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1021-1030 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：

Resisting Visual Hacking: A Novel Graphical Password Authentication System 3

Resisting Visual Hacking: A Novel Graphical Password Authent...

引用

3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Jebakumar Immanuel, D. Ramalingam, V. Tharun Kumar, P. Iyer, Akash Narayanan, M.S. Karpagam Institute of Technology Department of Artificial Intelligence and Data Science Coimbatore641 105 India Sns College of Engineering Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350322842

Password-based authentication is a widely used method to ensure security and privacy in computer applications. However, the selection of weak passwords and insecure input methods by users is considered the 'weakest link' in the authentication process. Instead of employing arbitrary alphanumeric sequences, individuals tend to opt for passphrases that are either mnemonic or abbreviated in nature. With the proliferation of web and mobile applications, users can access these applications at any time and from anywhere with various devices. Although this convenience is highly desirable, it also increases the likelihood of passwords being exposed to Visual Hacking. The forms of attack may be executed through either direct visual observation or the utilization of external recording devices in order to obtain the user's login information. In response to this issue, our team has devised an authentication system that centers on graphical passwords and is made to combat the threat of Visual Hacking. The system incorporates a three-layered security mechanism, comprising color and pattern matching functionalities in conjunction with password verification. This makes it highly challenging for potential attackers to deduce or limit the password even amidst numerous camera-based hacking attempts. Additionally, we have created and put to the test a prototype of the system to assess its user-friendliness. Our experimental results indicate that our system can resist Visual Hacking more effectively than previous authentication systems while still maintaining a high degree of usability and security. © 2023 IEEE.

关键词： pattern matching

来源：评论

学校读者我要写书评

暂无评论

A Forecasting Model for the Energy Requirements of an Office Building Based on Energy Modeling and machine Learning Models - A Case Study of Morocco 1

引用

3rd international conference on Digital Technologies and Applications

作者： Boumais, Khaoula Messaoudi, Faycal Sidi Mohamed Ben Abdellah Univ Natl Sch Appl Sci Lab Artificial Intelligence & Data Sci & Emerging Fes Morocco

ISBN: (数字)9783031298608

ISBN: (纸本)9783031298592;9783031298608

In Morocco, where buildings consume more than 35% of the country's energy, the decision to integrate energy efficiency practices into the building from the design phase can avoid any energy waste. In this study, we examine the impact of integrating insulation on the energy efficiency of an office building using two approaches, with a focus on predicting the energy demand of an office building in Casablanca. The first method uses the Trnsys software for dynamic thermal modeling and the result is 37.45 kWh/m(2).year on total energy demand modeling over one year, which has allowed us to meet the requirements of the Moroccan Thermal Regulation for Buildings (RTCM). The second approach is based on the use of two machine learning models, and the results show that the SVM is more efficient than the RF model. It achieved a coefficient of determination of 97%.

关键词： Office building energy demand dynamic thermal simulation machine learning Moroccan Thermal Regulation for Buildings (RTCM)

来源：评论

学校读者我要写书评

暂无评论

3rd international conference on Communication, Computing and Electronics Systems, ICCCES 2021

3rd International Conference on Communication, Computing and...

引用

3rd international conference on Communication, Computing and Electronics Systems, ICCCES 2021

ISBN: (纸本)9789811688614

The proceedings contain 75 papers. The special focus in this conference is on Communication, Computing and Electronics Systems. The topics include: Energy-Efficient Hybrid Secured Routing for 5G Vehicular Ad Hoc Network (VANET);a Study on Recent Advances in Artificial intelligence and Future Prospects of Attaining Superintelligence;development of Automated Protection and Monitoring System for Poor Railway Infrastructure;a System Design Perspective for Measurement of Parameters Using Different Scatterings Associated with Fibre Optic Sensors;Utilization of machine Learning Techniques for Prediction of COVID-19 Epidemic;internet of Things: Security Mechanisms;Performance Analysis of Video Transmission Over OWC-PON in Weak Turbulence Regimes;fish Species Detection Using Deep Learning for Industrial Applications;remaining Useful Life Prediction Using machine Learning Algorithms;dietary Assessment and Nutritional Analysis Using Deep Learning;binary and Multiclass Classifications Using a Deep Fusion Network;Image Processing-Based Switching Matrix for PV Array Under Partial Shading Conditions;an Enhanced Approach to Predict Re-occurrences of Breast Cancer Using machine Learning;A Review on IOT Response to COVID-19 Pandemic, Challenges and Open Issues;Food Assessment Model for Indian Elderly Persons Using CNN and Image Processing Techniques;changes in Commodity Circulation Channels Based on international Trade E-commerce Platform from Computing and Electronics System Perspectives;key Technologies of English Document Grammar recognition System with Cloud Computing and Electronics Systems;machine Learning-Based Approach for Depression Detection Using PHQ-9 and Twitter Dataset;systematic Review on Churn Prediction Systems in Telecommunications;generating Recommendations for Various Problems Using Data Mining and machine Learning Algorithms;music Emotion recognition Using Neural Networks;preface.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Predicting Life Expectancy using machine Learning Approach through Linear Regression and Decision Tree Classification Techniques 3

Predicting Life Expectancy using Machine Learning Approach t...

引用

3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Gill, Kanwarpartap Singh Anand, Vatsala Chauhan, Rahul Sharma, Manish Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Computer Science & Engineering Uttarakhand Dehradun24800 India

ISBN: (纸本)9798350319125

Predicting someone's longevity requires looking at a broad variety of circumstances, making it a difficult and multidimensional task. There are a number of important factors that must be taken into account from a substantive perspective in order to provide an accurate prediction of life expectancy. Life expectancy is not a constant that can be calculated from a person's genes or other unchangeable characteristics. Instead, it is affected by a complex interplay of biological, psychological, and social elements, any of which may play a greater or lesser role depending on the context. For instance, lifestyle variables like smoking, alcohol use, and exercise levels, as well as access to healthcare, nutrition, and clean water, may all have a substantial influence on life expectancy. It is difficult to estimate a person's lifespan without considering a broad variety of characteristics, such as their socioeconomic status, access to healthcare, and way of life. Life expectancy prediction is a regression issue rather than a classification problem, however both linear regression and decision tree classification are useful machine learning approaches for making predictions. In this study, we apply a machine learning strategy to the problem of life expectancy prediction utilising linear regression and decision tree classification methods. According to the findings, the Decision Tree Classifier obtained 92% accuracy while the Linear Regression Classifier reached 96% accuracy. © 2023 IEEE.

关键词： Artificial intelligence Classification Deep Learning Deep Learning Image Processing Life Expectancy Prediction Model Training Random Forest

来源：评论

学校读者我要写书评

暂无评论

Identification of Fingerprint Orientation Using Improved Generative Adversarial Network with Support Vector machine 3

Identification of Fingerprint Orientation Using Improved Gen...

引用

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

作者： Hameed Abdul Hussein, Abbas Ravindran, Gobinath Latef Naser, Zamen Almusawi, Muntather Santhiya, K. College of Pharmacy Ahl Al Bayt University Karbala Iraq SR University Department of Civil Engineering Telangana Warangal India National University of Science and Technology Dhi Qar Iraq The Islamic University Najaf Iraq PSG Institute of Technology and Applied Research Department of Artificial Intelligence and Data Science Coimbatore India

ISBN: (纸本)9798350317022

Fingerprint authentication is one of the methods used to prevent the loss of personal data, but the minutiae and angle variance of finger patterns make the process difficult. To overcome the issue, an authentication system for fingerprint orientation using an improved Generative Adversarial Network (GAN) with Support Vector machine (SVM) is being developed. The process begins with image enhancement using Contrastive Limited Adaptive Histogram Equalization (CLAHE) techniques to increase image contrast. Next, GAN with SVM is employed to generate synthetic data through data augmentation, and decision-making is carried out using SVM. Both real and synthetic samples are binarized using the global thresholding technique, and edge-based thinning methods are applied to enhance the fingerprint patterns. Finally, features such as minutiae points of fingerprints are extracted using the Scale Invariant Feature Transform (SIFT) algorithm, serving as input for the SVM classifier. The implemented GAN-SVM model demonstrates superior performance, achieving a False Acceptance Rate (FAR) of 0.12%, a False Rejection Rate (FRR) of 1.3%, an Equal Error Rate (EER) of 0.29%, and an accuracy of 95.87%. When compared to previous models like Multi-layer Perceptron Neural Network (MLP), Fuzzy Commitment (FC), and Genetic Encryption Algorithm (GEA). © 2023 IEEE.

关键词： Contrastive Limited Adaptive Histogram Equalization Generative Adversarial Network Global Thresholding Scale Invariant Feature Transform Support Vector machine

来源：评论

学校读者我要写书评

暂无评论

Enhancing Breast Cancer Screening: Mammogram Image Analysis with Multiclass Support Vector machine 3

Enhancing Breast Cancer Screening: Mammogram Image Analysis ...

引用

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

作者： Velumani, J. Issa, Ali Ashoor Kumar, Gotte Ranjith Hussein, A.H.A. Shakir, Aboothar Mahmood Paavai Engineering College Department of Cybersecurity Namakkal India National University of Science and Technology Dhi Qar Iraq School of Computer Science & Artificial Intelligence SR University Telangana Warangal India College of Pharmacy Ahl Al Bayt University Karbala Iraq The Islamic University Najaf Iraq

ISBN: (纸本)9798350317022

Mammography is an essential screening test for the early detection of breast cancer, significantly increasing the patient's chances of complete recovery. In this paper, a Multi-Class Support Vector machines (MSVM) is presented to address the overfitting problem and enhance the technique's performance in detecting locations and areas of breast cancer. This approach proves to be particularly effective in high-dimensional spaces, offering advantages in the context of breast cancer detection, where datasets may contain a large number of features. The MIAS dataset in the classification stage utilizing 60 breast cancer images including 100 malignant and 100 benign breast cancer images. All these images have been labeled with 63 images labeled as normal and 37 images as benign or micro, with an original pixel size of 1024×1024. After segmentation using Particle Swarm Optimizer (PSO) to segment nuclei and non-nuclei cells and involved parallel computing and global optimization to achieve superior results for the Super pixel. Feature extraction was performed using the Grey Level Co-Occurrence Matrix (GLCM). Finally, the (MSVM) classifier was utilized to grade the histology breast images. The experimental results demonstrate that the MSVM achieved an accuracy rate of 98.90% surpassing other existing models such as Convolutional Neural Network, Deep Neural Network, and Support Vector machine. © 2023 IEEE.

关键词： Grey Level Co-Occurrence Matrix Mammogram Image Multiclass Support Vector machine Super pixel Segmentation

来源：评论

学校读者我要写书评

暂无评论

Quality of AI Service Assurance in 6G Native Artificial intelligence Networks 3rd

Quality of AI Service Assurance in 6G Native Artificial Inte...

引用

3rd international conference on machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Hua, Meihui Chen, Tianjiao Liu, Guangyi Deng, Juan Li, Na Wang, Xiaoyun China Mobile Research Institute Beijing China ZGC Institute of Ubiquitous-X Innovation and Applications Beijing China China Mobile Communications Group Corporation Beijing China

ISBN: (纸本)9789819624676

6G native artificial intelligence (AI) networks are expected to support diverse vertical industries and offer countless emerging AI services. To satisfy stringent requirements of diversified services, network slicing is developed, which enables service-oriented resource allocation tailored for different AI scenarios. However, the mismatch between the user’s quality of AI service (QoAIS) requirements and the actual capacity of network slices, as well as the hierarchical network architecture, pose great challenges to the guarantee of QoAIS. This paper introduces AI-assisted slicing management framework to maintain a high performance of network operation by supporting diverse AI services and meeting QoAIS. A novel methodology and resource allocation scheme based on federated learning and transfer learning is proposed, which enables efficient life-cycle management of AI services and selection of network slices. Simulation results illustrate that the proposed scheme has superior performance in ensuring QoAIS compared with benchmarks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Learning additional latent representations using variational autoencoders 3

Learning additional latent representations using variational...

引用

3rd international conference on Signal Processing and machine Learning, CONF-SPML 2023

作者： Shen, Chong School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430070 China

A noticeable trend of machine learning is to deal with data of various modalities. Besides multimodal motivation, learning more from general information without forgetting the prior, or incremental learning, could also benefit unimodal machine learning. Human understanding often starts from a simplistic, generic view of the whole problem and then fills in the details and nuances. Incremental learning could enable imitation of such a learning process to learn more and potentially faster. This paper examines the possibility of learning additional latent variables from known latent variables for variational autoencoders. A method is proposed to facilitate learning additional information based on a modified β-TCVAE loss function that incorporates known general mutual information. A qualitative comparison is conducted on the dSprites dataset to evaluate the effect of this modification and the change of network structures on the learned latent, which hints at the structural tendency for β-TCVAE to learn new information from explicit known latent. © Published under licence by IOP Publishing Ltd.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

Transforming Work: The Impact of Artificial intelligence (AI) on Modern Workplace 3

Transforming Work: The Impact of Artificial Intelligence (AI...

引用

3rd international conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Anurag Vyas, Narayan Kumar Lilhore, Umesh Chandigarh University Department of Cse Punjab Mohali India

ISBN: (纸本)9798350342338

The impact of AI on the workplace is wide-ranging and significant. While AI can increase productivity and create new job opportunities, it also raises concerns about the displacement of human labor and the potential for unintentional bias and discrimination. The development of new skills, the assurance of transparency and accountability in the decision-making processes, and the development of rules to ensure that all facets of society share the benefits of AI are all necessary to address these issues. Modern workplace applications of Artificial intelligence (AI) have ushered in a disruptive era that has revolutionized business practices and altered the nature of employment. This research looks at the multifaceted impact of AI on the modern workplace, as well as the promise and issues. Robotics, machine learning, and other AI-related technologies have improved quickly, enabling organizations to automate repetitive jobs, speed up workflows, and augment human capacity. Consequently, organizations have seen enhanced efficiency, production, and cost savings. Customer service has improved thanks to AI-powered chatbots and virtual assistants, while predictive analytics has enhanced decision-making by extracting insights from enormous amounts of data. © 2023 IEEE.

关键词： Artificial intelligence (AI) Enhancement Marketplace Modern Workplace Revolution Workplace

来源：评论

学校读者我要写书评

暂无评论

Human phone usage recognition based on OpenPose 3

Human phone usage recognition based on OpenPose

引用

3rd international conference on Computer Vision, Image and Deep Learning and international conference on Computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Li, Yuyan Luo, Jiawen Wen, Jinghao Zhang, Yangjia Case Western Reserve University Weatherhead School of Management ClevelandOH44106 United States Beijing Institute of Technology Zhuhai College of Global Talents Zhuhai China Central China Normal University School of Computer Wuhan China Jianghan University School of Artificial Intelligence Wuhan China

ISBN: (纸本)9781665459112

With the development of science and technology, more and more people use mobile phones outdoors, which will cause danger to pedestrians using mobile phones and drivers on the road. This paper uses OpenPose method to detect whether pedestrians on the road are using mobile phones. We describe an approach to recognize and classify pedestrian posture in an individual context, more precisely in open door environment. The posture belongs into two main groups: phone usage and not. This paper uses 15 points OpenPose model to estimate human key points. Then select and calculate features using the estimated coordinates. Four neural network models are trained and tested using different feature combinations to classify the posture. The best model achieves 89.66% accuracy in classification. © 2022 IEEE.

关键词： Computer vision

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 << < 99 100 101 102 103 104 105 106 107 108 > >>

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：