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

258 篇 会议
122 篇 期刊文献

馆藏范围

380 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

238 篇 工学
- 180 篇 计算机科学与技术...
- 149 篇 软件工程
- 63 篇 信息与通信工程
- 27 篇 生物工程
- 26 篇 电气工程
- 25 篇 控制科学与工程
- 21 篇 机械工程
- 21 篇 电子科学与技术（可...
- 19 篇 光学工程
- 12 篇 仪器科学与技术
- 11 篇 化学工程与技术
- 10 篇 动力工程及工程热...
- 10 篇 交通运输工程
- 10 篇 生物医学工程（可授...
- 8 篇 环境科学与工程（可...
- 7 篇 土木工程
- 7 篇 安全科学与工程
- 6 篇 建筑学
138 篇 理学
- 85 篇 数学
- 32 篇 统计学（可授理学、...
- 29 篇 生物学
- 26 篇 物理学
- 11 篇 化学
- 7 篇 系统科学
75 篇 管理学
- 44 篇 管理科学与工程(可...
- 32 篇 图书情报与档案管...
- 22 篇 工商管理
20 篇 法学
- 17 篇 社会学
10 篇 医学
- 9 篇 临床医学
7 篇 经济学
- 7 篇 应用经济学
3 篇 教育学
3 篇 农学

主题

30 篇 feature extracti...
16 篇 semantics
11 篇 optimization
9 篇 deep learning
9 篇 image segmentati...
9 篇 cloud computing
9 篇 data models
9 篇 training
8 篇 predictive model...
7 篇 reinforcement le...
7 篇 big data
7 篇 data mining
7 篇 machine learning
6 篇 task analysis
6 篇 computational mo...
6 篇 particle swarm o...
6 篇 genetic algorith...
6 篇 clustering algor...
6 篇 computer vision
5 篇 computation offl...

机构

62 篇 college of mathe...
62 篇 college of compu...
38 篇 fujian provincia...
35 篇 fujian key labor...
26 篇 fujian key labor...
19 篇 engineering rese...
18 篇 fujian provincia...
17 篇 key laboratory o...
15 篇 fujian provincia...
11 篇 key laboratory o...
11 篇 key laboratory o...
9 篇 key laboratory o...
7 篇 shandong college...
7 篇 shandong provinc...
7 篇 peng cheng labor...
7 篇 fuzhou universit...
7 篇 college of mathe...
7 篇 fujian provincia...
7 篇 fujian provincia...
7 篇 school of inform...

作者

29 篇 guo wenzhong
20 篇 guo kun
14 篇 wenzhong guo
13 篇 xing chen
13 篇 xianghan zheng
12 篇 wang shiping
12 篇 chen xing
11 篇 yu zhiyong
10 篇 guolong chen
9 篇 xiao ke
9 篇 li jinping
8 篇 xiaodong wu
8 篇 zheng xianghan
8 篇 ke xiao
8 篇 yanhua liu
8 篇 wu ling
7 篇 huang fangwan
7 篇 kun guo
7 篇 genggeng liu
6 篇 lin dazhen

语言

364 篇 英文
14 篇 中文
7 篇 其他

检索条件"机构=Fujian Key Laboratory of Network Computing and Intelligent Information Processing"

共 380 条记录，以下是161-170 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：

Data Replication Placement Strategy Based On Bidding Mode for Cloud Storage Cluster

Data Replication Placement Strategy Based On Bidding Mode fo...

引用

2014 11th Web information System and Application Conference(第十一届全国web信息系统及其应用学术会议)

作者： Hong Zhang Bing Lin Zhanghui Liu Wenzhong Guo College of Mathematics and Computer Science Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou 350116 China

ISBN: (纸本)9781479957286

The data availability in large-scale cloud storage has been increasing by means of data *** provide cost-effective availability, minimize the response time of applications and make load balancing for cloud storage, a new replica placement policy with bidding thought is *** policy combines the own characteristics of replica and factors of bidding mode(e.g, bidding time, bidding standard, bidding price etc.) and starts replica bidding activity when the file data availability cannot meet the given *** placement is based on capacity and accessing probability of data *** experimental results show that our policy has a better performance in both load balance and response time comparing to the static replica policy and CDRM scheme.

关键词： Data Replica Bidding Mode Cloud Storage Load Balance

来源：评论

学校读者我要写书评

暂无评论

Camera Abnormal Movement and Foreign Object Invasion Detection Based on Cumulative Edge Distribution Probability Model

Camera Abnormal Movement and Foreign Object Invasion Detecti...

引用

2018 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2018

作者： Yu, Xiangru Cai, Fudong Dou, Yimin Li, Jinping Institute of Pattern Recognition and Intelligent System School of Information Science and Engineering University of Jinan Jinan China Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan China Shandong College University Key Laboratory of Information Processing and Cognitive Computing in 13th Five-year University of Jinan Jinan China Shandong Senter Electronic Co. Ltd Zibo China

ISBN: (纸本)9781728105512

In practice, there often exist some occasions where video surveillance can only be realized by using rechargeable batteries due to the high cost of power supply. In order to extend the battery life, images can only be taken at a certain interval. Obviously, image difference is an important method to obtain various changes in this case. Among these changes, foreign invasion is one of the focuses. However, due to bolt shedding, abnormal weather and other factors, the camera may have abnormal movement which may seriously affect the detection effect of image difference method. Therefore, it is an urgent issue to find an effective way to detect the abnormal movement of camera and improve the detection accuracy of foreign invasion. Considering the characteristics of this kind of image sequences, we propose an effective algorithm to detect the camera abnormal movement and foreign object invasion based on a cumulative edge distribution probability model. Since sky region is relatively simple, we only discuss changes in sky region to detect camera abnormal movement. Our algorithm has 6 basic steps: firstly, segment the sky region;secondly, extract the edge information of the current image and the preceding adjacent image in the image sequence;thirdly, determine if the edge information of two adjacent images coincide. If consistent, then go to the next step, otherwise, it indicates that the camera has abnormal movement, then alarm;fourthly, calculate the cumulative edge probability distribution model in the sky region by using the historical image sequence;fifthly, by using adaptive Parzen window, determine if foreign object invasion exists by comparing the probability model of cumulative edge distribution with edge distribution of the current image;sixthly, update the cumulative edge distribution probability model in sky region. The algorithm achieves good results in practical applications. Through the test of thousands of images taken in the wild, the detection accuracy of

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Exploring multi-loss function based attention framework for vehicle re-identification 10

Exploring multi-loss function based attention framework for ...

引用

10th International Conference on information Technology in Medicine and Education, ITME 2019

作者： Liu, Wei Zhang, Yi Luo, Zhiming Li, Shaozi East China Jiaotong University Jiangxi China Cognitive Science Department Xiamen University Fujian China Postdoc Center of Information and Communication Engineering Xiamen University China Key Lab. of Cogn. Computing and Intelligent Information Processing of Fujian Education Institutions Wuyishan China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering Yi Chang China

ISBN: (纸本)9781728139173

Vehicle Re-identification(Re-ID) refers to the task of matching a specific vehicle across multiple non-overlapping cameras. Precise vehicle Re-ID suffers from two main challenges: (1) different vehicle identities with a similar appearance of the same type have a subtle inter-instance discrepancy, (2) one vehicle usually has large intra-instance differences due to viewpoint and illumination variations. To address these challenges, in this paper, we proposed an Attention-based Framework for Vehicle Re-ID named AFVR, which combines the benefits of both the cross-entropy loss function and the triplet loss function. Experimental results on two popular vehicle Re-ID benchmarks demonstrate the effectiveness of our proposed method, compared with the state of the arts. © 2019 IEEE.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

Point matching of two images under large different resolution

Point matching of two images under large different resolutio...

引用

MIPPR 2007: Automatic Target Recognition and Image Analysis;and Multispectral Image Acquisition

作者： Ruan, Lei Hu, Maolin Lab. of Intelligent Computing and Signal Processing AnHui University Hefei AnHui 230039 China Key Laboratory of Wireless Sensor Network and Communication Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China

ISBN: (纸本)9780819469502

Image matching is the first step in almost any 3D computer vision task, and hence has received extensive attention. In this paper, the problem is addressed from a novel perspective, which is different from the classic stereo matching paradigm. Two images with different resolutions, that is high resolution versus low resolution are matched. Since the high resolution image only corresponds to a small region of the low resolution one, the matching task therefore consists in finding a small region in the low resolution image that can be assigned to the whole high resolution image under the plane similarity transformation, which can be defined by the local area correlation coefficient to match the interest points and rectified by similarity transform. Experiment shows that our matching algorithm can be used for scale changing up to a factor of 6. And it is successful to deal with the point matching between two images under large scale.

关键词： Image matching

来源：评论

学校读者我要写书评

暂无评论

Research on Futures Programmed Trading Based on Deep Reinforcement Learning

Research on Futures Programmed Trading Based on Deep Reinfor...

引用

International Conference on Cloud computing, Big Data and Blockchain (ICCBB)

作者： Weipeng Xie Xianghan Zheng College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China

ISBN: (纸本)9781728112787

There are many categories in the financial market, and futures market plays a very important role. How to make the most profit in futures market is a problem that investors, fund organizations and private placement teams have been studying all along. This paper constructs a futures investment decision model based on intensive learning model theory, makes graphical conversion according to historical time series data, defines the return of strategies for local strategy banks, trains a DQN network, automatically switches strategies, and ensures the maximization of gains.

关键词： Market research Switches Reinforcement learning Investment Data models Wavelet analysis Contracts

来源：评论

学校读者我要写书评

暂无评论

Adaptively Extracting Structured Data from Web Pages

Adaptively Extracting Structured Data from Web Pages

引用

IEEE International Conference on Big Data and Cloud computing (BdCloud)

作者： Yingnan Guo Jiajun Zhang Xing Chen College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Web pages contain a large amount of valuable information and resources, meanwhile may update at any time. However, the current Web-data extraction algorithms are generally targeted at specific web page structure. When web pages update, the problem which is caused by the changes of web pages may be encountered, leading to the inability to extract web page information or wrong information. In order to solve this problem, this paper proposes a new method to extract the feature values of each area in the web page through page rendering, and then combine the DOM tree structure of the page, semantic similarity and other information, so that it can still extract the target data correctly after the structure of the web page changes.

关键词： Data mining Web pages Feature extraction Layout Indexes Distributed processing Big Data

来源：评论

学校读者我要写书评

暂无评论

SFTA: Spiking Neural networks Vulnerable to Spiking Feature Transferable Attack

SFTA: Spiking Neural Networks Vulnerable to Spiking Feature ...

引用

IEEE International Symposium on Parallel and Distributed processing with Applications and IEEE International Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Xuanwei Lin Chen Dong Ximeng Liu College of Computer and Data Science Fuzhou University Fujian Key Laboratory of Network Computing and Intelligent Information Processing (Fuzhou University) Key Lab of Information Security of Network Systems (Fuzhou University)

Many recent works have shown that spiking neural networks (SNNs) are vulnerable to well-crafted adversarial attacks in the white-box setting, which may lead to misclassification of the trained model. However, the information about the model is in a black-box setting and is usually unknown to the attacker, e.g., the parameters and structure of the model. So it is more challenging to counter the attack in the black-box setting, and there is still little research on this aspect in SNNs. Therefore, this work describes a transfer-based black box adversarial attack against spike feature space representations, providing insights for robust spike features in SNNs models. The attack is explicitly designed to be transferable, and more robust feature gradients are obtained by accumulating the feature gradients of the intermediate layers. Then we can successfully attack the black-box model by suppressing robust positive features and enhancing negative features. Extensive experimental evaluation demonstrates the proposed method’s effectiveness and superior performance on static and neuromorphic datasets. i.e., The attack success is 89.72% and 90% on the static MNIST and CIFAR10 datasets, and 85.97% and 69.09% on the neuromorphic N-MNIST and CIFARO-DVS datasets.

关键词： Correlation Neuromorphics Neural networks Closed box Ubiquitous computing Optimization Glass box

来源：评论

学校读者我要写书评

暂无评论

IF-Font: Ideographic Description Sequence-Following Font Generation 38

IF-Font: Ideographic Description Sequence-Following Font Gen...

引用

38th Conference on Neural information processing Systems, NeurIPS 2024

作者： Chen, Xinping Ke, Xiao Guo, Wenzhong Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing College of Computer and Data Science Fuzhou University Fuzhou350116 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou350116 China

Few-shot font generation (FFG) aims to learn the target style from a limited number of reference glyphs and generate the remaining glyphs in the target font. Previous works focus on disentangling the content and style features of glyphs, combining the content features of the source glyph with the style features of the reference glyph to generate new glyphs. However, the disentanglement is challenging due to the complexity of glyphs, often resulting in glyphs that are influenced by the style of the source glyph and prone to artifacts. We propose IF-Font, a novel paradigm which incorporates Ideographic Description Sequence (IDS) instead of the source glyph to control the semantics of generated glyphs. To achieve this, we quantize the reference glyphs into tokens, and model the token distribution of target glyphs using corresponding IDS and reference tokens. The proposed method excels in synthesizing glyphs with neat and correct strokes, and enables the creation of new glyphs based on provided IDS. Extensive experiments demonstrate that our method greatly outperforms state-of-the-art methods in both one-shot and few-shot settings, particularly when the target styles differ significantly from the training font styles. The code is available at https://***/Stareven233/IF-Font. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Multi-scale Framework for Out-of-Distribution Detection in Dermoscopic Images 1

引用

4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Huang, Zhongzheng Wang, Tao Cai, Yuanzheng Liang, Lingyu College of Computer and Data Science Fuzhou University Fuzhou350108 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering and International Digital Economy College Minjiang University Fuzhou350108 China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyi University Wuyishan354300 China Fujian Yilian-Health Nursing Information Technology Co. Ltd. Fuzhou350003 China School of Electronic and Information Engineering South China University of Technology Guangzhou510641 China

ISBN: (数字)9783031200960

ISBN: (纸本)9783031200953

The automatic detection of skin diseases via dermoscopic images can improve the efficiency in diagnosis and help doctors make more accurate judgments. However, conventional skin disease recognition systems may produce high confidence for out-of-distribution (OOD) data, which may become a major security vulnerability in practical applications. In this paper, we propose a multi-scale detection framework to detect out-of-distribution skin disease image data to ensure the robustness of the system. Our framework extracts features from different layers of the neural network. In the early layers, rectified activation is used to make the output features closer to the well-behaved distribution, and then an one-class SVM is trained to detect OOD data;in the penultimate layer, an adapted Gram matrix is used to calculate the features after rectified activation, and finally the layer with the best performance is chosen to compute a normality score. Experiments show that the proposed framework achieves superior performance when compared with other state-of-the-art methods in the task of skin disease recognition. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Chemical activation

来源：评论

学校读者我要写书评

暂无评论

A New network Intrusion Detection based on Semi-supervised Dimensionality Reduction and Tri-LightGBM

A New Network Intrusion Detection based on Semi-supervised D...

引用

Pervasive Artificial Intelligence (ICPAI), International Conference on

作者： Hao Zhang Jieling Li College of Mathematics and Computer Science Fuzhou University Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China

ISBN: (数字)9781665404839

ISBN: (纸本)9781665404846

With the development of technology and threat forms, network intrusion detection has become a challenging task. The intrusion detection algorithm based on supervised learning requires a lot of manpower and material resources to obtain a large amount of labeled data. Besides, the accuracy of unsupervised learning can not meet the requirements of intrusion detection systems. We propose a semi-supervised network intrusion detection method in this paper. information Gain is employed to filter redundancy features. Then, we combine labeled samples with unlabeled samples and adopt Principal Component Analysis (PCA) to convert multiple features into comprehensive features. Finally, an Tri-Training strategy is adopted to integrate the basic LightGBM classifier, and make full use of unlabeled data to generate pseudo labels, thereby optimizing the basic LightGBM classifier. To verify the effectiveness of the proposed approach, a large number of experiments are performed on the UNSW-NB15 dataset. The experimental results fully show that the method is superior in improving detection efficiency and reducing label dependence, and has a lower false alarm rate and a higher detection rate.

关键词： Manganese Graphics processing units Artificial intelligence

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38页 << < 13 14 15 16 17 18 19 20 21 22 > >>

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：