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

6,437 篇 会议
961 篇 期刊文献
4 篇 学位论文
1 册 图书

馆藏范围

7,403 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,187 篇 工学
- 1,125 篇 电气工程
- 924 篇 计算机科学与技术...
- 665 篇 信息与通信工程
- 272 篇 控制科学与工程
- 203 篇 仪器科学与技术
- 165 篇 机械工程
- 164 篇 软件工程
- 128 篇 电子科学与技术（可...
- 101 篇 交通运输工程
- 101 篇 生物医学工程（可授...
- 88 篇 测绘科学与技术
- 72 篇 航空宇航科学与技...
- 34 篇 土木工程
- 29 篇 生物工程
- 24 篇 环境科学与工程（可...
- 19 篇 网络空间安全
- 17 篇 船舶与海洋工程
- 16 篇 光学工程
284 篇 理学
- 80 篇 系统科学
- 62 篇 物理学
- 50 篇 地球物理学
- 34 篇 数学
- 34 篇 生物学
- 22 篇 地理学
180 篇 医学
- 120 篇 临床医学
- 29 篇 基础医学(可授医学...
164 篇 管理学
- 155 篇 管理科学与工程(可...
49 篇 农学
- 26 篇 作物学
- 22 篇 农业资源与环境
35 篇 文学
- 35 篇 新闻传播学
14 篇 艺术学
6 篇 军事学
5 篇 经济学
4 篇 教育学
3 篇 法学

主题

7,403 篇 detection algori...
757 篇 detectors
754 篇 feature extracti...
621 篇 algorithm design...
576 篇 object detection
531 篇 image edge detec...
383 篇 testing
364 篇 robustness
330 篇 cameras
307 篇 computer science
283 篇 monitoring
277 篇 accuracy
274 篇 data mining
265 篇 computational mo...
255 篇 image segmentati...
234 篇 signal to noise ...
233 篇 clustering algor...
199 篇 change detection...
195 篇 pixel
191 篇 electrocardiogra...

机构

17 篇 school of electr...
15 篇 beijing universi...
13 篇 department of el...
13 篇 department of el...
11 篇 institute for in...
11 篇 department of el...
10 篇 national mobile ...
9 篇 department of el...
9 篇 wireless theorie...
8 篇 department of el...
8 篇 graduate school ...
8 篇 department of au...
8 篇 institute of com...
7 篇 beijing key labo...
7 篇 school of electr...
7 篇 department of el...
7 篇 department of el...
7 篇 department of el...
7 篇 mit lincoln labo...
7 篇 southeast univ n...

作者

13 篇 wei li
13 篇 bin wu
9 篇 dacheng yang
9 篇 ming chen
9 篇 h. wang
9 篇 r. raheli
8 篇 xin liu
8 篇 jaeseok kim
8 篇 shixin cheng
8 篇 keiichi tamura
8 篇 v.k. garg
8 篇 j. mcnames
8 篇 xin zhang
7 篇 lei wang
7 篇 a. schaum
7 篇 hajime kitakami
7 篇 hui zhao
7 篇 giulio colavolpe
7 篇 hui li
7 篇 yong li

语言

7,323 篇 英文
39 篇 其他
36 篇 中文
4 篇 西班牙文
1 篇 土耳其文

检索条件"主题词=detection algorithms"

共 7403 条记录，以下是1241-1250 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：

Detecting and Exploring Malicious Websites through Multi-Message Passing Heterogeneous Neural Network

Detecting and Exploring Malicious Websites through Multi-Mes...

引用

IEEE Symposium on Computers and Communications (ISCC)

作者： Xiaoyu Fang Xiaoqing Ma Cong Wang Yan Niu Liya Ma Tianmu Gao Rong Yang Institute of Information Engineering Chinese Academy of Sciences Beijing China National Engineering Laboratory for Information Security Technologies Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Security Research Institute China Academy of Industrial Internet Beihang University

ISBN: (数字)9798350354232

ISBN: (纸本)9798350354249

Identifying and blocking malicious domains is one of the most direct and effective ways to combat malicious websites. In recent years, tools and technologies such as domain registration services, code repositories, and Domain-Flux have been exploited to generate malicious websites, enabling them to quickly "reincarnate" after being identified and shut down. Detecting methods for such malicious website domains are gradually shifting from the Belief Propagation (BP) algorithm to the Graph Neural Network (GNN) algorithm because the latter excels at aggregating neighboring node information to integrate node representations and graph embeddings. However, cloud services, Content Delivery Network (CDN), and Carrier-Grade Network Address Translation (CGNAT) often lead to benign-malicious co-location for domains, causing miscommunication in messages passing based on domain association relationships, thus reducing detection accuracy. To overcome this limitation, this paper proposes a malicious website domain detection algorithm based on one Multi-Message Passing Heterogeneous Neural Network (HMPN) framework. We apply this method to real-world network traffic scenarios and find that it achieves a Macro-Average F1 score of 91.70%, outperforming the baselines. We further conduct a measurement and analysis of the malicious websites’ industrial characteristics to better explore and detect malicious websites.

关键词： Computers Codes Content distribution networks Message passing Telecommunication traffic Feature extraction Graph neural networks IP networks detection algorithms Network address translation

来源：评论

学校读者我要写书评

暂无评论

A Fully Automated System for Localization and Classification of Foot Bones in X-Rays

A Fully Automated System for Localization and Classification...

引用

Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Maryam Mehdizadeh Janardhan Vignarajan Ashu Gupta Sajib Saha Australian e-Health Research Centre (AEHRC) Commonwealth Scientific and Industrial Research Organisation (CSIRO) Kensington WA Australia Fiona Stanley Hospital Murdoch WA Australia

ISBN: (数字)9798350379037

ISBN: (纸本)9798350379044

Foot x-rays serve as a crucial diagnostic tool for identifying medical conditions affecting the foot. Among the critical steps in foot x-ray analysis are the localization and classification of individual bones. However, this task is often laborious and time-intensive. In this paper, we present a fully automated system for simultaneous localization and classification of foot bones. The system relies upon YOLOv7 convolutional neural networks-based object detection framework, and cascades two independently trained YOLOv7 networks: Backfoot-YOLOv7 and Forefoot-YOLOv7. Backfoot-YoLOv7 specializes in localizing and classifying larger bones in the hindfoot and midfoot (we termed backfoot), whereas, Forefoot-YOLOv7 specializes in localizing and classifying smaller bones in the forefoot. Experiments were conducted on a dataset comprising of 188 x-ray images. The results revealed that in comparison to applying YOLOv7 directly on the whole image (baseline approach), the proposed multi-step approach ensures overall improved performance. We achieved an overall accuracy of 0.98, with precision of 0.80, recall of 0.86, F1-score of 0.98, and IoU of 0.90. For the baseline approach we obtained the results of overall accuracy of 0.83, precision of 0.76, recall of 0.81, F1-score of 0.80, and IoU of 0.86.

关键词： Location awareness Accuracy Medical conditions Digital images X-rays Object detection Network architecture Bones Convolutional neural networks detection algorithms

来源：评论

学校读者我要写书评

暂无评论

MSCMFusion: Multi-Stage Cross-Modal Fusion for Low-light Environments

MSCMFusion: Multi-Stage Cross-Modal Fusion for Low-light Env...

引用

International Conference on Signal Processing Proceedings (ICSP)

作者： Yuanchen Sun Shikui Wei Peng Sun Bo Li Qingwen Li Hong Li School of Computer Science & Technology Beijing Jiaotong University Beijing China NR Electric Co. Ltd. Nanjing China Information Technology Research Institute China Tower Beijing China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

Traditional visible light cameras often fall short in providing sufficient information under low-light environments, necessitating the use of thermal imaging to bolster model robustness. However, integrating images from diverse imaging mechanisms poses significant challenges. Existing visible-thermal detection algorithms typically rely on basic fusion techniques like concatenation, element-wise summation, and weighted summation. These methods fail to effectively capture the complementarity and disparity between different modal features, leading to reduced feature distinctiveness. To overcome this, we introduce the Multi-stage Fusion Network (MFNet), which strategically segments the fusion process into alignment and fusion phases for multispectral features. The network incorporates a Modality Consistency Loss (MCL) during the alignment phase to reduce disparities by calculating the Kullback-Leibler divergence between features across modalities. Additionally, we propose a Multi-granularity Cross-Attention (MCA) mechanism in the fusion phase, enhancing the integration of complementary information through spatial correlation across various granularities. Comparative evaluations with existing visible-thermal fusion methods using the FLIR-Aligned and LLVIP datasets demonstrate significant performance enhancements across multiple metrics. Visualization experiments further corroborate the superior detection capabilities of MFNet in diverse scenarios, underscoring its practical efficacy and innovation in image fusion technology.

关键词： Measurement Technological innovation Correlation Signal processing algorithms Lighting Signal processing Cameras Robustness detection algorithms Image fusion

来源：评论

学校读者我要写书评

暂无评论

Discovery of Evolving Relationships of Software Vulnerabilities

Discovery of Evolving Relationships of Software Vulnerabilit...

引用

IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)

作者： Hailey Sparks Krishnendu Ghosh Department of Computer Science College of Charleston South Carolina USA

ISBN: (数字)9798350386745

ISBN: (纸本)9798350386752

Discovering the risks posed by software vulnerabilities is a challenge. Software vulnerabilities are often not listed and studies have shown 50.3% of the reports do not include the list of vulnerable libraries. Thus, it becomes critical to maximize the understanding of the vulnerability reports and the trends in vulnerabilities. In this work, a novel tool is created that is able to connect the vulnerabilities with time and identify subsets of vulnerabilities that are *** the first step of the model, a text network is created from the vulnerability reports of each month in a year. Then, a temporal network is constructed from text networks. Temporal network theoretic properties are evaluated on the model to understand the vulnerability trends and the evolution of relationships amongst the vulnerabilities. The analysis leverages on the community detection algorithms on text networks. The dynamics of evolving relationships of the software vulnerabilities are extracted using biclustering algorithms, and the statistical significance of the biclusters is evaluated. Experimental results based on vulnerability reports are analyzed and presented.

关键词： Privacy Heuristic algorithms Software algorithms Market research Software Libraries Security Intelligent systems detection algorithms

来源：评论

学校读者我要写书评

暂无评论

UAV-YOLOv8n: An Improved YOLOv8 to Detect Small Target in UAV Remote Sensing Images

UAV-YOLOv8n: An Improved YOLOv8 to Detect Small Target in UA...

引用

System Simulation Technology and its Application (CCSSTA), IEEE China Conference on

作者： Yue Ma Sen Yang Jigang Tong Na Liu School of Electrical Engineering and Automation Tianjin University of Technology Tianjin

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

UAV target detection is widely used in commercial, civil and military fields. However, UAV aerial images have few small target pixels and a large number of small targets, so there are omissions and false detections in target detection. Based on the above problems, an advanced YOLOv8n aerial photography detection algorithm is proposed. First, the RepNCSPELAN4 module is introduced, which has the functions of enhanced region representation and multi-scale fusion, which can effectively improve the correctness and robustness of the detection algorithm. Second, the SimAM (Simple Parameter-free Attention Module) attention mechanism is added after the backbone module and the RepNCSPELAN4 module to focus on the target region and refine the feature information. In addition, the convolution modules in the first and third layers of the backbone layer are replaced with dynamic convolution, which has higher parameter efficiency and feature expression ability, and can effectively improve the small target detection ability. Experiments show that the mAP 50 of the proposed model is improved by $1.8 \%$ on the VisDrone2021 public dataset, respectively, and there is also a significant improvement on the SeaDronesSee dataset.

关键词： Convolution Heuristic algorithms Computational modeling Object detection Autonomous aerial vehicles Robustness Satellite images Systems simulation detection algorithms Remote sensing

来源：评论

学校读者我要写书评

暂无评论

Simulating Accelerometer Signals of Parkinson’s Gait Using Generative Adversarial Networks

Simulating Accelerometer Signals of Parkinson’s Gait Using ...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Aaron J. Hadley Christopher L. Pulliam Hadley Research LLC South Euclid OH USA Department of Biomedical Engineering Case Western Reserve University Cleveland OH USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Wearable technologies have been demonstrated to have value in the objective assessment of Parkinson's disease. However, certain symptoms such as freezing of gait are challenging to monitor using current approaches. Data augmentation, wherein synthetic or simulated data is added to real world training sets to increase their size and diversity, has emerged as an approach to bolster the accuracy of machine learning models in other healthcare domains such as medical imaging. In this paper, we evaluate the use of generative adversarial networks to create synthetic accelerometry data representing both typical and freezing gait patterns. Our preliminary results suggest that these synthetic datasets can mimic realistic movement patterns of individuals with Parkinson’s disease. In the future, we will assess the impact that integrating these synthetic data into training sets has on the accuracy of freezing of gait detection algorithms.

关键词： Training Accuracy Parkinson's disease Medical services Machine learning Generative adversarial networks Biomedical monitoring detection algorithms Monitoring Synthetic data

来源：评论

学校读者我要写书评

暂无评论

Surface Defect detection of Cable Based on Improved YOLO V3

Surface Defect Detection of Cable Based on Improved YOLO V3

引用

International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Yu Wen Jianuo Chen Linjie Dong Rongkai He Xingsong Wang Mengqian Tian School of Mechanical Engineering Southeast University Nanjing China

ISBN: (纸本)9798350334340

When using yolov3 identification technology to detect the defects on the cable surface of cable-stayed bridge, although it has also achieved good detection results, there is a problem that the detection speed of the network is slow, and the detection accuracy of cracking is much lower than that of other kinds of defects. To solve these problems, this paper improves the running speed and detection accuracy, merges the BN layer and convolution layer, and embeds the CBAM attention mechanism into the yolov3 network. The experimental results show that the average accuracy map of crack detection is increased to 82.3%, and the running speed is increased to 51.4 frames per second, which meets the requirements of precision and speed of cable surface defect detection.

关键词： Training Bridges Mechatronics Convolution Machine vision Surface cracks detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Verifiable Obstacle detection

Verifiable Obstacle Detection

引用

International Symposium on Software Reliability Engineering (ISSRE)

作者： Ayoosh Bansal Hunmin Kim Simon Yu Bo Li Naira Hovakimyan Marco Caccamo Lui Sha University of Illinois Urbana-Champaign Mercer University Technical University of Munich

ISBN: (数字)9781665451321

ISBN: (纸本)9781665451338

Perception of obstacles remains a critical safety concern for autonomous vehicles. Real-world collisions have shown that the autonomy faults leading to fatal collisions originate from obstacle existence detection. Open source autonomous driving implementations show a perception pipeline with complex interdependent Deep Neural Networks. These networks are not fully verifiable, making them unsuitable for safety-critical tasks. In this work, we present a safety verification of an existing LiDAR based classical obstacle detection algorithm. We establish strict bounds on the capabilities of this obstacle detection algorithm. Given safety standards, such bounds allow for determining LiDAR sensor properties that would reliably satisfy the standards. Such analysis has as yet been unattainable for neural network based perception systems. We provide a rigorous analysis of the obstacle detection system with empirical results based on real-world sensor data.

关键词： Laser radar Neural networks Software algorithms Pipelines Safety Software reliability detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Heart Murmur Classification for Diagnostic Applications

Heart Murmur Classification for Diagnostic Applications

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Ashley FitzGerald Taikang Ning Department of Engineering Trinity College Hartford CT USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

This paper presents an innovative methodology for applying signal processing techniques and machine learning to process recently available data for heart murmur detection and classification. The scope of this research is to improve upon current heart murmur detection research by investigating the classification of murmur characteristics, such as pitch, duration, configuration, and quality, which are necessary for diagnosis. Feature extraction was performed on each cardiac cycle for a total of 53 features. The machine learning models tested included 5 supervised models, with 3 of those being boosting models, and 13 voting classifier combinations. The efficiency of the feature extraction methodology and the machine learning algorithms was evaluated with a confusion matrix. The murmur detection algorithm achieved an F-score of 0.87.

关键词： Heart Machine learning algorithms Signal processing Feature extraction Boosting Engineering in medicine and biology detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Pedestrian detection Algorithm Based on YOLOv3

Pedestrian Detection Algorithm Based on YOLOv3

引用

International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)

作者： Xueli Gong Mingliang Xie Haosen Xu College of Control Science and Engineering Bohai University Jinzhou China College of Photonic and Electronic Engineering Fujian Normal University Fuzhou China Changchun Normal University Changchun China

The current YOLOv3 algorithm also has shortcomings in dealing with pedestrian detection problems, such as pedestrian missed detection, false detection, and pedestrian multi-pose change problems. Therefore, an improved algorithm based on the YOLOv3 algorithm for accurate pedestrian detection in images was proposed. The algorithm introduces the CSPNet structure and the ECA attention mechanism to the original YOLOv3 algorithm, which greatly reduces the amount of computation compared with the original algorithm, and the performance is significantly improved. The experiment in this paper is based on the INRIA dataset,and the experimental results show that the detection performance of the optimized algorithm is *** with the original YOLOv3 network, the optimized algorithm improves the mAP value by 93.89%.

关键词： Redundancy Prediction algorithms Manufacturing Complexity theory Convolutional neural networks detection algorithms 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500页 << < 121 122 123 124 125 126 127 128 129 130 > >>

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：