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

169 篇 会议
145 篇 期刊文献

馆藏范围

314 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

249 篇 工学
- 158 篇 计算机科学与技术...
- 144 篇 软件工程
- 71 篇 信息与通信工程
- 48 篇 光学工程
- 40 篇 生物工程
- 34 篇 机械工程
- 26 篇 电气工程
- 26 篇 生物医学工程（可授...
- 24 篇 电子科学与技术（可...
- 21 篇 控制科学与工程
- 12 篇 化学工程与技术
- 10 篇 交通运输工程
- 9 篇 仪器科学与技术
- 8 篇 材料科学与工程（可...
- 7 篇 建筑学
- 6 篇 土木工程
- 5 篇 力学（可授工学、理...
142 篇 理学
- 64 篇 数学
- 50 篇 物理学
- 44 篇 生物学
- 22 篇 统计学（可授理学、...
- 12 篇 化学
- 11 篇 系统科学
63 篇 管理学
- 44 篇 图书情报与档案管...
- 23 篇 管理科学与工程(可...
- 6 篇 工商管理
12 篇 医学
- 12 篇 基础医学(可授医学...
- 12 篇 临床医学
- 10 篇 药学(可授医学、理...
8 篇 法学
- 8 篇 社会学
3 篇 经济学
3 篇 教育学
2 篇 农学
1 篇 军事学
1 篇 艺术学

主题

11 篇 deep learning
11 篇 training
9 篇 semantics
9 篇 feature extracti...
7 篇 compressed sensi...
7 篇 magnetic resonan...
7 篇 convolution
6 篇 image coding
6 篇 image classifica...
6 篇 image reconstruc...
5 篇 generative adver...
5 篇 image segmentati...
5 篇 face recognition
5 篇 optimization
5 篇 estimation
5 篇 computer vision
5 篇 encoding
5 篇 shape
4 篇 image enhancemen...
4 篇 object detection

机构

25 篇 shenyang institu...
24 篇 university of ch...
23 篇 fujian key labor...
20 篇 school of comput...
18 篇 school of comput...
16 篇 school of comput...
14 篇 institutes for r...
14 篇 jiangsu key labo...
11 篇 college of compu...
9 篇 key laboratory o...
9 篇 key laboratory o...
9 篇 key laboratory o...
9 篇 key laboratory o...
9 篇 jiangsu key labo...
8 篇 key laboratory o...
8 篇 fujian key labor...
8 篇 key laboratory o...
8 篇 key laboratory o...
7 篇 key laboratory o...
7 篇 key laboratory o...

作者

30 篇 yang jian
22 篇 gong maoguo
20 篇 wang da-han
20 篇 liu fang
20 篇 jiao licheng
18 篇 gong chen
15 篇 wu yue
12 篇 li hao
11 篇 licheng jiao
10 篇 ma wenping
9 篇 zhu shunzhi
9 篇 jian yang
8 篇 luo haibo
8 篇 miao qiguang
8 篇 haibo luo
8 篇 wan sheng
7 篇 da-han wang
7 篇 hao hongxia
6 篇 weng wei
6 篇 shang fanhua

语言

300 篇 英文
11 篇 中文
4 篇 其他

检索条件"机构=The Key Laboratory of Image Understanding and Computer Vision"

共 314 条记录，以下是51-60 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：

Multi-Head Attention Mechanism for MultiStation Passenger Flow Prediction

Multi-Head Attention Mechanism for MultiStation Passenger Fl...

引用

2022 International Symposium on Design Studies and Intelligence Engineering, DSIE 2022

作者： Chen, Long Liu, Lijuan Yuan, Lei College of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen361024 China

ISBN: (纸本)9781643683720

Passenger flow prediction is of great significance for public transportation. Most of the existing studies mainly predict the flow for a single station only extracting temporal features without considering spatial features. Passenger flow predicting for multiple stations or even the whole network is beneficial to grasp the overall situation, which has more research value in practical application. Thus, a passenger flow prediction model for multiple stations has been proposed based on spatio-Temporal attention mechanism. This model is applied to Xiamen bus rapid transit (BRT) using the time granularity of 5-min. The experimental results demonstrate that our model improves the prediction accuracy compared to the baselines. © 2023 The authors and IOS Press.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

image Segmentation of Endoscopic Cataract Based on Semantic Segmentation 6

Image Segmentation of Endoscopic Cataract Based on Semantic ...

引用

2022 6th International Conference on Machine vision and Information Technology, CMVIT 2022

作者： Chen, Jingshi Ye, Haili Yin, Huayi Wang, Da-Han Li, Jianmin School of Computer and Information Engineering Xiamen University of Technology Xiamen361000 China Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen361000 China

Medical imaging technology has become one of the indispensable computer-assisted intervention methods in clinical disease diagnosis and treatment, including identifying and locating lesion areas, detecting and segmenting tissue and organ lesions in different modalities. The wide application of medical image analysis in clinical examination and medical auxiliary diagnosis has effectively improved the diagnostic efficiency of doctors. In this paper, we propose a novel and effective model to achieve semantic segmentation of cataract datasets. This model uses the self-supervised method BYOL for parameter pre-training, which improves the model's ability to extract image consistency features. In addition, we have added a lightweight Coordinate attention mechanism to the backbone network to enable the model to independently learn the correlation between the channel and the space and enhance the ability of network feature expression. Experiments are conducted on the cataract endoscopy fine-grained segmentation data set, showing the effectiveness of the proposed method for segment the organs and surgical instruments in the cataract surgical microscope image, which demonstrates the accuracy and robustness of the proposed method. © Published under licence by IOP Publishing Ltd.

关键词： Endoscopy

来源：评论

学校读者我要写书评

暂无评论

Reference point-based evolutionary multi-objective optimization for reversible logic circuit synthesis 7

Reference point-based evolutionary multi-objective optimizat...

引用

2014 7th International Conference on BioMedical Engineering and Informatics, BMEI 2014

作者： Wang, Xiaoxiao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xidian University Xi'an China School of Computer Science Xi'An Shiyou University Xi'an China

ISBN: (纸本)9781479958382

In this paper, Reversible logic circuit synthesis is formulated as a quantum cost-minimization problem with equality constraint. A new reference-point based evolutionary multi-objective method R-EMO-RLC is specially designed to attack the equality constraint. First, the reference point is determined dynamically according the distribution of solutions. Then, a new crowding comparative operator is fabricated to adapt the uncertainty of constraint violation and objective value aroused by variable length encoding. Experimental results show that R-EMO-RLC can increase the feasible ratio and obtain savings in quantum cost for some benchmarks from recent publications comparing with previously known circuits. © 2014 IEEE.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Multi-objective Gene Expression Programming Based Automatic Clustering Method 9th

Multi-objective Gene Expression Programming Based Automatic ...

引用

9th International Symposium on Intelligence Computation and Applications, ISICA 2017

作者： Liu, Ruochen Li, Jianxia He, Manman Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi’an710071 China School of Computer Xi’an Shiyou University Xi’an710065 China

ISBN: (纸本)9789811316470

We have proposed multi-objective Gene Expression Programming (GEP) based automatic clustering method (do not need prior knowledge), which is denoted as MOGEPC. In our algorithm, we adopt GEP based multi-objective optimization, which has a powerful global search ability to optimize the two objective functions, namely, compactness and connectedness simultaneously. We use center-based encoding to generate chromosomal in the encoding phase and expression tree (ET) to decode chromosome to cluster centers. The introduction of multi-objective in GEP is helpful to make the clustering quality of data sets with different structures better. Finally, we apply MOGEPC on artificial data sets, real data sets from UCI. Experiments show that MOGEPC is robust in clustering various data sets without any apriori information. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

image Super-resolution Reconstruction Based on Bionic Intelligence 4

Image Super-resolution Reconstruction Based on Bionic Intell...

引用

4th IEEE International Conference on image, vision and Computing, ICIVC 2019

作者： Wang, Xin Wang, Qiong Lv, Guofang Nanjing University of Science and Technology Jiangsu Key Laboratory of Image and Video Understanding for Social Safety Nanjing China Hohai University College of Computer and Information Nanjing China

ISBN: (纸本)9781728123257

Traditional super-resolution reconstruction methods usually process a low resolution image as a whole, which ignores the differences among image patches, resulting in ineffective reconstruction result. In this paper, we adopt the concept of patch as the basic unit of super resolution reconstruction, and establish a novel image super-resolution reconstruction method based on bionic intelligence. The original low resolution image is initially reconstructed by bicubic interpolation. Then, a biological visual attention mechanism inspired approach is applied to the initial reconstruction result to detect the salient regions. Subsequently, a super-resolution convolutional neural network model is applied to the salient image patches so as to get the precise reconstruction results. Extensive experiments manifest that the proposed method outperforms many current state-of-the-art schemes in reconstruction quality, and achieves fast speed for practical application. © 2019 IEEE.

关键词： Bionics

来源：评论

学校读者我要写书评

暂无评论

Pinning consensus in networks with time-varying topology and event-triggered diffusions via impulsive control 35

Pinning consensus in networks with time-varying topology and...

引用

第35届中国控制会议

作者： HAN Yujuan LU Wenlian LIU Bo CHEN Tianping College of Information Engineering Shanghai Maritime University School of Mathematical Sciences Fudan University Key Laboratory of Intelligent Perception and Image Understanding Xidian University School of Computer/Mathematics Sciences Fudan University

ISBN: (纸本)9781509009107

This paper studies pinning consensus of networks with time-varying topology via impulsive control. Event-triggered rules are employed in diffusion coupling terms to reduce the updating load of the coupled system. Sufficient conditions to pin the network to a prescribed value are proposed. It is proved that in case the coupling matrix across time intervals with length less than some given constant has spanning trees, then the proposed algorithms can realize consensus on the prescribed value when the impulsive controller is imposed randomly on one agent with appropriate impulsive strength and impulse intervals. The imposed pulses can be very sparse, with the impulsive intervals being lower bounded. Two kinds of event-triggered schemes coexist in this pinning control algorithm, one for updating the coupling diffusions;one for applying the impulsive control. Examples with numerical simulation are provided to show the effectiveness of the theoretical results.

关键词： Event-triggered Pinning Impulsive Scheme Time-varying Topology

来源：评论

学校读者我要写书评

暂无评论

Uncertainty Quantification in Medical image Segmentation

Uncertainty Quantification in Medical Image Segmentation

引用

International Conference on computer and Communications (ICCC)

作者： Haixing Li Haibo Luo The Key Lab of Image Understanding and Computer Vision Shenyang City Liaoning Province China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

In medical images, the observer's manual description of different structures is very different, and it spans a wide range of various structures and pathologies. This variability (which is a characteristic of biological issues, imaging modality and expert annotators) has not been fully considered in the design of computer algorithms for medical image quantification. So far, few people predict the uncertainty of medical image segmentation. In this paper, we designed a V-shaped network to quantify the uncertainty in prostate MRI image segmentation. We have embedded a feature pyramid attention module in the backbone network, which can extract high-level semantic context information at different scales and provide a pixel-level attention to the decoder. At the same time, the module will not bring a large computational burden. In our experiments, we tested the performance of the proposed method on 55 clinical subjects.

关键词： image segmentation Uncertainty Magnetic resonance imaging Semantics Feature extraction Prediction algorithms Biomedical imaging

来源：评论

学校读者我要写书评

暂无评论

Terahertz compressive imaging: understanding and improvement by a better strategy for data selection

Terahertz compressive imaging: understanding and improvement...

引用

作者： Xing, Chungui Qi, Feng Liu, Zhaoyang Wang, Yelong Guo, Shuxu State Key Laboratory on Integrated Optoelectronics College of Electronic Science and Engineering Jilin University Changchun China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang China Key Lab of Image Understanding and Computer Vision Shenyang China

Compressive sensing (CS) is a novel sampling modality, which indicates the signals can be sampled at a rate much below the Nyquist sampling rate. CS has increasing interest recently due to high demand of rapid, efficient, and in-expensive signal processing applications in the μmWave and mmWave frequencies, such as communication and imaging. There have been a lot of theoretical studies on this topic, but there is a lack of systematic experimental analysis of the implementation method itself. In this paper, we have investigated the influencing factors of terahertz compressive sensing based on experimental results, including illumination and the size of the pixel. Besides, to differentiate from current approaches, which generally make full use of the data, we propose to sort the data first and select a part of them based on amplitude, which might deliver a better image by prompting the mathematical calculations compulsively. We believe that such considerations given above would help to make a better system design and improve the performance of compressive imaging, and these results will also be helpful in the application of terahertz communication. © 2021 John Wiley & Sons, Ltd

关键词： Compressed sensing

来源：评论

学校读者我要写书评

暂无评论

A Dynamic Spatio-temporal Network with Self-attention for Multi-station Passenger Flow Prediction 12

A Dynamic Spatio-temporal Network with Self-attention for Mu...

引用

12th International Conference on Awareness Science and Technology, iCAST 2023

作者： Wang, Fengzhi Lv, Qinzhi Liu, Lijuan College of Computer and Information Engineering Xiamen University of Technology Xiamen China College of Computer and Information Engineering Xiamen University of Technology Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen China

ISBN: (纸本)9798350324693

Passenger flow prediction is vitally significant for intelligent transportation systems (ITS). Most of the studies typically focus on the passenger flow prediction for an individual station, and only capture the temporal features without considering any spatial features. Constructing a passenger flow prediction model for multiple stations, or even a whole network, is more valuable for practical applications. Therefore, we develop a dynamic spatio-temporal network (DSTNet) with a self-attention (SA) mechanism for multi-station passenger flow prediction. A dynamic graph convolutional network (DGCN) is applied for the spatial feature extraction, and gated recurrent unit (GRU) is combined to learn the temporal features. SA is applied to further assign the weights for the extracted spatio-temporal features. The Experiment has been conducted on the passenger flow in the Xiamen bus rapid transit (BRT). The results demonstrate that the proposed DSTNet with SA (SA-DSTNet) outperforms the baselines in the multi-station passenger flow prediction task. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Sensitiveness Based Strategy for Network Compression 2

Sensitiveness Based Strategy for Network Compression

引用

2nd International Conference on Industrial Artificial Intelligence, IAI 2020

作者： Lu, Yiheng Feng, Kaiyuan Li, Hao Wu, Yue Gong, Maoguo Xu, Yaoting School of Electronic Engineering Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xidian University China School of Computer Science and Technology Xidian University China

ISBN: (纸本)9781728182162

The success of convolutional neural networks has contributed great improvement on various tasks. Typically, larger and deeper networks are designed to increase performance on classification works, such as AlexNet, VGGNets, GoogleNet and ResNets, which are composed by enormous convolutional filters. However, these complicated structures constrain models to be deployed into real application due to limited computational resources. In this paper, we propose a simple method to sort the importance of each convolutional layer, as well as compressing network by removing redundant filters. There are two implications in our work: 1) Downsizing the width of unimportant layers will lead to better performance on classification tasks. 2) The random-pruning in each convolutional layer can present similar results as weight-searching algorithm, which means that structure of the network dominates its ability of representation. As a result, we reveal the property of different convolutional layers for VGG-16, customized VGG-4 and ResNet-18 on different datasets. Consequently, the importance of different convolutional layers is described as sensitiveness to compress these networks greatly. © 2020 IEEE.

关键词： image classification

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32页 << < 2 3 4 5 6 7 8 9 10 11 > >>

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：