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791-800 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：

Demo - Unmasking the Unseen: CryptojackingTrap, the Most Resilient Evasion-Proof Cryptojacking Malware detection Algorithm

Demo - Unmasking the Unseen: CryptojackingTrap, the Most Res...

引用

IEEE International Workshop on Information Forensics and Security (WIFS)

作者： Atefeh Zareh Chahoki Hamid Reza Shahriari Marco Roveri Inf. Eng. and Computer Science Dept. University of Trento Trento Italy Computer Engineering Dept. Amirkabir University of Technology Tehran Iran

ISBN: (数字)9798350364422

ISBN: (纸本)9798350364439

This demonstration presents CryptojackingTrap, an advanced cryptojacking malware detection solution that stands out among similar works due to its superior evasion resilience. The demonstration covers the architecture, design, and implementation of CryptojackingTrap, highlighting its effectiveness in detecting cryptojacking attempts, even in scenarios where attackers employ evasion techniques to reduce the hash rate by up to tenfold. The evaluation includes rigorous experimental testing against both miner and non-miner executables. This demonstration provides cybersecurity specialists with a deep understanding of the algorithm, showcasing its robustness and potential for extension, and offering insights into benchmarking detection solutions using publicly available datasets and opensource codebases.

关键词： Instruments Forensics Conferences Benchmark testing Malware Robustness detection algorithms Computer security Resilience

来源：评论

学校读者我要写书评

暂无评论

Research on Helicopter Obstacle detection Algorithm Based on Object Recognition

Research on Helicopter Obstacle Detection Algorithm Based on...

引用

IEEE International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Jiang Li Mingze Ma Xiankuan Zhang Leilei Shi Unit 61255 of the People's Liberation Army Houma China

ISBN: (数字)9798350377033

ISBN: (纸本)9798350377040

In this paper, a new 2D-Single Machine (2D-SM) algorithm is proposed, which is applied to helicopter obstacle detection based on target recognition to judge whether there are obstacles in the shutdown environment. The algorithm combines SSD (Single Shot MultiBox Detector) target detection algorithm, Support Vector Machine (SVM) classification algorithm and Dijkstra path search algorithm. SSD is used for multi-scale target detection, which can efficiently detect targets in the environment, generate accurate candidate boxes, and quickly identify obstacles in the shutdown environment. SVM classifies the detected obstacles to improve the accuracy of recognition. Dijkstra's algorithm is used to optimize path planning to ensure that the helicopter can land efficiently and safely while there are no obstacles in the shutdown environment. Finally, compared with the traditional detection algorithm, the results show that the 2D-SM algorithm can quickly identify obstacles in complex environments, provide a safe shutdown environment judgment for the helicopter, and ensure the safety of the helicopter during takeoff and landing. The algorithm has the characteristics of high efficiency and accuracy, and provides a new solution for helicopter obstacle detection.

关键词： Support vector machines Accuracy Target recognition Helicopters Object detection Detectors Path planning Classification algorithms Safety detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Research and Application of Efficient detection Algorithm for Harmful Substances in Food

Research and Application of Efficient Detection Algorithm fo...

引用

Power, Electrical Engineering, Electronics and Control (PEEEC), International Conference on

作者： Hongyan Liu Yanchun Ruan Wei Wang Xinglin Zeng Ruichen Bu College of Cuisine Science and Technology Jiangsu Vocational College of Tourism Yangzhou Jiangsu China

ISBN: (数字)9798350378917

ISBN: (纸本)9798350378924

With food safety becoming the focus of global attention, rapid and accurate detection of harmful substances in food has become the key to protect public health. In this study, the efficient detection algorithm of harmful substances in food is deeply studied, aiming at developing a hybrid model combining advanced machine learning technology and big data analysis to realize rapid and accurate identification of harmful substances in food. By constructing a hybrid model (CNN-LSTM) based on Convolutional Neural Network (CNN) and Long Short Term Memory Network (LSTM), this study fully utilizes the complementary information in food image and spectral data to improve detection accuracy and efficiency. The experimental results show that the proposed CNN-LSTM hybrid model shows excellent performance in the detection of harmful substances in food, with high accuracy and strong generalization ability, and can be applied to various types of food samples and harmful substances. This study not only provides an efficient and convenient detection method for food safety supervision, but also provides a new idea and method for the research of harmful substances detection algorithm in food.

关键词： Electrical engineering Deep learning Accuracy Food safety Data models Convolutional neural networks Labeling detection algorithms Public healthcare Long short term memory

来源：评论

学校读者我要写书评

暂无评论

A Particle Swarm Optimization Algorithm Based on Multi-Population Mutual Learning for SNP-SNP Interaction detection

A Particle Swarm Optimization Algorithm Based on Multi-Popul...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Linqian Zhao Yahan Li Junliang Shang Qianqian Ren 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 Science University of Health and Rehabilitation Sciences Qingdao China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Single nucleotide polymorphism (SNPs) data have become abundant thanks to the quick advancement of high-throughput sequencing technology, which provides convenience for genome-wide association studies. Single SNPs have been proven to be the cause of some diseases, and the emergence of complex diseases is often thought to be the result of the interaction of multiple SNPs. However, the possible interaction of millions of SNPs imposes a heavy computational burden for uncovering complex disease mechanisms. The existing SNP-SNP interaction detection algorithms frequently have flaws including high computation complexity and poor optimization effectiveness. In this study, a particle swarm optimization algorithm based on multi-population mutual learning (PSOMPML) is proposed to detect SNP-SNP interactions. In this algorithm, the mutual learning strategy is introduced to deal with different particles in different sub-populations to facilitate knowledge exchange. In addition, the elite preservation mechanism is incorporated into PSOMPML, to better preserve the good SNPs in the elite particles. The promising region local search strategy searches the optimal solution along the target solution and its near space to increase the convergence speed of the proposed algorithm. Experiments on simulated data sets and real data also demonstrate the effectiveness of the proposed algorithm.

关键词： Sequential analysis Genomics Search problems Particle swarm optimization Bioinformatics detection algorithms Computational complexity Optimization Diseases Convergence

来源：评论

学校读者我要写书评

暂无评论

FTN detection Algorithm Based on Iterative Residual ISI Estimation and Correction

FTN Detection Algorithm Based on Iterative Residual ISI Esti...

引用

International Conference on Electronic Engineering and Informatics (EEI)

作者： Zhiwen Li Qiang Chen Hui Xie School of Electronic and Information Engineering Chongqing Three Gorges University Chongqing China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

To address the severe Inter-Symbol Interference (lSI) problem introduced in faster-than-Nyquist (FTN) communication systems, a soft-information sequence detection algorithm based on iterative residual lSI estimation and correction is proposed. The algorithm first performs matched filtering and downsampling on the received signal, then obtains bit soft-information using soft demodulation, and utilizes channel decoding to acquire the initial decoding result. On this basis, the algorithm estimates the residual lSI component by re-mapping the initial decoded symbols and subtracting them from the received signal. The estimated lSI is then superimposed onto the mapped symbols as the input for the next iteration, achieving gradual lSI elimination and sequence detection performance improvement through multiple iterations. Simulation results show that the proposed algorithm can achieve bit error rate performance close to Nyquist orthogonal transmission under different signal-to-noise ratios and compression factors, and can effectively converge after 3–4 iterations. Compared with existing FTN sequence detection algorithms, this algorithm greatly reduces computational complexity while ensuring detection performance.

关键词： Communication systems Simulation Bit error rate Symbols Estimation Interference Iterative algorithms detection algorithms Computational complexity Iterative decoding

来源：评论

学校读者我要写书评

暂无评论

A Speed detection Method for BLDC Motor

A Speed Detection Method for BLDC Motor

引用

Information Technology and Data Science (CITDS), IEEE Conference on

作者： Fehmi Sevilmis Ali Sait Özer Hulusi Karaca Dept. of Electrical and Electronics Engineering Selçuk University Konya Türkiye Dept. of Control and Automation Technology Konya Technical University Konya Turkiye

ISBN: (数字)9798350387889

ISBN: (纸本)9798350387896

It is very important to accurately determine the position and speed of BLDC motor. The use of an encoder to precisely control the motor is a suitable solution, but the placement of the encoder on the motor shaft causes the volume of the system to increase. In addition, the high cost of the encoder is another disadvantage. To overcome these problems, sensorless control algorithms can be used for position and speed detection. However, the complex structure of sensorless control methods and their inadequate performance at low speeds cause them not to be preferred in practical applications. For these reasons, hall-effect sensor control algorithms come to the forefront due to their simple structure and low cost. Since the resolution of hall sensor signals is low, these signals must be processed properly in speed detection. For this purpose, MAF-PLL-based speed detection method is proposed in this study. The proposed method is tested under different conditions. The results obtained show the accuracy of the proposed speed detection algorithm.

关键词： Shafts Costs Rotors Estimation Sensorless control Data science Motors detection algorithms Information technology Signal resolution

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based DDoS Attack detection Using Adversarial Optimization

Deep Learning-Based DDoS Attack Detection Using Adversarial ...

引用

IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Dahai Yu Jianming Cui Yungang Jia Peiguo Fu Ming Liu School of Information Engineering Chang’an University Xi’an China National Computer Network Emergency Response Technical Team Coordination Center of China Beijing China

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

In the field of cybersecurity, increasingly emerging network threats seriously affect the security of network and users. Notably, DDoS attacks represent a critical concern due to their capacity to inundate and debilitate targeted systems via distributed networks. This study introduces a DDoS attack detection framework employing a dual-detection model designed to identify both conventional and adversarial DDoS attacks. Adversarial DDoS attacks are characterized by their enhanced capability to circumvent standard DDoS detection mechanisms. The proposed framework incorporates an optimized CNN architecture for the detection of traditional DDoS attacks. This optimization involves substituting fully connected layers with global average pooling layers, an approach validated through comparative experimentation to yield the most effective base CNN model. For the detection of adversarial DDoS attacks, we propose a new detection algorithm, in which methodology initially employs the WGAN-GP data generation process to create synthetic DDoS attack data, followed by the strategic alteration of certain feature values within the generated attack data using normal traffic data. The resultant perturbed data are then utilized to train the adversarial DDoS attack detection model. Empirical assessments performed on the CIC-IDS2017 and CIC-DDoS2019 datasets confirm the efficacy of the dual-detection model in accurately identifying both traditional and adversarial DDoS attacks, achieving an accuracy exceeding 95%.

关键词： Accuracy Denial-of-service attack Generative adversarial networks Feature extraction Real-time systems Data models Convolutional neural networks Computer crime detection algorithms Optimization

来源：评论

学校读者我要写书评

暂无评论

Coherent Integration detection of Maneuvering Targets Using Non-Uniformly Resampling Trilinear Autocorrelation Function and KT

Coherent Integration Detection of Maneuvering Targets Using ...

引用

International Conference on Signal Processing Proceedings (ICSP)

作者： Liang Qiao Hongmeng Chen Ming Li Lei Zuo National Key Laboratory of Radar Signal Processing Xidian University Xi’an China Beijing Institute of Radio Measurement Beijing China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

The presence of range migration (RM) and Doppler migration (DM) leads to the degradation of performance in coherent integration detection of maneuvering targets. This article proposed a coherent integration detection method for third-order maneuvering targets based on the non-uniformly resam-pling trilinear autocorrelation function (NRTAF) and keystone transform (KT). Firstly, The NRTAF is introduced to address DM, as well as second-order and third-order RM, while first-order RM is eliminated using KT. Subsequently, the energy of signal is accumulated through fast Fourier transform (FFT) and inverse fast Fourier transform (IFFT). The proposed algorithm completely avoids searching for motion parameters, resulting in lower computational complexity. It can effectively suppress cross terms, making it suitable for multi-objective scenarios. Additionally, it is appropriate for high-speed target scenarios. The effectiveness of the algorithm has been confirmed through simulation and measured data.

关键词： Resistance Parameter estimation Fast Fourier transforms Noise Signal processing algorithms Transforms Doppler effect Autocorrelation Computational complexity detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Multi-Class Abnormal Behavior detection Algorithm Based on YOLOv9

Multi-Class Abnormal Behavior Detection Algorithm Based on Y...

引用

Algorithm, Image Processing and Machine Vision (AIPMV), International Conference on

作者： Baixuan Han Yueping Peng Hexiang Hao Wenchao Kang Xuekai Zhang School of Information Engineering Engineering University of PAP Xi'an China

ISBN: (数字)9798350390254

ISBN: (纸本)9798350390261

Aiming at the shortage of accuracy and feature extraction ability of aerial image behavior detection algorithm, we designed an improved YOLOv9 multi-class abnormal behavior detection algorithm. Use drones to take aerial photos and build abnormal behavior data sets; The dimensional awareness selective integration module DASI was used to improve the detection accuracy of the model and the feature extraction ability of the self- built data set. A new general inverted bottleneck module is added at the end of the model trunk to improve the model inference efficiency. The results show that compared with the original network, the detection accuracy is increased from 90.9% to 92.6%, and the model reasoning speed is reduced from 266.2GFLOPS to 258.0GFLOPS, which improves the computing efficiency of the model and meets the requirement of high precision detection.

关键词： Accuracy Computational modeling Machine vision Feature extraction Data models Cognition detection algorithms Drones

来源：评论

学校读者我要写书评

暂无评论

The Enhanced MPPT Using Slope detection Algorithm for PV System Under Partial Shading and Low Irradiation Conditions

The Enhanced MPPT Using Slope Detection Algorithm for PV Sys...

引用

International Conference on Business and Industrial Research (ICBIR)

作者： Jirada Gosumbonggot Department of Electrical Engineering Faculty of Engineering Thai-Nichi Institute of Technology Bangkok Thailand

ISBN: (数字)9798350383027

ISBN: (纸本)9798350383034

Photovoltaic (PV) technology, being a prominent renewable energy source primarily due to its environmentally friendly operation and versatile installation options. To improve the efficiency of photovoltaic (PV) systems, it is essential to take into account the impact of weather conditions. Irradiation and temperature are two primary parameters influencing PV-generated power, both of which vary depending on the location where the PV system is installed. Consequently, the issue of irradiation mismatch may arise, posing challenges for the PV system in achieving its maximum potential power generation. This paper presents the maximum power point tracking (MPPT) algorithm that can operates under partial shading and low irradiation conditions. The algorithm operates with a concept of searching the highest mountain's peak point. Case studies using the irradiation dataset from the Department of Alternative Energy Development and Efficiency are input to evaluate the performance of the proposed method under different weather conditions. Graphical and numerical results show the effectiveness of the algorithm, with the searching time under 1.36 seconds and the accuracy at 99.55%.

关键词： Maximum power point trackers Photovoltaic systems Radiation effects Renewable energy sources Temperature dependence Accuracy Estimation Robustness detection algorithms Meteorology

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 << < 76 77 78 79 80 81 82 83 84 85 > >>

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：