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

707 篇 会议
400 篇 期刊文献
4 册 图书

馆藏范围

1,111 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

763 篇 工学
- 444 篇 计算机科学与技术...
- 422 篇 软件工程
- 224 篇 控制科学与工程
- 130 篇 信息与通信工程
- 117 篇 机械工程
- 107 篇 生物工程
- 74 篇 环境科学与工程（可...
- 70 篇 电气工程
- 69 篇 生物医学工程（可授...
- 59 篇 光学工程
- 48 篇 仪器科学与技术
- 48 篇 化学工程与技术
- 42 篇 电子科学与技术（可...
- 35 篇 交通运输工程
- 28 篇 材料科学与工程（可...
- 28 篇 安全科学与工程
- 23 篇 动力工程及工程热...
- 20 篇 土木工程
381 篇 理学
- 183 篇 数学
- 111 篇 生物学
- 80 篇 物理学
- 55 篇 系统科学
- 52 篇 统计学（可授理学、...
- 40 篇 化学
- 19 篇 大气科学
217 篇 管理学
- 160 篇 管理科学与工程(可...
- 60 篇 图书情报与档案管...
- 28 篇 工商管理
38 篇 医学
- 30 篇 临床医学
- 26 篇 基础医学(可授医学...
17 篇 法学
13 篇 经济学
9 篇 农学
6 篇 教育学
1 篇 文学
1 篇 军事学
1 篇 艺术学

主题

47 篇 feature extracti...
35 篇 training
29 篇 deep learning
29 篇 predictive model...
26 篇 neural networks
24 篇 visualization
24 篇 semantics
20 篇 reinforcement le...
19 篇 convolution
16 篇 three-dimensiona...
16 篇 mathematical mod...
15 篇 object detection
15 篇 computational mo...
15 篇 forecasting
15 篇 adaptation model...
14 篇 adaptive dynamic...
14 篇 robots
14 篇 accuracy
14 篇 wastewater treat...
14 篇 convolutional ne...

机构

281 篇 faculty of infor...
259 篇 beijing key labo...
102 篇 beijing key labo...
79 篇 university of ch...
53 篇 engineering rese...
51 篇 school of artifi...
35 篇 beijing laborato...
30 篇 beijing universi...
27 篇 beijing key labo...
26 篇 guangdong engine...
23 篇 beijing institut...
23 篇 beijing laborato...
22 篇 college of elect...
22 篇 beijing laborato...
20 篇 beijing key labo...
19 篇 key laboratory o...
17 篇 beijing engineer...
17 篇 shenzhen institu...
17 篇 beijing universi...
16 篇 school of intern...

作者

59 篇 junfei qiao
47 篇 xiaoli li
41 篇 qiao junfei
35 篇 kang wang
32 篇 ding wang
32 篇 gang xiong
31 篇 han honggui
30 篇 jia kebin
27 篇 jian tang
26 篇 honggui han
23 篇 zuo guoyu
22 篇 zhen shen
22 篇 yang li
21 篇 xiong gang
21 篇 kebin jia
21 篇 feng jinchao
20 篇 xiaogang ruan
20 篇 guoyu zuo
19 篇 wu xinyu
19 篇 songmin jia

语言

1,049 篇 英文
45 篇 其他
18 篇 中文

检索条件"机构=Beijing Key Laboratory of Computing Intelligence and Intelligent System"

共 1111 条记录，以下是191-200 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：

Nonlinear system identification using deep belief network based on PLSR 36

Nonlinear system identification using deep belief network ba...

引用

第36届中国控制会议

作者： Wang Gongming Li Wenjing Qiao Junfei Wu Guandi Faculty of Information Technology Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Technical Test Center of Shengli Oilfield Branch Sinopec

ISBN: (纸本)9781538629185

Deep learning has been successfully applied into pattern recognition due to its deep architecture and effective unsupervised learning,and deep belief network(DBN) is a popular model based on deep learning *** this paper,a DBN identification model based on partial least square regression(PLSR),named PLSR-DBN,is proposed for nonlinear system *** order to improve the identification accuracy,PLSR is introduced into the supervised fine-tuning of DBN to elimate the overfitting and local minimum resulted from gradients-based learning,and contrastive divergence(CD) algorithm is used in unsupervised ***,the proposed PLSR-DBN is tested on a benchmark nonlinear *** experiment results show that the proposed PLSR-DBN has a better performance on nonlinear system identification than other similar methods.

关键词： Deep learning Deep belief network Nonliear system identification fine-tuning Partial least square regression

来源：评论

学校读者我要写书评

暂无评论

Driver fatigue detection system based on DSP platform 22nd

Driver fatigue detection system based on DSP platform

引用

22nd International Conference on MultiMedia Modeling, MMM 2016

作者： Li, Zibo Zhang, Fan Sun, Guangmin Zhao, Dequn Zheng, Kun Department of Electronic Engineering Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9783319276731

Due to non-invasiveness, monitoring driver state in computer vision (CV) has become a major way to detect driver fatigue. In contrast to other researches, we brought the driver fatigue detection system on the basis of DSP platform, which can make contribution to application on the integrated system for vehicle. However, the conventional system cannot easily be transplanted into DSP due to its storage and computation capacity. Therefore, designing an algorithm that can detect the fatigue efficiently is goal in this study. As the most important part of system, the geometric relationship and shape information within near frontal face is employed in the eye detection part, which depicts the eyebrow, eye and nose. In experiment part, a self-made database is assembled to test the performance of system. As the results of experiment, the detection rate of eye is achieved at 92.71% and driver fatigue state is obtained at 97.5%. © Springer International Publishing Switzerland 2016.

关键词： Digital signal processing

来源：评论

学校读者我要写书评

暂无评论

Position-based visual servo control of intelligent wheelchair/bed docking

Position-based visual servo control of intelligent wheelchai...

引用

2018 IEEE International Conference on Information and Automation, ICIA 2018

作者： Li, Xiuzhi Liang, Xingnan Fan, Jinhui Jia, Songmin Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9781538680698

For the automatic docking problem of a Mecanum-wheeled omnidirectional intelligent wheelchair/bed system, a visual servo control method which is based on position feedback is proposed in this paper. When it is docked with the auxiliary bed, the intelligent wheelchair firstly collects and identifies special landmark on the auxiliary bed through the vehicle vision system;Then the relative pose between the wheelchair and the auxiliary bed is determined according to the transformation between the camera coordinate system and the bed coordinate system based on an artificial landmark;Finally, the intelligent wheelchair is controlled to travel from the initial position to the desired position by position-based visual servo (PBVS) control method and completes docking task between the intelligent wheelchair and the auxiliary bed. The implementation of visual docking control for the intelligent wheelchair is based on the Robotic Operating system (ROS) platform. Experimental results are presented to validate the practicality and effectiveness of the proposed method in this paper. © 2018 IEEE.

关键词： Visual servoing

来源：评论

学校读者我要写书评

暂无评论

Data Preprocessing Method for Landslide Displacement Prediction Based on XG Boost 13

Data Preprocessing Method for Landslide Displacement Predict...

引用

13th IEEE Data Driven Control and Learning systems Conference, DDCLS 2024

作者： Luo, Shuang El, Xinhua Li, Xiaoli Beijing University of Technology Faculty of Information Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9798350361674

In machine learning-driven landslide prediction models, data quality directly determines the accuracy of landslide predictions. Currently, data preprocessing methods mainly involve fitting the data using moving averages or least squares methods. While these methods are effective and convenient for processing global data, they face limitations when dealing with local data during heavy rainfall events. The sharp increase in cumulative landslide displacement during significant rainfall makes it challenging for overall data preprocessing methods to effectively handle local data, leading to potential data loss and compromising data quality. To address this limitation, this paper proposes a segmented data processing approach. During periods of heavy rainfall, cubic spline interpolation is employed to interpolate missing data, providing a better representation of data variability. For smaller rainfall amounts, linear interpolation is utilized. Finally, the LOESS smoothing method is applied to further enhance data quality. These meticulous data processing steps aim to accurately capture the changing trends in rainfall-induced landslides. By providing more reliable inputs to machine learning prediction models, this approach seeks to improve the accuracy and reliability of landslide predictions. © 2024 IEEE.

关键词： Data accuracy

来源：评论

学校读者我要写书评

暂无评论

End-to-end Visual Navigation with Intrinsic Motivation in 3D Maze-like Environments

End-to-end Visual Navigation with Intrinsic Motivation in 3D...

引用

2021 China Automation Congress, CAC 2021

作者： Li, Peng Ruan, Xiao-Gang Zhu, Xiao-Qing Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9781665426473

Learning to navigate in visually rich environment with sparse reward is a long-standing problem in developing AI agent. In this paper, inspired by spontaneous exploration behaviour in animals, we proposed an end-to-end visual navigation method which use intrinsic reward to motivate explore-exploit strategy. Firstly, in order to directly obtain control policy from pixel-level input and implement end-to-end training, we take deep reinforcement learning as basic navigation framework. Secondly, we allow the agent to create reward for itself, and the intrinsic reward is related to episode memory and include two parts: (1) the frequency of agent reach a state is recorded, and these counts are then used to compute bonus according to the classic count-based method;(2) we also take temporal distance as a basis for distributing bonus, and the magnitude of it is determined by environment steps between current observation and those in memory. Finally, such intrinsic reward is summed up with the real task reward, thus making agent is able to use the combined reward to learn control policy. We test our approach in 3D maze-like environment in DMlab, and validate its navigation performance through different reward scenarios. The experiment results show our approach can get effective goal-driven behaviour from raw sensory input and outperform the baselines across all tasks. Furthermore, the agent equipped with our intrinsic motivation appear to explore faster in no reward environment. © 2021 IEEE

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

A Micro SLAM system Based on ORB for RGB-D Cameras

A Micro SLAM System Based on ORB for RGB-D Cameras

引用

2018 International Conference on Electrical Engineering, Control and Robotics, EECR 2018

作者： Wang, Fei Ruan, Xiaogang Dong, Pengfei Sie, Ouattara Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

In this paper, a micro SLAM system based on ORB features for RGB-D cameras has been proposed. With only a RGB-D sensor, this method can be applied in small environment for localization and mapping. Furthermore, the task of 3D reconstruction can also be accomplished by using the approach. The pose graph based on Bundle Adjustment is adopted for reducing the estimation error. In order to further speed up computing to meet the requirement of real-time, we have proposed the piecewise optimization strategy. The approach is evaluated on public benchmark datasets. Compared with several state-of-the-art scheme, this method has proven to work well in these environments. © The Authors, published by EDP Sciences, 2018.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Diffusion Ranking Scores Based Improved Hypergraph Generation Method for Visual Classification Tasks 13

Diffusion Ranking Scores Based Improved Hypergraph Generatio...

引用

13th IEEE Data Driven Control and Learning systems Conference, DDCLS 2024

作者： Wang, Shuai Wang, Kang Li, Xiaoli Beijing University of Technology Faculty of Information Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9798350361674

Visual classification has attracted considerable research attention in the last few decades. This paper presents an approach to improve the hypergraph structure using a diffusion ranking method and employs hypergraph neural networks for such tasks. Hyperedges are formed by connecting a set of vertices, and the generation of the hypergraph structure is typically task-dependent, making hypergraph generation methods less generalizable. Previous approaches have employed implicit hypergraphs for visual tasks, especially in visual classification, using attribute-based or neighborhood-based methods. However, these approaches cannot fully explore the global manifold structure of the feature space. To address this problem, this paper proposes a novel two-stage hypergraph construction method, which fully utilizes the ability of diffusion process to capture the manifold structure of feature data. Initially, the hypergraph structure is constructed using a neighbor-based approach, and subsequently, the final hypergraph structure is obtained by ranking scores of diffusion processes that reflect the degree of vertex similarity. Comparing with state-of-the-art hypergraph neural network algorithms on classical 3D visual image datasets, experimental results demonstrate the effectiveness of the proposed algorithm. © 2024 IEEE.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Monitoring of Wastewater Treatment Process Based on Slow Feature Analysis Variational Autoencoder 10

Monitoring of Wastewater Treatment Process Based on Slow Fea...

引用

10th IEEE Data Driven Control and Learning systems Conference, DDCLS 2021

作者： Wang, Kai Chang, Peng Meng, Fanchao Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9781665424233

The wastewater treatment process (WWTP) is a complex nonlinear, uncertain and dynamic physical and biochemical reaction process. The non-linearity, uncertainty and dynamicity of the WWTP increase the difficulty of extracting data features, and also make it difficult to monitor the faults in this process. Aiming at the problems of non-linearity, uncertainty and dynamicity, a slow feature variational autoencoder (SFAVAE) process monitoring model is proposed. With the dynamicity of WWTP data taken into account, the slow feature analysis algorithm (SFA) is used to extract the slowly changing dynamic features of wastewater data. The variational autoencoder can impose Gaussian distribution restrictions on its hidden layer features, so that it can simultaneously learn nonlinear and certain features that obey the Gaussian distribution to deal with the nonlinearity and uncertainty of data. Finally, the hidden layer space of the variational autoencoder model is used to construct hidden layer feature statistics Z2 to realize process monitoring. Compared with the principal component analysis (PCA), independent component analysis (ICA), kernel principal analysis (KPCA) and variational auto-encoder (VAE) models, the experimental results of the benchmark simulation model 1 (BSM1) model show that the SFAVAE model has higher effectiveness in process monitoring. © 2021 IEEE.

关键词： Process monitoring

来源：评论

学校读者我要写书评

暂无评论

The Batch Process Fault Monitoring Using Adversarial Auto-encoder and K-Nearest Neighbor Rule 10

The Batch Process Fault Monitoring Using Adversarial Auto-en...

引用

10th IEEE Data Driven Control and Learning systems Conference, DDCLS 2021

作者： Li, Zeyu Chang, Peng Wang, Kai Wang, Pu Beijing University of Technology Faculty of Information Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9781665424233

In the industrial batch process monitoring domain, the conventional multivariate monitoring methods may not always function well in monitoring faults that have both Non-Linear and Non-Gaussian properties. To enhance the monitoring capability, the adversarial auto-encoder (AAE) was introduced to increase the sensitivity to Non-Gaussian anomalies by projecting non-Gaussian information into a given Gaussian distribution feature space. At the same time, low-dimensional feature space can avoid the problem of 'Concentration of measure' and improve the ability to distinguish minor small abnormalities. Therefore, A novel statistic index was constructed in the feature space based on the k-nearest neighbor rule (KNN) to improve the ability of minor fault monitoring. The proposed model is compared with the traditional multivariate statistical process monitoring methods in numerical examples and penicillin fermentation platform, which proves that it has better monitoring ability for minor magnitude and non-Gaussian faults. © 2021 IEEE.

关键词： Gaussian distribution

来源：评论

学校读者我要写书评

暂无评论

A cognitive map learning model based on hippocampal place cells 2018

A cognitive map learning model based on hippocampal place ce...

引用

4th International Conference on Mechatronics and Robotics Engineering, ICMRE 2018

作者： Chai, Jie Ruan, Xiaogang Huang, Jing Zhu, Xiaoqing Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9781450363655

Aiming at the environment cognition and navigation problem of autonomous mobile robots in unknown environment, a cognitive map learning model is proposed based on hippocampal place cells, which can memorize and map surroundings. The model uses the self-organizing feature map as the basic structure. Each hippocampal place cell is represented by a neural node. The robot builds up the hippocampal place cells layer through environment exploration. The simulation results show that the model has self-learning ability, which enables robots to acquire environment knowledge and establish a complete cognitive map gradually like human beings and animals, making the robot's environment cognition and navigation process become more bionic and intelligent. © 2018 Association for computing Machinery.

关键词： Cells

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112页 << < 16 17 18 19 20 21 22 23 24 25 > >>

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：