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

6,718 篇 会议
329 册 图书
119 篇 期刊文献

馆藏范围

7,165 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

4,791 篇 工学
- 3,970 篇 计算机科学与技术...
- 2,033 篇 软件工程
- 808 篇 电气工程
- 771 篇 信息与通信工程
- 592 篇 控制科学与工程
- 395 篇 生物工程
- 381 篇 生物医学工程（可授...
- 297 篇 光学工程
- 296 篇 机械工程
- 213 篇 仪器科学与技术
- 182 篇 电子科学与技术（可...
- 138 篇 化学工程与技术
- 128 篇 材料科学与工程（可...
- 120 篇 网络空间安全
- 108 篇 安全科学与工程
- 91 篇 动力工程及工程热...
1,629 篇 理学
- 809 篇 数学
- 494 篇 物理学
- 490 篇 生物学
- 273 篇 统计学（可授理学、...
- 190 篇 化学
- 141 篇 系统科学
844 篇 管理学
- 463 篇 管理科学与工程(可...
- 425 篇 图书情报与档案管...
- 181 篇 工商管理
679 篇 医学
- 604 篇 临床医学
- 254 篇 基础医学(可授医学...
- 145 篇 药学(可授医学、理...
- 100 篇 公共卫生与预防医...
122 篇 法学
- 115 篇 社会学
92 篇 教育学
58 篇 农学
52 篇 经济学
43 篇 艺术学
12 篇 文学
4 篇 军事学
1 篇 哲学

主题

927 篇 pattern recognit...
800 篇 artificial intel...
447 篇 machine learning
291 篇 feature extracti...
243 篇 deep learning
203 篇 accuracy
185 篇 support vector m...
134 篇 data mining
128 篇 training
126 篇 neural networks
126 篇 face recognition
103 篇 local binary pat...
103 篇 computer imaging...
102 篇 computer vision
88 篇 image processing...
87 篇 real-time system...
87 篇 convolutional ne...
85 篇 information syst...
83 篇 pattern matching
83 篇 computational mo...

机构

39 篇 chitkara univers...
33 篇 maharishi school...
27 篇 school of comput...
27 篇 indian stat inst...
25 篇 centre of interd...
25 篇 the islamic univ...
23 篇 department of ar...
23 篇 concordia univ c...
22 篇 national univers...
20 篇 school of comput...
19 篇 univ chinese aca...
18 篇 school of comput...
18 篇 univ waterloo de...
17 篇 vishwakarma inst...
16 篇 national laborat...
15 篇 school of artifi...
15 篇 institute of aut...
14 篇 lovely professio...
14 篇 uttaranchal inst...
14 篇 college of pharm...

作者

54 篇 suen ching y.
24 篇 suen cy
22 篇 kamel mohamed s.
18 篇 lu bao-liang
18 篇 karray fakhri
17 篇 de-shuang huang
17 篇 abraham ajith
14 篇 maji pradipta
13 篇 dash yajnaseni
12 篇 c.y. suen
10 篇 liu cheng-lin
10 篇 venkatesh svetha
10 篇 wong alexander
10 篇 chauhan rahul
10 篇 natarajan s.
10 篇 zheng wei-long
10 篇 liu wei
10 篇 vinay a.
9 篇 zhang lei
9 篇 gill kanwarparta...

语言

6,735 篇 英文
403 篇 其他
65 篇 中文
1 篇 土耳其文

检索条件"任意字段=3rd International Conference on Pattern Recognition and Machine Intelligence"

共 7166 条记录，以下是831-840 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：

A Hazelnut Tree Search Algorithm for Enhancing Large-Scale Electric Vehicle Charging on the Power Grid 3

A Hazelnut Tree Search Algorithm for Enhancing Large-Scale E...

引用

3rd international conference on Automation, Computing and Renewable Systems, ICACRS 2024

作者： Kavithamani, K. Priya, G. Adline Saranya, S. Anupriya, K. Ramkumar, M. Siva Kaliappan, S. Department of Electrical and Electronics Engineering Karpagam College of Engineering Tamilnadu Coimbatore641032 India Department of Information and Technology Sri Krishna College of Technology Tamilnadu Coimbatore641042 India Department of Artificial Intelligence and Machine learning Hindusthan College of Engineering and Technology Tamilnadu Coimbatore641050 India Dept of ECE SNS College of Technology India

ISBN: (纸本)9798331532420

Electric vehicle (EV) adoption on a large scale would drastically change patterns of electricity demand, posing both opportunities and challenges for modern power systems. However, the increased and often unpredictable demand from simultaneous EV charging can strain grid infrastructure, leading to potential overloads and instability. This paper proposes the Hazelnut Tree Search Algorithm (HTSA) as an effective optimization method for large-scale EV charging. The objective of the proposed method is to minimize electricity costs and improve grid efficiency in the EV charging. By optimizing charging schedules, HTSA enhances grid stability and improves load balancing throughout the power grid (PG). By then, the proposed method is implemented in MATLAB platform and compared to other existing methods such as Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and NSGA-II. Results show that HTSA reduces electricity costs to 4.3 INR/kWh, and achieves 96% of higher efficiency compared to other existing methods. This superior performance demonstrates HTSA’s potential for optimizing EV charging strategies while minimizing grid disruptions and enhancing the integration of renewable energy sources (RES). © 2024 IEEE.

关键词： Power grids

来源：评论

学校读者我要写书评

暂无评论

An Effective Clustering Using Moth Flame Optimization for Content-Based Image Retrieval 3

An Effective Clustering Using Moth Flame Optimization for Co...

引用

3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Aluvala, Srinivas Abed Almoussawi, Zainab Almusawi, Muntather Latef Naser, Zamen Meenakshi Sundaram, S. School of Computer Science & Artificial Intelligence SR University Telangana Warangal India College of Islamic Science Ahl Al Bayt University Karbala Iraq The Islamic University Najaf Iraq National University of Science and Technology Dhi Qar Iraq Nitte Meenakshi Institute of Technology Department of AI and DS Bengaluru India

ISBN: (纸本)9798350317022

Content-based image retrieval plays an important role in many domains and the volume of the image database increasing tremendously. It is very complex to comparing the query image feature with all images in the dataset during the retrieval phase. Due to computational complexity increase which degrades the performance of recognition accuracy. The proposed model Clustering using Moth Flame Optimizer are pre-processing, feature extraction, feature fusion, clustering and classification. The corel lk dataset is utilized in this research for effective classification of CBIR method. Filter using First Average Peer Group (F APG) is used to remove the noise in the pre-processing stage. Feature extracted using Local Binary pattern (LBP) and Hue Saturation Value (HSV) based feature extraction techniques. All these two features are fused into single feature using average and weighted technique. Next, proposed model clustering using Moth Flame Optimization algorithm, it enhance the flames and flame value is obtained in ***, the relevant image is retrieved using SAR classifier which utilized Deep Learning (DL) for effective classification. The obtained result shows the proposed clustering using MFO model achieve better accuracy of 99.87% on Corel lk dataset which insure accurate classification compared to other existing methods like Bi-Iayer method and Texture from semantic pyramid. © 2023 IEEE.

关键词： clustering Content based image retrieval Deep Learning Deep Neural Network Moth Flame Optimization

来源：评论

学校读者我要写书评

暂无评论

AUV Path Planning and Image recognition Based on Convolutional Neural Network 3

AUV Path Planning and Image Recognition Based on Convolution...

引用

3rd international conference on Big Data, Artificial intelligence and Internet of Things Engineering, ICBAIE 2022

作者： Zhang, Yuhan Ge, Weili Zhengzhou University School of Computer and Artificial Intelligence Zhengzhou China

ISBN: (数字)9781665451604

ISBN: (纸本)9781665451604

Autonomous Underwater Vehicle (AUV) has been widely used in marine resources development and underwater engineering operations. Vision is one of the most important environmental testing technologies at present, and Convolutional Neural Networks are widely used in target testing. Based on LENET-5, a Convolutional Neural Network (CNN) for underwater training set was proposed, and image recognition was implemented through Raspberry PI. AUV controls the camera and underwater lighting through Raspberry Pi, and builds a model based on the TensorFlow framework. The tested dataset showed that the accuracy of the 7-layer Convolutional Neural Network is only 80%. So,in this paper, the Convolutional Neural Network was improved to finally design a 13-layer neural network, including 1 input layer, 4 convolutional layers, 4 pooling layers, 3 fully connected layers, and 1 output layer. After 100 iteration training experiments, the accuracy of underwater target recognition reached 99.18%, and the independent underwater robot underwater target recognition was achieved. © 2022 IEEE.

关键词： Autonomous underwater vehicles

来源：评论

学校读者我要写书评

暂无评论

Research on Digital Twin Technology of Port Structure Safety based on Floating 3D Display 3

Research on Digital Twin Technology of Port Structure Safety...

引用

3rd IEEE international conference on Information Technology, Big Data and Artificial intelligence, ICIBA 2023

作者： Li, Zilong Wang, Peiren Han, Xue Shang, Dongfang Tianjin Research Institute for Water Transport Engineering M.O.T. Tianjin China

ISBN: (纸本)9781665490788

Because of the port's intricate structure and underwater concealment, structure health monitoring is a crucial tool for ensuring the safe and steady functioning of the facility. This work proposes the visualization improvement approach of multi-source data fusion and builds a digital twin model of the port structure and auxiliary monitoring system based on the virtual-real mapping port digital twin modeling theory. This paper also implements the innovation of the digital twin display carrier, proposes the floating stereoscopic display technology for the naked eye and the multi-source interaction technology based on gesture recognition, develops the floating stereoscopic display equipment, and realizes the visual display and natural interaction of the digital twin for the safety monitoring of port structure, which is a new exploration for the safety maintenance of port structure. © 2023 IEEE.

关键词： Port structures

来源：评论

学校读者我要写书评

暂无评论

A Complete Framework for Shop Signboards Detection and Classification 26

A Complete Framework for Shop Signboards Detection and Class...

引用

26th international conference on pattern recognition / 8th international Workshop on Image Mining - Theory and Applications (IMTA)

作者： Almuhajri, Mrouj Suen, Ching Y. Concordia Univ Ctr Pattern Recognit & Machine Intelligence Montreal PQ H3G 2W1 Canada Saudi Elect Univ Dept Comp Sci Riyadh Saudi Arabia

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Many factors can influence the process of detecting and classifying stores based on their visual appearance. Previous studies built models that considered the whole storefront however, the detection and classification results were negatively impacted because of the lack of consistency in storefront design. This research focuses on store signboards as they are much more consistent. A complete framework is provided in which it enables existing real-time object detectors to integrate with another model connected to an OCR and then classify shops using NLP techniques. The models were trained and evaluated utilizing the ShoS dataset which was collected from Google Street Views for different research purposes. A total of 10k storefront signboards were captured and fully annotated. The outcomes of different baseline methodology and applications on the ShoS dataset are provided to measure the performance of our work.

关键词： Support vector machines Visualization Annotations Optical character recognition Detectors Real-time systems Internet

来源：评论

学校读者我要写书评

暂无评论

Research on target attitude estimation method based on image 3

Research on target attitude estimation method based on image

引用

3rd IEEE international conference on Information Technology, Big Data and Artificial intelligence, ICIBA 2023

作者： Zhao, Tengfei Zhang, Rui Cao, Jianxin ShaanXi Institute of International Trade&Commerc College of Information Engineering ShanXi China Lvliang Vocational Technical Institute College of Big Data ShanXi China

ISBN: (纸本)9781665490788

Aiming at the real time and accuracy of door handle pose estimation, this paper improved ORB matching algorithm and combined with least square plane fitting algorithm. In order to improve the real-time performance of the system to obtain the location information of the door handle, the ORB matching algorithm was used to reduce the time complexity of the algorithm itself and the polar constraint algorithm was added to reduce the search dimension to straight line search to reduce the matching time and reduce the mismatching. Finally, the least square plane fitting algorithm is used to obtain the spatial attitude information of the door handle under the camera plane. The accuracy and real-time performance of the improved ORB matching algorithm and the accuracy of the door handle pose are verified by experiments. The proposed method can meet the requirements in practical application. © 2023 IEEE.

关键词： Door handles

来源：评论

学校读者我要写书评

暂无评论

Anti-pattern Based IoRT-Aware Business Process Structure Verification Approach 3rd

Anti-pattern Based IoRT-Aware Business Process Structure Ver...

引用

3rd international conference on Language Processing and Knowledge Management-LPKM

作者： Fattouch, Najla Ben Lahmar, Imen Boukadi, Khouloud Sfax Univ MIRACL Lab FSEG Sfax Sfax Tunisia Sfax Univ ReDCAD Lab ISIM Sfax Sfax Tunisia

ISBN: (纸本)9783031850660;9783031850677

The IoRT-aware Business Process is a new business type. It embedded IoT and robot technologies to automate classic BP. To effectively execute an IoRT-aware BP, it is significant to ensure that is accurately modeled. Referring to the literature, various modeling languages can be used to model an IoRT-aware BP. The Business Process Model and Notation (BPMN) is among the most attractive and descriptive languages. However, the latter lacks a formal aspect, potentially leading to inconsistencies and ambiguities. Therefore, to effectively check an IoRT-aware BP modeled using BPMN, it seems relevant to cope with a consistent formalism (e.g., Petri Net (PN), Discrete Event System Specification (DEVS), etc.), simplifying the process structure verification. From this perspective, we propose an approach that deals with DEVS formalism to check IoRT-aware BP structure (e.g., deadlock, loop, dead task, etc.). To evaluate the proposed approach, we consider a case study of IoRT-aware BP in agriculture by checking its process model structure. The findings show the effectiveness of our approach in capturing structure errors.

关键词： Structure Verification Anti-pattern DEVS IoRT-aware BP

来源：评论

学校读者我要写书评

暂无评论

Data Mining of Garment pattern Based on Decision Tree Algorithm 3rd

Data Mining of Garment Pattern Based on Decision Tree Algori...

引用

3rd EAI international conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2023

作者： Li, Jing Li, Chen Shandong Vocational College of Light Industry Shandong Zibo255300 China

ISBN: (纸本)9783031631320

With the development of economy, society and culture, the traditional tailor-made clothing has been unable to meet people’s needs for personalization, fit and online customization of clothing. The clothing industry has gradually changed from the original large-scale and standardized production to flexible and personalized customization. Data mining is the process of extracting useful information from data. Data mining is a process of discovering patterns in a large amount of data by applying statistical and computational techniques to data. Decision tree algorithm is such a technology that helps to find patterns in a large amount of data. It uses decision tree to find the best method to classify objects according to their attributes or characteristics. In recent years, the application of advanced technologies, such as computer graphics, digital image processing and artificial intelligence, has brought new opportunities to the garment industry, promoted the mode update of the garment industry, and also promoted the digitalization and intelligence of garment design. Garment digital version is the key problem and research hotspot of garment digital technology. In this paper, the research and analysis of data mining of garment pattern based on decision tree algorithm. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Image enhancement-based quick response code recognition in complex working conditions 3

Image enhancement-based quick response code recognition in c...

引用

3rd international conference on Electronic Information Engineering, Big Data, and Computer Technology, EIBDCT 2024

作者： Liu, Shang Xie, Cheng Zhong, Guoqiang Wang, Chao Ping, Xianyao Wang, Zhenya Chu, Zhihao Science and Technology Research and Development Center Shandong Provincial Communications Planning and Design Institute Group Co.Ltd Shandong Jinan250101 China School of Computer Science and Artificial Intelligence Wuhan University of Technology Hubei Wuhan430070 China Enterprise Management Department Shandong Dongfang Highway and Bridge Construction Co. Ltd Shandong Jinan250000 China Security Management Department Shandong Dongfang Highway and Bridge Construction Co. Ltd Shandong Jinan250000 China

ISBN: (纸本)9781510680449

In the industrial field, Quick Response code has been widely used in the automatic management of production lines because of its high-density storage and fast reading characteristics. However, in real-world scenarios, the recognition success rate of Quick Response code often falls short of the desired outcome due to interference from factors such as lighting, noise, and scale variations. To solve this problem, this paper proposes an Image Enhancement-based Quick Response Code recognition in complex working conditions (IE-QRCR). Firstly, the Quick Response code image is preprocessed through the joint optimization method of perspective transformation and low-light enhancement to improve image quality and reduce interference. Then, the optimized Quick Response code image is input into the recognition algorithm for recognition. The method can effectively improve the accuracy and robustness of recognition, especially in complex environments with low illumination and poor image quality. We verify the effectiveness of the method on some public Quick Response code datasets, which provides a useful reference for further research in the field of Quick Response code recognition. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

New Invariant Meixner Moments for Non-uniformly Scaled Images 2nd

New Invariant Meixner Moments for Non-uniformly Scaled Image...

引用

3rd international conference on Digital Technologies and Applications

作者： Yamni, Mohamed Daoui, Achraf Karmouni, Hicham Sayyouri, Mhamed Qjidaa, Hassan Jamil, Mohammed Ouazzani Sidi Mohamed Ben Abdellah Fez Univ Dhar El Mahrez Fac Sci Lab Elect Signals & Syst Informat LESSI STICCED ST Fes Morocco Sidi Mohamed Ben Abdellah Univ Engn Syst & Applicat Lab Natl Sch Appl Sci BP 72My Abdallah Ave Km 5Imouzzer Rd Fes Morocco Cadi Ayyad Univ Natl Sch Appl Sci Marrakech Morocco Private Univ Fez UPF Syst & Sustainable Environm Lab SED Fac Engn Sci FSI Fes Morocco

ISBN: (纸本)9783031298561;9783031298578

Invariants of discrete orthogonal moments have been applied in several research fields of image processing and pattern recognition due to their ability of representing digital images. Generally, moment invariants are invariant only for image translation, rotation and uniform scaling. These moments are not invariant when an image is scaled non-uniformly in the x- and y-axes directions. In this paper, we propose a new set of discrete orthogonal moments namely Meixner moments, which are invariant when an image is scaled uniformly/non-uniformly. The proposed invariants are completely independent of scale factors unlike some existing invariant moments in the literature. The experimental results show the efficiency of the proposed descriptors.

关键词： Non-uniform scaling Discrete orthogonal moments Meixner moments pattern recognition

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 << < 80 81 82 83 84 85 86 87 88 89 > >>

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：