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651-660 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：

Lightweight Driver and Window detection Algorithm Based on Improved YOLOv5s

Lightweight Driver and Window Detection Algorithm Based on I...

引用

IEEE International Conference on Industrial Informatics (INDIN)

作者： Yuan Liu ZeXin Xu ChunQi Gao Yong Wang Shandong Academy of Sciences Institute of Automation Qilu University of Technology JiNan China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Aiming at the high complexity of the real-time driver detection model for highway autonomous card acceptance robots, which is difficult to be deployed on limited resource devices, this paper proposes a lightweight driver and window detection algorithm based on YOLOv5s. The algorithm combines the C3P and GS modules of PConv and GhostNet, introduces a parameter-free attention mechanism, extracts multi-scale features from the network, focuses on the target information, and the GS module performs feature fusion with DWConv to replace the feature fusion part in the original YOLOv5s network, and introduces a non-parametric attention mechanism of the PfAAMLayer in the Detect part, improving the ability to generalise *** finally the FGS-pf-YOLOv5s network is constructed by using SIoU (Scale-Invariant Objective for Union) loss to better deal with the occlusion and overlapping problems between targets, which reduces the number of network parameters and the GFLOPs while maintaining the model recognition accuracy, and reduces the number of GFLOPs in the network. number and GFLOPs, reducing the size of the model. The experimental results show that the parameters of the PGS-pf-YOLOv5s model proposed in this paper are reduced by 68%, the GFLOPs are reduced by 51 %, and the size of the weight file is only 4.7 4M, which is reduced by 67% compared with the source code, but the Map50 is improved by 0.2% compared with the source code on the basis of lightweighting, This shows that the model in this paper can solve the model deployment problem while achieving real-time target detection and maintain the same high accuracy.

关键词： YOLO Accuracy Attention mechanisms Target recognition Source coding Feature extraction Real-time systems Robustness detection algorithms Vehicles

来源：评论

学校读者我要写书评

暂无评论

A Joint detection System for Radio Frequency Interference in Spaceborne Microwave Radiometers

A Joint Detection System for Radio Frequency Interference in...

引用

Artificial Intelligence, Networking and Information Technology (AINIT), International Seminar on

作者： Huiyuan Li Chuan Bai Shijie Rong Jiakai He Lifei Jiang Passive Remote Sensing Department Shanghai Aerospace Electronic Technology Institute Shanghai China Active Remote Sensing Department Shanghai Aerospace Electronic Technology Institute Shanghai China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

Microwave radiometer is a highly sensitive receiver for detecting the emitted and scattered energy of objects, but the radio frequency interference (RFI) caused by the use of radio equipment seriously affects the measurement accuracy of the microwave radiometers. In the view of the increasingly serious RFI of microwave radiometers, the joint RFI detection algorithm system has been proposed for spaceborne microwave radiometers. The frequency domain is subdivided in the mode of digital channelized, then the time domain detection and the statistical domain detection are combined in each sub band to identify and suppress interference signals. The time-domain detection algorithm is optimized to determine the specific position and duty cycle of the interference signals, and then, the kurtosis algorithm is used to determine the interference signal so that it can eliminate the bottom noise fluctuations caused by external environmental factors. Finally, a high-resolution fast detection method is achieved and the system simulation performance is provided. The algorithm implementation complexity is low, it is easy to reuse and also suitable for the engineering implementation of RFI detection in satellite microwave radiometers.

关键词： Microwave measurement Interference Microwave devices Kurtosis Systems simulation Microwave radiometry detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Cross Language Similarity detection Technology Combining Optimized K-Means Algorithm with CL-ESA

Cross Language Similarity Detection Technology Combining Opt...

引用

Artificial Intelligence Technology (ACAIT), Asian Conference on

作者： Yuxin Gan Qian Xu Foreign Language Department Chengdu College of Arts and Sciences Chengdu China

ISBN: (数字)9798331517090

ISBN: (纸本)9798331517106

Academic plagiarism is becoming an increasingly serious cross language problem, and the academic community is paying more and more attention to cross language text similarity detection algorithms. In order to improve the accuracy of cross linguistic text similarity detection algorithms, the study first combines word level precise translation and sentence level contextual understanding, and combines machine translation algorithms based on word granularity text with those based on sentence granularity text to design an improved machine translation algorithm. At the same time, a heuristic retrieval mechanism is introduced on the basis of CL-ESA to narrow down the search scope of cross linguistic text similarity detection, and an improved index document selection algorithm (IIDSA) is proposed in combination with the K-Means algorithm. Finally, a cross lingual text similarity detection model is constructed by combining the IIDSA algorithm with an improved machine translation algorithm. This study extracted 500 pairs of concept aligned Chinese and English texts from Wikipedia as experimental texts to test the algorithm. The results show that the accuracy of the model is 96.2%, which is superior to other models. The above conclusions verify that the proposed cross language similarity detection model can meet people's needs for cross language text similarity detection and to some extent promote the development of academic research.

关键词： Accuracy Translation Text recognition Plagiarism Heuristic algorithms Clustering algorithms Linguistics Internet Machine translation detection algorithms

来源：评论

学校读者我要写书评

暂无评论

A multi-objective genetic algorithm based on neighborhood coevolution for community detection

A multi-objective genetic algorithm based on neighborhood co...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Mingyuan Bi Junliang Shang Xiaotong Kong Feng Li Yuanyuan Zhang Jin-Xing Liu School of Computer Science Qufu Normal University Rizhao China School of Information and Control Engineering Qingdao University of Technology Qingdao China School of Health and Life Sciences University of Health and Rehabilitation Sciences Qingdao China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Community detection has attracted growing interest, with multi-objective evolutionary algorithms proving to be highly competitive in this area. In this paper, a community detection method based on a multi-objective neighborhood coevolution genetic algorithm, NCMOGA, is proposed. To improve the computational efficiency in large-scale networks, NCMOGA introduces a network processing strategy to simplify the network before and during evolution. A neighborhood coevolution strategy is proposed, in which the corresponding subpopulation is formed according to the neighborhood of each individual. A series of operations such as crossover, mutation and update are performed in the subpopulation, emphasizing the synergy between individuals and their neighbors. Mating selection and crossover operations are performed based on the center selection idea of density peak clustering, and the most important nodes are selected to generate offspring. The effectiveness of NCMOGA is verified on synthetic networks and real-world networks. In addition, the results in guiding the classification of disease and healthy samples demonstrate the high quality of the modules detected by NCMOGA.

关键词： Evolutionary computation Computational efficiency detection algorithms Bioinformatics Genetic algorithms Diseases

来源：评论

学校读者我要写书评

暂无评论

Human detection Based on Learning and Classification of Radio Scattering Parameters and Para-Hermitian Eigenvalue Decomposition

Human Detection Based on Learning and Classification of Radi...

引用

IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Frank E. Ebong Nicola Novello Andrea M. Tonello Institute of Networked and Embedded Systems University of Klagenfurt Klagenfurt Austria

ISBN: (数字)9798350362244

ISBN: (纸本)9798350362251

In this article, we introduce a novel machine learning algorithm termed the S-parameters-based Human detection Algorithm (S-PBHD). Designed to operate on radio frequency datasets transformed into an S-parameter multi-port channel matrix, our algorithm aims to detect human targets within indoor environments using distributed antennas. Central to the efficacy of this algorithm lies its preprocessing phase, which entails the extraction of critical components from the scattered radio field. This is achieved through the Para-Hermitian Eigenvalue Decomposition method, which effectively disentangles the complexities inherent in the S-parameter multi-port channel matrix.

关键词： Machine learning algorithms Eigenvalues and eigenfunctions Scattering parameters Sensors Indoor environment Complexity theory Classification algorithms Matrix decomposition detection algorithms Land mobile radio

来源：评论

学校读者我要写书评

暂无评论

An Improved Fire detection Algorithm Based on YOLOv5

An Improved Fire Detection Algorithm Based on YOLOv5

引用

International Conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Zhenjie Wu Xiang Wang Gang Wang Chengzhe Jiang Beihua University Jilin China Jilin Institute of Chemical Technology Jilin China

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

Early warning of fire is crucial for improving survival rates during fire incidents. Fire and smoke detection is an extremely important safety technology that plays a vital role in timely and accurately detecting fires in the surrounding environment to ensure the safety of lives and production environments. To address the challenge of detecting fires in complex scenarios, we propose a YOLO-based algorithm, utilizing YOLOv5 as its foundation, which offers high detection accuracy while remaining lightweight. Our algorithm incorporates the C2f-ODConv module into the network, allowing for dynamic adjustment of the convolution kernel's shape and size based on the input data's features during the convolution process. This adaptability ensures better compatibility with different input data types. Additionally, we introduce the Decoupled head in the detection head section, replacing the original detection head. This modification reduces interference between the classification head and the detection head of the model, thereby enhancing the overall detection accuracy of the model. Experimental results demonstrate that our proposed algorithm achieves a detection accuracy of 94.7% and a recall rate of 93.2%. These impressive results ensure accurate Decoupled head fire detection even in complex situations.

关键词： YOLO Adaptation models Accuracy Convolution Heuristic algorithms Interference Feature extraction Safety Kernel detection algorithms

来源：评论

学校读者我要写书评

暂无评论

IAT-YOLO: A black pig detection model for use in low-light environments

IAT-YOLO: A black pig detection model for use in low-light e...

引用

Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

作者： Mengzhen Huang Lao Li Huanjun Hu Yifan Liu Yuting Yao Rui Song School of Mathematics and Computer Science Wuhan Polytechnic University Wuhan China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

In the large-scale intelligent pig farming industry, it is crucial to achieve real-time and accurate identification and positioning of each pig. However, the existing mainstream pig detection algorithms are mainly designed for white pigs, and the detection effect of black pigs is poor in low-light environments. In addition, when black pigs gather and adhesion and occlusion occur, the complexity of detection is further increased. Although strong light irradiation in the pigpen can improve the detection accuracy, it will have an adverse effect on the normal growth of pigs. To ensure accurate detection of black pigs in low-light environments without interfering with the normal growth of pigs, this research presents the IAT-YOLO model, derived from YOLOv7. It combines the brightness adaptive module IAT (Illumination-Adaptive-Transformer), the CA (Coordinate Attention mechanism) and the improved SPPCSPC-R module, which can effectively identify and locate the position and number of black pigs. Tests on the low-light black pig dataset reveal that the proposed model attains 96.8% accuracy, 83.8% recall, 91.8% mAP@0.5, and 54.5% mAP@0.5:0.95, which demonstrates higher accuracy and provides technical support for the intelligent detection of black pigs in such environments.

关键词： Smart agriculture Adaptation models Radiation effects Accuracy Computational modeling Object detection Robustness Real-time systems detection algorithms Farming

来源：评论

学校读者我要写书评

暂无评论

System Architecture Design for Spoofing detection Based on Baseband Information

System Architecture Design for Spoofing Detection Based on B...

引用

World Congress on Computing and Communication Technologies (WCCCT)

作者： Zhen Peng Ao Peng Jianghong Shi School of Information Science and Engineering Xiamen University Xiamen China

ISBN: (数字)9798331512620

ISBN: (纸本)9798331512637

This paper evaluates the performance of two anti-spoofing algorithms, studies the performance boundary of anti-spoofing technology under multiple parameters, verifies its reliability and effectiveness in the face of multiple spoofing attack ways, and provides a judgment basis for scheme selection. Moreover, combining the complementarity of advantages of different spoofing detection technologies, the detection probability in joint detection scenarios is calculated, it provides effective support for various spoofing scenarios. This paper then proposes an anti-spoofing system architecture based on baseband information. The architecture utilizes multi-dimensional and multi-feature signal analysis, and combines various spoofing parameters using specific group strategies, so as to obtain a more comprehensive reference for detection effects.

关键词： Global navigation satellite system Baseband Systems architecture Computer architecture Prediction algorithms Probability distribution Reliability Signal analysis detection algorithms Faces

来源：评论

学校读者我要写书评

暂无评论

A lightweight small-object detection algorithm for remote sensing images based on 4SDC-YOLOv8

A lightweight small-object detection algorithm for remote se...

引用

Computer Applications and Information Technology (ISCAIT), International Symposium on

作者： Hanqing Ding Lichao Mo Shengfa Yue Jiaxue Li School of Electronics and Information Zhengzhou University of Light Industry Zhengzhou China School of Computer Science and Technology Zhengzhou University of Light Industry Zhengzhou China

ISBN: (数字)9798331542856

ISBN: (纸本)9798331542863

In the field of object detection, remote sensing image detection has become a critical research focus. However, existing small-object detection algorithms for remote sensing images often fail to strike an effective balance between detection accuracy and computational complexity, thereby limiting their application on mobile devices. To address this issue, this paper proposes a lightweight small-object detection algorithm for remote sensing images, named 4SDC-YOLOv8, built upon YOLOv8. Firstly, we incorporate the SimSPPF spatial pyramid pooling structure, using pooling kernels of different sizes across multiple scales to improve the detector’s performance. Secondly, we design a lightweight neck network that leverages the dynamic upsampling operator DySample and the partial convolution Partial Conv to introduce the new CSPPC architecture, reducing redundant computations and enhancing both real-time performance and model compactness. Finally, we add a dedicated small-object detection layer, enabling the feature map to capture rich semantic and spatial information, with four detection heads supporting multi-scale small-object detection and improving detection capability for small targets. Experimental results on the DIOR dataset show that, compared with YOLOv8, 4SDC-YOLOv8 significantly reduces model size and computational load by 24.6% and 24%, respectively, achieves an accuracy of up to 90%, and maintains a respectable real-time performance at 145 FPS. Confirm that 4SDC-YOLOv8 effectively balances detection accuracy and computational complexity, thereby offering a promising reference for implementing small-object remote sensing detection on mobile devices.

关键词： Performance evaluation YOLO Accuracy Computational modeling Semantics Real-time systems Mobile handsets detection algorithms Computational complexity Remote sensing

来源：评论

学校读者我要写书评

暂无评论

Hash-Prune-Invert: Improved Differentially Private Heavy-Hitter detection in the Two-Server Model

Hash-Prune-Invert: Improved Differentially Private Heavy-Hit...

引用

IEEE Symposium on Security and Privacy

作者： Borja Balle James Bell-Clark Albert Cheu Adria Gascon Jonathan Katz Mariana Raykova Phillipp Schoppmann Thomas Steinke Google DeepMind Google Research Google

ISBN: (数字)9798331522360

ISBN: (纸本)9798331522377

Differentially private (DP) heavy-hitter detection is an important primitive for data analysis. Given a threshold $t$ and a dataset of $n$ items from a domain of size $d$ , such detection algorithms ignore items occurring fewer than $t$ times while identifying items occurring more than $t+\Delta$ times; we call $\Delta$ the error margin. In the central model where a curator holds the entire dataset, $(\varepsilon, \delta)$ -DP algorithms can achieve error margin $\Theta\left(\fracalgorithms{\varepsilon} \log \fracalgorithms{\delta}\right)$ , which is optimal when $d\gg 1/\delta$ . Several works, e.g., Poplar (S&P 2021), have proposed protocols in which two or more non-colluding servers jointly compute the heavy hitters from inputs held by $n$ clients. Unfortunately, existing protocols suffer from an undesirable dependence on Iog $d$ in terms of both server efficiency (computation, communication, and round complexity) and accuracy (i.e., error margin), making them unsuitable for large domains (e.g., when items are kB-long strings, log $d\approx 10^{4}$ ). We present hash-prune-invert (HPI), a technique for compiling any heavy-hitter protocol with the log $d$ dependencies mentioned above into a new protocol with improvements across the board: computation, communication, and round complexity depend (roughly) on log $n$ rather than log $d$ , and the error margin is independent of $d$ . Our transformation preserves privacy against an active adversary corrupting at most one of the servers and any number of clients. We apply HPI to an improved version of Poplar, also introduced in this work, that improves Poplar's error margin by roughly a factor of $\sqrt{n}$ (regardless of $d)$ . Our experiments confirm that the resulting protocol improves efficiency and accuracy for large $d$ .

关键词： Privacy Protocols Accuracy Data analysis Computational modeling Computational efficiency Complexity theory Servers Security detection algorithms

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 << < 62 63 64 65 66 67 68 69 70 71 > >>

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：