The average computational cost of the algorithm is below three hundred EM analyses of the circuit, with the quality of generated Pareto sets surpassing those produced by the benchmark methods.

关键词： Microwave design multi-objective optimization design automation machine learning neural networks surrogate modeling Pareto optimality

来源：评论

学校读者我要写书评

暂无评论

Hand-Eye Calibration of Surgical Robots Based on a BP Neural Network Optimized by Using an Improved Sparrow Search Algorithm

Hand-Eye Calibration of Surgical Robots Based on a BP Neural...

引用

international conference on Control, automation, robotics and Vision (ICARCV)

作者： Jiaqi Zhu Weibo Ning Ye Yuan Hongjiang Chen Weijun Zhou Yecheng Tan Shuxing He Jun Hu Zhun Fan Shantou University Shantou China Hospital of Medical College of Shantou University Shantou China

ISBN: (纸本)9781665476881

Hand-eye calibration methods for surgical robots are employed to derive a transformation between the robot's base motor and visual coordinate systems. Accurately completing hand-eye calibration procedures provides an important guarantee that a surgical robot will exhibit positioning and execution accuracy sufficient for assisting surgeons in successfully completing surgical procedures. To improve the accuracy of robot hand-eye calibration methods based on backpropagation neural network (BPNN) models, we propose a modified BP neural network optimized using the sparrow search algorithm for hand-eye calibration model (TSSABPNN), which can enhance population initialization by applying tent mapping. Furthermore, we also design a new sliding 3D calibration tool. The sparrow search algorithm exhibits good local exploration ability, and we introduce a tent map with ergodic characteristics to initialize the sparrow population information, which further improves the network's global search ability and convergence rate. Finally, we experimentally analyze four calibration models: TSSABP NN model, a BP NN model optimized using a genetic algorithm of simulated annealing (GASABPNN), an unoptimized BP NN model, and the traditional singular value decomposition method. The results indicate that the proposed TSSABP NN model exhibits the maximum calibration precision and best robustness and iteratively converges faster.

关键词： Analytical models Medical robotics Three-dimensional displays Robot kinematics Sociology Artificial neural networks Robustness

来源：评论

学校读者我要写书评

暂无评论

Digital control method for bucket truck based on PSO algorithm

Digital control method for bucket truck based on PSO algorit...

引用

IEEE international conference on Mechatronics, robotics and automation (ICMRA)

作者： Xu Jian Liang Zhang Shuangxue Sun Shengzu Li Gang Wang Jinbin Li Beinuo Huang Electric Power Research Institute State Grid Hubei Electric Power Co. Ltd Wuhan China Wuhan Power Supply Company State Grid Hubei Electric Power Co. Ltd Wuhan China School of Automation China University of Geosciences Wuhan China

ISBN: (数字)9798350307535

ISBN: (纸本)9798350307542

In the aspect of power maintenance, the control of bucket trucks has always been a difficult problem. It often requires operators to have enough experience. However, even so, due to the complex environment, it often takes a lot of time to control the end effector of the bucket truck to reach the appropriate position, which greatly reduces the efficiency of the operation and increases the accident rate during the entire process. To solve this problem, this article proposes a digital control method for bucket truck based on PSO algorithm. We first established a mathematical model of the bucket truck based on DH parameters and completed its forward kinematics derivation. On this basis, we introduced the PSO algorithm to complete the digital control of the bucket truck, solving the problem of high difficulty in obtaining its analytical solution. The experiment shows that the proposed method has high accuracy in both virtual and real environments, greatly improving the control efficiency of the bucket truck.

关键词： Digital control Mechatronics Trajectory planning Software algorithms Process control Kinematics Software Mathematical models Maintenance robotics and automation

来源：评论

学校读者我要写书评

暂无评论

Determination of Basic Probability Assignment Based on Membership Function and PCA

Determination of Basic Probability Assignment Based on Membe...

引用

international conference on robotics and automation Engineering (ICRAE)

作者： Aoxiang Zhao Junwei Li Huanyu Liu School of Artificial Intelligence Henan University Zhengzhou China

When using evidence theory to identify targets, how to generate basic probability assignment (BPA) based on the collected data is still an open issue. Based on this problem, a novel method to generate BPA based on membership function and principal component analysis (PCA) is proposed. First, this paper proposed a novel membership function and divide the data set into the training set and testing set, the membership model of each attribute is constructed based on the training set data. Secondly, the testing set sample is input to obtain the initial BPA of each attribute. Thirdly, the contribution rate of each attribute is used by PCA. Finally, the final BPA is obtained by discounting the initial BPA according to the contribution rate. The results of the experiment have demonstrated the classification accuracy under the Iris dataset is higher than other methods, and the average recognition rate of the Iris dataset is 97.3%.

关键词： Training automation Evidence theory Data models Principal component analysis Iris recognition Testing

来源：评论

学校读者我要写书评

暂无评论

YOLO-ELD: Efficient and Lightweight Detection for UAV Aerial Imagery

YOLO-ELD: Efficient and Lightweight Detection for UAV Aerial...

引用

2024 IEEE international conference on Systems, Man, and Cybernetics, SMC 2024

作者： Yan, Haimin Wang, Juncheng Kong, Xiangbo Tomiyama, Hiroyuki Graduate School of Science and Engineering Ritsumeikan University 1-1-1 Noji-Higashi Shiga Kusatsu Japan Chongqing Branch China United Network Communications Corporation Chongqing China Toyama Prefectural University Faculty of Information Engineering Department of Intelligent Robotics Kurokawa Imizu Toyama5180 Japan

ISBN: (纸本)9781665410205

Object detection in UAV imagery has become a hot topic in recent years. However, deploying real-time detection models on UAV platforms is highly challenging due to limited computational power and memory. Moreover, the large size of UAV-captured images, the small size of objects, and their dense distribution all impact detection efficiency. Many researchers have made a series of improvements to address these issues, but they have not maintained a good balance among model size, inference speed, and accuracy. To address above difficulties, this paper proposes an efficient and lightweight model that maintains moderate detection accuracy while achieving model lightweighting and reduced inference time. Concretely, considering the higher resolution of drone-captured images, we have designed a backbone with more lightweight downsampling modules, enhancing deployment efficiency on devices with limited resources. Additionally, this work incorporates a self-attention mechanism in the feature extraction component of the model, which significantly improves the ability to process critical areas in the image, crucial for detecting small-scale and densely distributed targets. Moreover, this work designs an IoU tailored for drone aerial images, which calculates losses by focusing on the shape and scale of bounding boxes, thereby enhancing the accuracy of bounding box regression. Additionally, it uses a ratio of scale factors to control the generation of auxiliary bounding boxes, which aids in loss calculation and accelerates convergence. Experimental results on the VisDrone 2019 dataset show that compared to existing detection methods used for drones, our model is more lightweight and efficient, while also achieving medium accuracy. Also, compared to our baseline method, YOLO-ELD reduces the number of model parameters by about 40%, increases the inference speed of the model by 10%, and also improves the precision of model by 3%. © 2024 IEEE.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Hybrid FM-GCN-Attention Model for Personalized Recommendation

Hybrid FM-GCN-Attention Model for Personalized Recommendatio...

引用

Electrical automation and Artificial Intelligence (ICEAAI), international conference on

作者： Erfan Wang Rice University Dallas TX USA

ISBN: (数字)9798331506797

ISBN: (纸本)9798331506803

Personalized recommendation systems play a crucial role in enhancing user engagement and decision-making across various domains. Traditional approaches, such as collaborative filtering and matrix factorization, have shown effectiveness but suffer from data sparsity and cold-start problems. Recent advances in deep learning, graph-based models, and attention mechanisms have significantly improved recommendation performance. This paper proposes a novel hybrid recommendation model that integrates Factorization Machines (FM), Graph Convolutional Networks (GCN), and Multi-Layer Attention Networks (MLAN) to optimize feature representations and enhance prediction accuracy. Experimental results demonstrate the superiority of the proposed approach over baseline methods in key performance metrics.

关键词： Measurement Frequency modulation Attention mechanisms Accuracy Graph convolutional networks Scalability Predictive models Robustness Recommender systems Optimization

来源：评论

学校读者我要写书评

暂无评论

A fault detection method for AUV based on multi-scale spatiotemporal feature fusion 5

A fault detection method for AUV based on multi-scale spatio...

引用

5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Xia, Shaoxuan Zhou, Xiaofeng Shi, Haibo Li, Shuai Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510662520

Autonomous underwater vehicles (AUVs) are important equipment for ocean development and exploration. To ensure the task implementation of AUV, faults shall be detected in time. We propose a fault detection method based on multi-scale spatiotemporal feature fusion (MSF) for the time-varying characteristics and multiple correlation characteristics of AUV monitoring data. First, we apply a variety of sampling and data processing methods to generate monitoring windows with different scales along the time axis. Then, a composite feature extraction method is proposed to obtain temporal and spatial features simultaneously, and a feature pyramid of temporal and spatial information is formed. We use bidirectional long short-term memory (BiLSTM) to obtain the time-series characteristics of a single monitoring variable, and convolutional neural networks (CNN) to obtain the implicit spatial relationship characteristics among multiple monitoring variables. Next, we use an adaptive feature fusion method to solve the inconsistency in different feature scales, which can adaptively suppress the possible conflict information of different scale features. Finally, we use a fully connected network to detect the fault of the fused features. The fault detection experiment of Haizhe AUV shows the effectiveness and superiority of the proposed method. © 2023 SPIE.

关键词： Autonomous underwater vehicles

来源：评论

学校读者我要写书评

暂无评论

Reinforcement Learning for Manipulating Large Flat Objects on the Horizontal Surface

Reinforcement Learning for Manipulating Large Flat Objects o...

引用

IEEE international conference on Cyber Technology in automation, Control, and Intelligent Systems

作者： Houxue Yang Chengzhong Ma Xingyu Chen Xuguang Lan Department of Institute of Artifcial Intelligence and Robotics Xi'an Jiaotong University Xi'an Shaanxi China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

Grasping large rigid flat objects on a horizontal surface is often considered a challenging task. Previous work has implemented pushing objects against walls or table edges to make objects graspable. However, these methods often rely on special external conditions, such as walls and table edges. Inspired by human operation, we can solve this problem by flipping the object and then grasping it from the side, thereby avoiding strong dependence on the external environment. In this paper, we develop a model-free deep reinforcement learning framework Flipping and Grasping of Large Rigid Flat Ungraspable Objects (FGLO) to guide robot actions. We adopt a Soft Actor-Critic algorithm with a common Actor-Critic reward to learn flipping actions and grasping actions. Experimental results show that our network policy can be generalized to objects of different densities and sizes with a success rate of 89%.

关键词： automation Grasping Deep reinforcement learning Control systems Intelligent systems Grippers Robots

来源：评论

学校读者我要写书评

暂无评论

Multi-Joint Predictor for Human Upper Limbs in Human-Robot Collaboration Tasks

Multi-Joint Predictor for Human Upper Limbs in Human-Robot C...

引用

Electrical Engineering, Control and robotics (EECR), international conference on

作者： Mengyao Zhang Zijian Zhang Linjian Wang Qinghua Li Chao Feng School of Information and Automation Qilu University of Technology (Shandong Academy of Sciences) Jinan China International School for Optoelectronic Engineering Qilu University of Technology (Shandong Academy of Sciences) Jinan China College of Artifificial Intelligence and Big Data for Medical Sciences Shandong First Medical University (Shandong Academy of Medical Sciences) Jinan China

ISBN: (数字)9798350370003

ISBN: (纸本)9798350370010

The safety of collaborators is the primary concern in human-robot collaboration tasks. Accurately perceiving the human body pose information is a crucial technology for achieving the safe execution of human-robot collaboration. This paper proposes a multi-joint predictor for the human upper limb, discusses the correlation between multiple joints and the predictor's performance under different motion speeds to provide precise obstacle avoidance information for collision detection. A combined dataset is created by collecting operation information from medical personnel in a cellular experiment context. Secondly, the sparrow search algorithm is utilized to optimize the Long Short Term Memory network for constructing a predictor for multiple joints while discussing the correlation between each joint to obtain real-time position updates. Finally, the usability and accuracy of the proposed predictor is validated.

关键词： Wrist Correlation Collaboration Predictive models Prediction algorithms Task analysis Collision avoidance

来源：评论

学校读者我要写书评

暂无评论

MD2VO: Enhancing Monocular Visual Odometry through Minimum Depth Difference

MD2VO: Enhancing Monocular Visual Odometry through Minimum D...

引用

international Joint conference on Neural Networks (IJCNN)

作者： Pengzhi Li Chengshuai Tang Yifu Duan Zhiheng Li Tsinghua Shenzhen International Graduate School Tsinghua University China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Monocular visual odometry is an indispensable technique in visual signal tasks, including robotics and navigation. However, the scale ambiguity and poor generalizability of monocular systems remain significant challenges. To address this issue, we propose a novel framework to enhance visual odometry (VO) using monocular depth estimation algorithms and geometry-based methods. Our approach employs a depth point filtering method that utilizes depth information output from multiple depth estimation models with a minimum depth difference strategy. This approach effectively combines depth information from different models, resulting in more accurate scale factor recovery and trajectory prediction using PnP. Experiment results demonstrate that our method outperforms current learning-based VO methods in terms of generalization capability and accuracy. Additionally, we show that incorporating pre-trained models in the VO system to obtain pseudo-labeled depth data significantly enhances the performance of existing geometry-based VO methods.

关键词： Visualization Accuracy Navigation Estimation Predictive models Prediction algorithms Trajectory

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 475 476 477 478 479 480 481 482 483 484 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：