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

1,211 篇 会议
9 篇 期刊文献

馆藏范围

1,220 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

494 篇 工学
- 384 篇 控制科学与工程
- 244 篇 计算机科学与技术...
- 146 篇 电气工程
- 85 篇 软件工程
- 61 篇 机械工程
- 39 篇 仪器科学与技术
- 17 篇 信息与通信工程
- 16 篇 力学（可授工学、理...
- 12 篇 生物工程
- 11 篇 材料科学与工程（可...
- 11 篇 交通运输工程
- 10 篇 生物医学工程（可授...
- 9 篇 光学工程
- 9 篇 土木工程
- 7 篇 建筑学
- 5 篇 动力工程及工程热...
- 5 篇 电子科学与技术（可...
- 5 篇 化学工程与技术
- 5 篇 石油与天然气工程
- 5 篇 安全科学与工程
100 篇 理学
- 66 篇 数学
- 21 篇 物理学
- 19 篇 统计学（可授理学、...
- 14 篇 生物学
- 13 篇 系统科学
- 6 篇 化学
35 篇 管理学
- 30 篇 管理科学与工程(可...
- 7 篇 工商管理
- 7 篇 图书情报与档案管...
7 篇 医学
- 6 篇 临床医学
3 篇 文学
2 篇 农学
1 篇 法学
1 篇 教育学
1 篇 军事学

主题

165 篇 mathematical mod...
104 篇 predictive model...
93 篇 automation
93 篇 adaptation model...
90 篇 robots
87 篇 computational mo...
82 篇 data models
81 篇 training
61 篇 trajectory
59 篇 analytical model...
58 篇 equations
57 篇 accuracy
55 篇 numerical models
51 篇 approximation me...
48 篇 stability analys...
46 篇 vectors
45 篇 feature extracti...
39 篇 robot sensing sy...
39 篇 control systems
39 篇 estimation

机构

10 篇 faculty of mecha...
9 篇 state key labora...
8 篇 institute of com...
8 篇 school of electr...
8 篇 institute of aut...
6 篇 department of el...
6 篇 silesian tech un...
6 篇 university of ch...
6 篇 univ rostock cha...
5 篇 faculty of elect...
5 篇 chair of mechatr...
5 篇 faculty of elect...
5 篇 institute of aut...
5 篇 institute of aut...
5 篇 systems research...
4 篇 carleton univ de...
4 篇 department of au...
4 篇 department of au...
4 篇 department of au...
4 篇 institute of aut...

作者

13 篇 jerzy baranowski
12 篇 waldemar bauer
8 篇 janusz szpytko
8 篇 rafał stanisławs...
7 篇 aschemann harald
7 篇 marian łukaniszy...
7 篇 krzysztof j. lat...
6 篇 krzysztof gałkow...
6 篇 jarosław figwer
6 篇 wojciech p. hune...
6 篇 baranowski jerzy
6 篇 rauh andreas
6 篇 yang li
6 篇 harald aschemann
5 篇 andreas rauh
5 篇 ignacy duleba
5 篇 szulc katarzyna
5 篇 krzysztof arent
5 篇 krzysztof bartec...
4 篇 rydel marek

语言

1,211 篇 英文
6 篇 中文
3 篇 其他
1 篇 西班牙文

检索条件"任意字段=25th International Conference on Methods and Models in Automation and Robotics"

共 1220 条记录，以下是431-440 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：

Motion Planning of a Rehabilitation Robotic Arm using Brain data & Deep Learning

Motion Planning of a Rehabilitation Robotic Arm using Brain ...

引用

RSI/ISM international conference on robotics and Mechatronics (ICROM)

作者： Ali Soltani S. Ali A. Moosavian Advanced Robotics and Automated Systems (ARAS) Lab K. N Toosi University of Technology Tehran Iran

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

the Brain-Computer Interface (BCI) technology has emerged as an innovative tool in the field of rehabilitation, aimed at restoring and improving patient motor and sensory functions. the motivation for using BCI in rehabilitation is primarily based on the ability of these systems to establish a direct correlation between brain activity and external devices, such as motor prostheses or assistive robots. this technology aids patients with spinal cord injuries, strokes, or neurological diseases in regaining lost functionality by directly controlling assistive devices. the primary objective of research in this area is to enhance the quality of life for individuals with motor impairments and to improve the efficiency of rehabilitation methods, potentially leading to the development of models for automation in clinics and rehabilitation centers. In this study, to utilize the BCI as an automated system for controlling rehabilitation devices or functional prostheses, a series of experiments were designed and conducted to record electroencephalography (EEG) data from healthy individuals during a variety of hand motions, while simultaneously the motion is captured with two webcams. the initial data was collected and analyzed, and the results indicate that increasing the number of test subjects and employing more advanced equipment for signal recording could lead to more accurate results and the development of a more comprehensive model. Obtained model can then be used to command a rehabilitation arm according to the patient brain signals.

关键词： Webcams Stroke (medical condition) Motors Brain modeling Assistive robots Robot sensing systems Electroencephalography Brain-computer interfaces Recording Spinal cord injury

来源：评论

学校读者我要写书评

暂无评论

A Container Cloud Elastic Scaling Method Based on GRU Attention Mechanism

A Container Cloud Elastic Scaling Method Based on GRU Attent...

引用

Computer Engineering and Intelligent Control (ICCEIC) international conference on

作者： Yue Zhang Yong Sun Chunhe Song Pengpei Gao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798331507992

ISBN: (纸本)9798331508005

In modern container cloud computing environments, achieving efficient elastic scaling is crucial to optimizing resource utilization and improving system performance. this paper proposes a new prediction model based on gated recurrent unit (GRU) and attention mechanism for load prediction and elastic scaling strategy optimization. the model uses the time series processing capability of GRU combined with the optimization characteristics of the attention mechanism to improve the accuracy and real-time performance of load prediction. Experimental results show that compared with traditional methods, the model can more accurately capture the load change trend and achieve more agile and efficient resource scheduling and management, thereby effectively reducing resource waste and improving service quality. this study provides a novel and effective solution for elastic scaling in container cloud environments.

关键词： Cloud computing Attention mechanisms Computational modeling System performance Time series analysis Containers Predictive models Resource management Optimization Load modeling

来源：评论

学校读者我要写书评

暂无评论

ARAS-Farabi Experimental Framework for Skill Assessment in Capsulorhexis Surgery 9

ARAS-Farabi Experimental Framework for Skill Assessment in C...

引用

9th RSI international conference on robotics and Mechatronics (ICRoM)

作者： Ahmadi, Mohammad Javad Allahkaram, Mohammad Sina Rashvand, Ashkan Lotfi, Faraz Abdi, Parisa Motaharifar, Mohammad Mohammadi, S. Farzad Taghirad, Hamid D. K N Toosi Univ Technol Adv Robot & Automated Syst Tehran Iran Univ Isfahan Dept Elect Engn Esfahan Iran Univ Tehran Med Sci Tehran Iran

ISBN: (纸本)9781665420945

Automatic surgical instruments detection in recorded videos is a key component of surgical skill assessment and content-based video analysis. Such analysis may be used to develop training techniques, especially in ophthalmology. this research focuses on capsulorhexis, the most fateful process in cataract surgery, which is a very delicate procedure and requires very high surgical skill. Assessment of the surgeon's skill in handling surgical instruments is one of the main parameters of surgical quality assessment, and requires the proper detection of important instruments and tissues during a surgical procedure. the traditional methods to accomplish this task are very time-consuming and effortful, and therefore, automating this process by using computer vision approaches is a stringent requirement. In order to accomplish this requirement, a proper dataset is prepared. By consulting the expert surgeons, the pupil, and the surgical tool, namely the capsulorhexis cystotome, are annotated in this dataset. then, we created a general framework for implementing and examining different approaches, models, and techniques on the developed dataset, and reporting the comparative analysis. this study shows that the object detection task can be accurately performed for various scenarios using this dataset. the developed dataset, the developed deep learning general framework, and other developments are made public for further research.

关键词： Object detection Surgical instrument detection Dataset preparation automation Cataract surgery Capsulorhexis cystotome

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning-Based Fatigue Extraction Method Using Human Manipulation Video Data in Smart Manufacturing

A Machine Learning-Based Fatigue Extraction Method Using Hum...

引用

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

作者： Jiarong Yao Nabeel Muhammad Chongshan He Kaixu Li Rong Su School of Electrical and Electronic Engineering Nanyang Technological University Singapore Centre for Advanced Robotics Technology Innovation (CARTIN) School of Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

As an important part in smart manufacturing under Industry 4.0 era, human-robot collaboration (HRC) features the interaction between human operators and machines, which makes the research of human fatigue come into sight. However, most existing studies on human fatigue or efficiency detection are realized using detectors and models from bioelectronics, whose intrusive detection and decoding of electromyographic signal limits the generality and applicability of such methods. therefore, this study proposes a human fatigue extraction method based on video data. A new dataset on human manipulation is established by collecting video data of assembly operations to simulate the working status of human operators under smart manufacturing environment. With human skeletal data extracted from the video using a machine learning-based pose extraction tool, MediaPipe, a spatiotemporal analysis for critical skeleton points is implemented for working status categorization and learning using a stochastic gradient descent (SGD) classifier. In this way, the duration taken to complete an assembly task can be extracted as the operation time using the trained SGD classifier, and thus the time-varying operation time series data are obtained to show the trend of human fatigue level. An accuracy of 98.3% is obtained for working status identification for the dataset. Several quantitative indicators like pearson correlation, R-squared value, root mean squared error (RMSE), and Fréchet Distance, are used to evaluate the accuracy of both the extracted operation time and its time-varying curve as compared to the ground truth, with satisfactory results showing the effectiveness of the proposed method.

关键词： Accuracy Surveillance Time series analysis Switches Fatigue Data mining Robots Assembly Unsupervised learning Smart manufacturing

来源：评论

学校读者我要写书评

暂无评论

Incremental Latin Hypercube Additive Design for LOLIMOT 25

Incremental Latin Hypercube Additive Design for LOLIMOT

引用

25th IEEE international conference on Emerging Technologies and Factory automation (ETFA)

作者： Voigt, Tim Kohlhase, Martin Nelles, Oliver Bielefeld Univ Appl Sci Ctr Appl Data Sci Gutersloh Gutersloh Germany Univ Siegen Automat Control Mechatron Siegen Germany

ISBN: (纸本)9781728189567

Estimating data based models of industrial processes is an essential step in making existing production lines intelligent and increasing their flexibility and efficiency. the collection of data during the normal operation often does not provide sufficient information to achieve a high model quality, so that design of experiments methods are needed. In this paper a step-wise methodology for the design of experiments and modeling is proposed, which makes it more applicable for industrial processes. In contrast to commonly used experimental designs, in which all available inputs are varied at once, the proposed method starts with only one input and successively adds another input to the design in each step. the experimental design is combined with an incremental modeling strategy using LOLIMOT-trained models. Experimental results are presented based on a computer experiment and a heating system. In both experiments a model quality comparable to a standard approach is achieved.

关键词： design of experiments static process models LOLIMOT

来源：评论

学校读者我要写书评

暂无评论

DgrCLR: Dual Gradient Reinforcement Contrastive Learning for Coal Gangue Classification

DgrCLR: Dual Gradient Reinforcement Contrastive Learning for...

引用

robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Hongxi Li Wenbo Zhu Zhen Zhu Juqing Yang Jianwen Chen Haibing Li Zhongbo Zhang School of Electronic Information Engineering Foshan University Foshan China School of Mechatronic Engineering and Automation Foshan University Foshan China Electronic Information school Foshan polytechnic Foshan China

In the application of coal gangue visual classification, the influence of strong vibration and uneven illumination in an industrial environment causes the fuzzy boundary of the target and reduces the degree of discrimination of sample features. the existing contrastive learning methods cause apparent gradient degradation due to model and design limitations, leading to fuzzy sample classification failure. Getting rid of the samples with poor annotation effects and alleviating gradient degradation are critical issues in improving the accuracy of coal gangue classification. this paper proposes DgrCLR, a dual gradient reinforcement coal gangue classification algorithm based on improved contrastive learning. By designing the Hybrid reinforcement module and Multi-scale feature fusion module, the gradient degradation is alleviated, the dependence on labeled samples is reduced, and the detail representation ability of the model is improved. the experimental results show that the highest accuracy of the DgrCLR model for coal gangue classification is 85.4%, much higher than that of traditional supervised deep learning models. In addition, the gradient strength of DgrCLR is 20 times or higher than that of SimCLR in some model layers by gradient strength summation comparison.

关键词：

来源：评论

学校读者我要写书评

暂无评论

EDPCS: Efficient Dynamic Gesture Recognition under Point Cloud Sequences

EDPCS: Efficient Dynamic Gesture Recognition under Point Clo...

引用

robotics, Control and automation (ICRCA), international conference on

作者： He Miao Gao Quanli Wang Xihan Liang Jiao Li Jincao Gao Rongxin School of Computer Science Xi'an Polytechnic University Xi'an China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

Dynamic gesture recognition is an important part of virtual reality and human-computer interaction, while point clouds provide important clues for gesture recognition because they contain rich spatial information. However, dynamic gesture recognition under point cloud sequences is still facing challenges such as difficulty capturing spatio-temporal correlation and insufficient global feature integration capability. To address these challenges, in this paper, we describe gesture recognition as an irregular sequence recognition problem, with the goal of capturing spatio-temporal correlations between point cloud sequences and enhancing the salient features at certain locations in the sequences, and we propose a novel and effective method, EDPCS, which focuses on intra- and inter-frame feature extraction by introducing self-attention mechanism and cross-attention mechanism to enhance the model's spatio-temporal feature representation and improving the integration of global features to efficiently recognize dynamic gestures. Firstly, while maintaining the spatial structure, our method captures the global temporal dynamic features between point cloud frames through the self-attention mechanism in the intra-frame feature extraction stage; then, in the inter-frame feature extraction stage, the features of the neighbouring frames are fused into the current frame through the cross-attention mechanism, thus enhancing the feature extraction effect. this approach is not only effective in recognizing dynamic gestures but can also be integrated into many other sequence learning methods. In terms of gesture recognition, our method improves the classification accuracy from 86.1% to 88.6% on the NVGesture dataset and from 87.8% to 94.5% on the SHREC'17 Track dataset. the ablation experiments further validate the effectiveness of the self-attention mechanism and the cross-attention mechanism in our approach. Our study demonstrates that the dynamic gesture recognition method based on s

关键词： Point cloud compression Solid modeling Correlation Accuracy three-dimensional displays Dynamics Gesture recognition Virtual reality Feature extraction Data models

来源：评论

学校读者我要写书评

暂无评论

PointStack: A Point Cloud Processing Network with Enhanced Global Feature Aggregation

PointStack: A Point Cloud Processing Network with Enhanced G...

引用

Software Engineering and Computer Science (CSECS), international conference on

作者： Yongliang Tao Jintao Wang Pengchao Li Mingmin Liu Zhenjun Du Yang Liu Chengpeng Li Faculty of Robot Science and Engineering Northeastern university Shenyang China Central Research Academy ShanDong SIASUN Industrial Software Research Institute Co. Ltd Shandong China Central Research Academy SIASUN Robot & Automation Co. Ltd Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

Point cloud data, characterized by its rich geometric information, dense data representation, and flexible topological structure, finds extensive application in fields such as computer graphics, computer vision, and robotics perception. the rapid advancement and upgrade of three-dimensional point cloud acquisition devices have made the acquisition of point cloud data increasingly convenient. this, in turn, has spurred an urgent need for research on point cloud data processing. the irregularity and disorderliness of point clouds necessitate the design of network models that differ from those used for image processing. Presently, most network models for point cloud processing focus primarily on the design for local feature extraction, even though the effectiveness of these improvements has become somewhat marginal. In response to this, a stacked diffusion network model designed to capture global context has been proposed. this model excels at capturing global information and can effectively integrate it with local information. Extensive experiments conducted on standard benchmark datasets such as ModelNet40 and ShapeNetPart indicate that this model, in comparison to DGCNN, improves point cloud classification by 1.2%, achieving an Overall Accuracy (OA) of 94.1%. Furthermore, it enhances point cloud part segmentation by 1.3%, reaching an mIOU evaluation metric of 86.5%. When compared to other advanced methods, this model also exhibits noticeable improvements in point cloud classification and part segmentation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Reachability Analysis and Simulation for Hybridised Event-B models 17th

Reachability Analysis and Simulation for Hybridised Event-B ...

引用

17th international conference on Integrated Formal methods (IFM)

作者： Ait-Ameur, Yamine Bogomolov, Sergiy Dupont, Guillaume Singh, Neeraj Kumar Stankaitis, Paulius INPT ENSEEIHT 2 Rue Charles Camichel Toulouse France Newcastle Univ Sch Comp Newcastle Upon Tyne Tyne & Wear England

ISBN: (纸本)9783031077272;9783031077265

the development of cyber-physical systems has become one of the biggest challenges in the field of model-based system engineering. the difficulty stems from the complex nature of cyber-physical systems which have deeply intertwined physical processes, computation and networking system aspects. To provide the highest level of assurance, cyber-physical systems should be modelled and reasoned about at a system-level as their safety depends on a correct interaction between different subsystems. In this paper, we present a development framework of cyber-physical systems which is built upon a refinement and proof based modelling language - Event-B and its extension for modelling hybrid systems. To improve the level of automation in the deductive verification of the resulting hybridised Event-B models, the paper describes a novel approach of integrating reachability analysis in the proof process. Furthermore, to provide a more comprehensive cyber-physical system development and simulation-based validation, we describe mechanism for translating Event-B models of cyber-physical systems to Simulink. the process of applying our framework is evaluated by formally modelling and verifying a cyber-physical railway signalling system.

关键词： Hybrid systems Formal verification Event-B Reachability analysis Simulink

来源：评论

学校读者我要写书评

暂无评论

Learning Embeddings with Centroid Triplet Loss for Object Identification in Robotic Grasping

Learning Embeddings with Centroid Triplet Loss for Object Id...

引用

IEEE international conference on automation Science and Engineering (CASE)

作者： Anas Gouda Max Schwarz Christopher Reining Sven Behnke Alice Kirchheim TU Dortmund Lamarr Institute for Machine Learning and Artificial Intelligence Autonomous Intelligent Systems - Computer Science VI & Center for Robotics University of Bonn Germany Fraunhofer IML

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Foundation models are a strong trend in deep learning and computer vision. these models serve as a base for applications as they require minor or no further fine-tuning by developers to integrate into their applications. Foundation models for zero-shot object segmentation such as Segment Anything (SAM) output segmentation masks from images without any further object information. When they are followed in a pipeline by an object identification model, they can perform object detection without training. Here, we focus on training such an object identification model. A crucial practical aspect for an object identification model is to be flexible in input size (number of input images). As object identification is an image retrieval problem, a suitable method should handle multi-query multigallery situations without constraining the number of input images (e.g. by having fixed-size aggregation layers). the key solution to train such a model is the centroid triplet loss (CTL), which aggregates image features to their centroids. CTL yields high accuracy, avoids misleading training signals and keeps the model input size flexible. In our experiments, we establish a new state of the art on the ArmBench object identification task, which shows general applicability of our model. We furthermore demonstrate an integrated unseen object detection pipeline on the challenging HOPE dataset, which requires finegrained detection. there, our pipeline matches and surpasses related methods which have been trained on dataset-specific data. Code and pretrained models are available. 5

关键词： Training Location awareness Image segmentation Accuracy Pipelines Object detection Object segmentation Market research Object recognition Proposals

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122页 << < 40 41 42 43 44 45 46 47 48 49 > >>

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：