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

24,748 篇 会议
161 篇 期刊文献
57 册 图书
1 篇 学位论文

馆藏范围

24,967 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

10,243 篇 工学
- 6,423 篇 控制科学与工程
- 4,201 篇 计算机科学与技术...
- 2,698 篇 软件工程
- 2,185 篇 电气工程
- 1,899 篇 机械工程
- 1,151 篇 仪器科学与技术
- 781 篇 信息与通信工程
- 591 篇 生物工程
- 478 篇 生物医学工程（可授...
- 432 篇 光学工程
- 413 篇 力学（可授工学、理...
- 403 篇 电子科学与技术（可...
- 274 篇 化学工程与技术
- 266 篇 动力工程及工程热...
- 263 篇 交通运输工程
- 253 篇 材料科学与工程（可...
- 220 篇 土木工程
- 213 篇 石油与天然气工程
- 209 篇 建筑学
3,113 篇 理学
- 1,797 篇 数学
- 912 篇 物理学
- 646 篇 生物学
- 586 篇 统计学（可授理学、...
- 482 篇 系统科学
- 237 篇 化学
1,268 篇 管理学
- 997 篇 管理科学与工程(可...
- 319 篇 图书情报与档案管...
- 315 篇 工商管理
340 篇 医学
- 294 篇 临床医学
- 207 篇 基础医学(可授医学...
127 篇 经济学
110 篇 法学
87 篇 农学
56 篇 教育学
29 篇 文学
16 篇 军事学
13 篇 艺术学
1 篇 哲学

主题

2,492 篇 predictive model...
1,996 篇 robots
1,824 篇 robotics and aut...
1,747 篇 computational mo...
1,725 篇 automation
1,666 篇 data models
1,586 篇 robot sensing sy...
1,494 篇 analytical model...
1,424 篇 adaptation model...
1,401 篇 training
1,205 篇 accuracy
1,142 篇 mathematical mod...
1,101 篇 trajectory
1,051 篇 mobile robots
935 篇 feature extracti...
857 篇 robustness
840 篇 robot kinematics
795 篇 control systems
715 篇 solid modeling
698 篇 cameras

机构

179 篇 university of ch...
145 篇 school of artifi...
111 篇 robotics institu...
89 篇 school of automa...
86 篇 institute of aut...
73 篇 shenyang institu...
68 篇 the robotics ins...
68 篇 institutes for r...
67 篇 school of electr...
66 篇 state key labora...
62 篇 school of mechat...
50 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...
31 篇 college of autom...

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 li yang
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

语言

23,446 篇 英文
1,438 篇 其他
106 篇 中文
1 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 24967 条记录，以下是4121-4130 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：

Semantic-Based Clustering for 3D Instance Segmentation In Sparse Radar Point Clouds

Semantic-Based Clustering for 3D Instance Segmentation In Sp...

引用

2023 international conference on Algorithms, Computing and Data Processing, ACDP 2023

作者： Yuan, Qingwen School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

ISBN: (纸本)9798350326680

With the development of intelligent driving, radar has become one of the core sensors of automotive assisted driving system because of its excellent performance of harsh environments. Current instance segmentation methods usually perform poorly on radar point clouds, where insufficient feature extraction leads to unsatisfying accuracy of foreground points. In this paper, we focus on the false positive foreground objects and semantic prediction errors for sparse radar point clouds. To overcome this, we build a novel multi-scale feature integration module with both spatial-wise and channel-wise attention mechanism which can be easily integrated into a deep network. In addition, we devise a similarity matrix of Mahalanobis distance to enhance the representation of features per point. To demonstrate the validity of our models in radar point clouds environment perception, we conducted experiments on the RadarScenes dataset. The results show that the proposed method can significantly improve the performance on Radar instance segmentation. © 2023 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Automatic 3D Object Recognition and Localization for Robotic Grasping 18

Automatic 3D Object Recognition and Localization for Robotic...

引用

18th international conference on Informatics in Control, automation and robotics (ICINCO)

作者： Santo, Bruno Antao, Liliana Goncalves, Gil Univ Porto Fac Engn Res Ctr Syst & Technol SYSTEC Rua Dr Roberto Frias P-4200465 Porto Portugal

ISBN: (纸本)9789897585227

With the emergence of Industry 4.0 and its highly re-configurable manufacturing context, the typical fixedposition grasping systems are no longer usable. This reality underlined the necessity for fully automatic and adaptable robotic grasping systems. With that in mind, the primary purpose of this paper is to join Machine Learning models for detection and pose estimation into an automatic system to be used in a grasping environment. The developed system uses Mask-RCNN and Densefusion models for the recognition and pose estimation of objects, respectively. The grasping is executed, taking into consideration both the pose and the object's ID, as well as allowing for user and application adaptability through an initial configuration. The system was tested both on a validation dataset and in a real-world environment. The main results show that the system has more difficulty with complex objects;however, it shows promising results for simpler objects, even with training on a reduced dataset. It is also able to generalize to objects slightly different than the ones seen in training. There is an 80% success rate in the best cases for simple grasping attempts.

关键词： robotics Grasping Object Pose Estimation Object Recognition

来源：评论

学校读者我要写书评

暂无评论

Learning Temporal Cues by Predicting Objects Move for Multi-camera 3D Object Detection

Learning Temporal Cues by Predicting Objects Move for Multi-...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Seokha Moon Hongbeen Park Jaekoo Lee Jinkyu Kim Department of Computer Science and Engineering Korea University Seoul Republic of Korea College of Computer Science Kookmin University Seoul Republic of Korea

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In autonomous driving and robotics, there is a growing interest in utilizing short-term historical data to enhance multi-camera 3D object detection, leveraging the continuous and correlated nature of input video streams. Recent work has focused on spatially aligning BEV-based features over timesteps. However, this is often limited as its gain does not scale well with long-term past observations. To address this, we advocate for supervising a model to predict objects’ poses given past observations, thus explicitly guiding to learn objects’ temporal cues. To this end, we propose a model called DAP (Detection After Prediction), consisting of a two-branch network: (i) a branch responsible for forecasting the current objects’ poses given past observations and (ii) another branch that detects objects based on the current and past observations. The features predicting the current objects from branch (i) is fused into branch (ii) to transfer predictive knowledge. We conduct extensive experiments with the large-scale nuScenes datasets, and we observe that utilizing such predictive information significantly improves the overall detection performance. Our model can be used plug-and-play, showing consistent performance gain.

关键词： Solid modeling Three-dimensional displays Refining Object detection Predictive models Streaming media Performance gain

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-based Feature Fusion for Action Recognition Using Skeleton Information

Deep Learning-based Feature Fusion for Action Recognition Us...

引用

international conference on robotics and Artificial Intelligence (ICRAI)

作者： Fahad Ul Hassan Asif Mattoo Umar Shahbaz Khan Tahir Nawaz Nasir Rashid Department of Mechatronics Engineering College of Electrical and Mechanical Engineering National University of Sciences and Technology Islamabad Pakistan

Various action recognition systems have been proposed, but most of them are not feasible to be used in real-time applications. Skeleton-based action recognition has a low computational cost and is not affected by background changes. As the pose estimation models are becoming faster (almost real-time), a model was created with only 1.8M parameters named DD-net, which uses the skeleton information to predict the action. Recently an improved version of the model came out and was named TD-net. The model is very rich with geometric-based features but lacks motion-based features. To overcome this we added two motion features in the model named acceleration and velocity. These features were created using second order Taylor's approximation, in a window around the current frame. The model accuracy was compared with DD-net, TD-net, and state-of-the-art algorithms using three different datasets. An increase in accuracy is observed for all three datasets (i.e 1.1% for SHERC, 1.7% for FPHAB and 2% for JHMDB) when compared with TD-net.

关键词： Industries Computational modeling Pose estimation Predictive models Streaming media Skeleton Real-time systems

来源：评论

学校读者我要写书评

暂无评论

A Novel Variable Resolution Torque Sensor Based on Variable Stiffness Principle

A Novel Variable Resolution Torque Sensor Based on Variable ...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Sun, Xiantao Chen, Wenjie Zhang, Jianbin Wang, Jianhua Jiang, Jun Chen, Weihai Anhui Univ Sch Elect Engn & Automat Anhui Engn Lab Human Machine Cooperat Syst & Inte Hefei Peoples R China Beihang Univ Sch Mech Engn & Automat Beijing Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing Peoples R China Beijing Inst Control Engn Beijing Peoples R China

ISBN: (纸本)9781728190778

High resolution and large range force/torque (F/T) measurements are usually required in many engineering tasks. However, most existing F/T sensors only have a fixed resolution over their whole ranges. The key lies in that it is difficult to well balance high resolution and large range in the sensor design. Taking the torque sensor for example, this paper presents a better compromise for this problem i.e., a novel variable resolution torque sensor based on variable stiffness principle. From the structural points of view, the sensor is constructed with multiple radial flexures to achieve a pure rotational motion with negligible parasitic center motions. Two resistive strain gauges (RSGs) are selected as the measuring units of the sensor to detect the applied external torque and meanwhile provide variable resolutions in the two different measuring ranges (each RSG for one range). Static and dynamic models of the sensor are established in details and validated through finite element analysis (FEA) to evaluate its characteristics. A principle prototype is finally fabricated and tested to verify the effectiveness of the presented design. RSGs are calibrated through a commercial six-axis F/T sensor from ATI Industrial automation, Inc. Experimental results show that the torque sensor can provide high and low resolutions in the small and large ranges respectively and possesses the first natural frequency of 673 Hz. In addition, the proposed variable resolution method can also be applied to the development of multi-axis F/T sensors.

关键词： Mechanical sensors Vibrations Analytical models Torque Sensor phenomena and characterization Strain measurement Shock absorbers

来源：评论

学校读者我要写书评

暂无评论

MOFT: Monocular odometry based on deep depth and careful feature selection and tracking

MOFT: Monocular odometry based on deep depth and careful fea...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Karlo Koledić Igor Cvišić Ivan Marković Ivan Petrović University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Autonomous Systems and Mobile Robotics Zagreb Croatia

Autonomous localization in unknown environments is a fundamental problem in many emerging fields and the monocular visual approach offers many advantages, due to being a rich source of information and avoiding comparatively more complicated setups and multisensor calibration. Deep learning opened new venues for monocular odometry yielding not only end-to-end approaches but also hybrid methods combining the well studied geometry with specific deep components. In this paper we propose a monocular odometry that leverages deep depth within a feature based geometrical framework yielding a lightweight frame-to-frame approach with metrically scaled trajectories and state-of-the-art accuracy. The front-end is based on a multihypothesis matcher with perspective correction coupled with deep depth predictions that enables careful feature selection and tracking; especially of ground plane features that are suitable for translation estimation. The back-end is based on point-to-epipolar line minimization for rotation and unit translation estimation, followed by deep depth aided reprojection error minimization for metrically correct translation estimation. Furthermore, we also present a domain shift adaptation approach that allows for generalization over different camera intrinsic and extrinsic setups. The proposed approach is evaluated on the KITTI and KITTI-360 datasets, showing competitive results and in most cases outperforming other state-of-the-art stereo and monocular methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Method for Improvement of Biosignal Measurement Accuracy in the IoB System

Method for Improvement of Biosignal Measurement Accuracy in ...

引用

international conference on Soft Computing and Measurements (SCM)

作者： Yeldos A. Altay Raisa K. Uskenbayeva Alexey V. Fedorov Department of Robotics and Technical Means of Automation Satbayev University Almaty Kazakhstan Satbayev University Almaty Kazakhstan Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russian Federation

ISBN: (数字)9798350363708

ISBN: (纸本)9798350363715

This paper presents filtering methods for improvement of biosignal measurement accuracy - an ECG signal under the influence of electromagnetic interference, which has a significant impact on the operation of the IoB system. A single-frequency polynomial notch filter has been synthesized to filter this noise to improve the accuracy of ECG signal measurement. The results of the implementation of the synthesized notch filter demonstrated that the filter makes it possible to separate the informative component from the distorting noise and increase the accuracy of signal measurement during its implementation in comparison with wavelet filters.

关键词： Accuracy Shape Filtering Electromagnetic interference Measurement uncertainty Electrocardiography Polynomials

来源：评论

学校读者我要写书评

暂无评论

A Hierarchical Decoupling Approach for Fast Temporal Logic Motion Planning

A Hierarchical Decoupling Approach for Fast Temporal Logic M...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Ziyang Chen Zhangli Zhou Shaochen Wang Zhen Kan Department of Automation University of Science and Technology of China Hefei Anhui China

Fast motion planning is of great significance, espe-cially when a timely mission is desired. However, the complexity of motion planning can grow drastically with the increase of environment details and mission complexity. This challenge can be further exacerbated if the tasks are coupled with the desired locations in the environment. To address these issues, this work aims at fast motion planning problems with temporal logical specifications. In particular, we develop a hierarchical decoupling framework that consists of three layers: the high-level task planner, the decoupling layer, and the low-level motion planner. The decoupling layer is designed to bridge the high and low layers by providing necessary information exchange. Such a framework enables the decoupling of the task planner and path planner, so that they can run independently, which significantly reduces the search space and enables fast planing in continuous or high-dimension discrete workspaces. In addition, the implicit constraint during task-level planning is taken into account, so that the low-level path planning is guaranteed to satisfy the mission requirements. Numerical simulations demonstrate at least one order of magnitude speed up in terms of computational time over existing methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Extrinsic calibration for highly accurate trajectories reconstruction

Extrinsic calibration for highly accurate trajectories recon...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Maxime Vaidis William Dubois Alexandre Guénette Johann Laconte Vladimír Kubelka François Pomerleau Northern Robotics Laboratory Université Laval Québec City Canada Mobile Robotics and Olfaction lab AASS research center at Örebro University Sweden

In the context of robotics, accurate ground-truth positioning is the cornerstone for the development of mapping and localization algorithms. In outdoor environments and over long distances, total stations provide accurate and precise measurements, that are unaffected by the usual factors that deteriorate the accuracy of Global Navigation Satellite System (GNSS). While a single robotic total station can track the position of a target in three Degrees Of Freedom (DOF), three robotic total stations and three targets are necessary to yield the full six DOF pose reference. Since it is crucial to express the position of targets in a common coordinate frame, we present a novel extrinsic calibration method of multiple robotic total stations with field deployment in mind. The proposed method does not require the manual collection of ground control points during the system setup, nor does it require tedious synchronous measurement on each robotic total station. Based on extensive experimental work, we compare our approach to the classical extrinsic calibration methods used in geomatics for surveying and demonstrate that our approach brings substantial time savings during the deployment. Tested on more than 30 km of trajectories, our new method increases the precision of the extrinsic calibration by 25 % compared to the best state-of-the-art method, which is the one taking manually static ground control points.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Channel-distribution Hybrid Deep Learning for sEMG-based Gesture Recognition

Channel-distribution Hybrid Deep Learning for sEMG-based Ges...

引用

2022 IEEE international conference on robotics and Biomimetics, ROBIO 2022

作者： Lu, Keyi Guo, Hao Qi, Fei Gong, Peihao Gu, Zhihao Sun, Lining Huang, Haibo School of Mechanical and Electric Engineering Jiangsu Provincial Key Laboratory of Advanced Robotics Soochow University Suzhou215123 China School of Mechanical and Electric Engineering Soochow University Suzhou215123 China

ISBN: (纸本)9781665481090

In recent years, CNNs (Convolutional Neural Networks) with their powerful feature representation and feature learning capabilities, have played an important role in gesture recognition tasks based on sparse multichannel surface EMG signals. As each muscle group in the upper limb plays a different role in a particular hand movement, we propose a hybrid CNN model that considers the spatial distribution of muscle groups in the myoelectric channel to improve the accuracy of hand gesture recognition. The model takes the spectrogram of CWT (Continuous Wavelet Transform) as input, based on the spatial distribution of channels, decomposes all channels into multiple input streams, lets the CNN learn the features of each stream separately, and gradually fuses (slowly fusion) the features learned by each stream, and then performs gesture classification. Finally, the results of several of these stream-division methods are fused for decision making to obtain classification accuracies. The proposed model was validated and tested on the Nina Pro DB4 dataset, and the average accuracy was improved compared to both traditional machine learning methods and multi-stream CNN models that do not take into account the spatial distribution of channels. © 2022 IEEE.

关键词： Neural network models

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 << < 409 410 411 412 413 414 415 416 417 418 > >>

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：