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

22,150 篇 会议
3,542 篇 期刊文献
209 册 图书

馆藏范围

25,901 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

15,856 篇 工学
- 11,170 篇 计算机科学与技术...
- 9,359 篇 软件工程
- 4,303 篇 信息与通信工程
- 2,516 篇 控制科学与工程
- 2,157 篇 电子科学与技术（可...
- 2,132 篇 电气工程
- 1,540 篇 生物工程
- 1,323 篇 生物医学工程（可授...
- 1,142 篇 光学工程
- 1,028 篇 机械工程
- 882 篇 仪器科学与技术
- 834 篇 动力工程及工程热...
- 744 篇 化学工程与技术
- 626 篇 安全科学与工程
- 525 篇 交通运输工程
- 469 篇 材料科学与工程（可...
- 446 篇 建筑学
8,234 篇 理学
- 4,525 篇 数学
- 2,421 篇 物理学
- 1,707 篇 生物学
- 1,385 篇 统计学（可授理学、...
- 917 篇 系统科学
- 759 篇 化学
4,001 篇 管理学
- 2,399 篇 管理科学与工程(可...
- 1,836 篇 图书情报与档案管...
- 1,259 篇 工商管理
1,077 篇 医学
- 952 篇 临床医学
- 887 篇 基础医学(可授医学...
- 574 篇 药学(可授医学、理...
714 篇 法学
- 562 篇 社会学
444 篇 经济学
348 篇 教育学
320 篇 农学
110 篇 文学
72 篇 军事学
26 篇 艺术学
4 篇 哲学
3 篇 历史学

主题

723 篇 accuracy
540 篇 feature extracti...
501 篇 deep learning
491 篇 computational mo...
386 篇 training
383 篇 support vector m...
365 篇 computer science
323 篇 internet of thin...
299 篇 real-time system...
288 篇 machine learning
282 篇 computer archite...
247 篇 predictive model...
227 篇 reliability
222 篇 routing
221 篇 convolutional ne...
220 篇 optimization
209 篇 data mining
207 篇 neural networks
200 篇 throughput
195 篇 image segmentati...

机构

85 篇 dept. of compute...
84 篇 institut univers...
84 篇 université de st...
83 篇 north-west unive...
83 篇 tno technical sc...
82 篇 infn sezione di ...
81 篇 national centre ...
80 篇 nikhef national ...
76 篇 infn sezione di ...
67 篇 university würzb...
66 篇 università di ca...
53 篇 leiden universit...
51 篇 dept. of compute...
50 篇 school of automa...
50 篇 university of jo...
48 篇 university moham...
44 篇 university moham...
43 篇 in2p3 lpc campus...
42 篇 infn lnf via enr...
42 篇 university of gr...

作者

95 篇 ardid m.
93 篇 ferrara g.
92 篇 kalekin o.
92 篇 díaz a.f.
91 篇 boumaaza j.
90 篇 coleiro a.
89 篇 calvo d.
83 篇 gal t.
82 篇 bozza c.
80 篇 chen a.
78 篇 gozzini s.r.
76 篇 huang f.
75 篇 dallier r.
72 篇 anguita m.
61 篇 enzenhöfer a.
60 篇 kulikovskiy v.
60 篇 boettcher m.
58 篇 celli s.
53 篇 aly z.
52 篇 dornic d.

语言

23,073 篇 英文
2,461 篇 其他
272 篇 中文
75 篇 日文
21 篇 朝鲜文
4 篇 斯洛文尼亚文
1 篇 阿拉伯文
1 篇 德文
1 篇 法文
1 篇 土耳其文

检索条件"机构=Dept. Computer Technology and Computer Graphics"

共 25901 条记录，以下是611-620 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：

Covid-19 crowd detection and alert system using image processing

Covid-19 crowd detection and alert system using image proces...

引用

2023 International Conference on Advances in Intelligent Computing and Applications, AICAPS 2023

作者： Lodha, Nitin Singh Gahlaut, Harshvardhan Vellore Institute of Technology Dept. of Computer Science and Engineering Vellore India

ISBN: (纸本)9798350333817

In this paper, we aim to help in identifying the people that are violating social distancing norms set by the government (necessary during the COVID-19 pandemic in public places), by providing an efficient real-time deep learning-based framework to automate the process of monitoring the social distancing via object detection and tracking approaches. Our system is divided into two subsystems: one that deals with crowd detection and control, and the other that sends information to the police authorities. Our system technologies, including as IoT, image processing, web cams, BLE, OpenCV, and Cloud, are being considered for inclusion in the proposed framework. The image processing is divided into two sections, the first of which is the extraction of frames from real-time movies, and the second of which is the processing of the frame to determine the number of individuals in the crowd. Even in a crowd, dissemination may be restricted if people adhere to social distancing standards. As a result, the image processing model primarily targets the number of people who do not adhere to social distancing norms and stand too close together. © 2023 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Women's Rights in India 3

Women's Rights in India

引用

3rd International Conference on Advanced Computing Technologies and Applications, ICACTA 2023

作者： Alvares, Andrea Varghese, Leona Jesus, Tiffany Shaikh, Sana Don Bosco Institute of Technology Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9798350348347

Violence against women and discrimination based on gender are still major problems in the world. It is critical to have access to legal resources in order to address these issues. This requirement is met by the Women's Rights Portal, a web-based portal that offers a thorough database of laws and prior rulings concerning women's rights. The platform also has a built-in chatbot system that makes use of natural language processing to offer users who need information or legal advice individualised support. The portal also employs machine learning algorithms to provide pertinent case searches in response to user inquiries. By giving women the legal knowledge and assistance needed to claim their rights and fight gender-based discrimination, the Women's Rights Portal is a special and cutting-edge instrument that empowers women. Through this portal, women can access information about their rights and the legal resources available to them, empowering them to make informed decisions about their lives. The Portal is not only a valuable resource for women, but also for legal professionals, activists, and policymakers who seek to address gender-based discrimination. © 2023 IEEE.

关键词： Portals

来源：评论

学校读者我要写书评

暂无评论

Multimodal biometric authentication using Fully Homomorphic Encryption 2

Multimodal biometric authentication using Fully Homomorphic ...

引用

2nd International Conference on Paradigm Shifts in Communications Embedded Systems, Machine Learning and Signal Processing, PCEMS 2023

作者： Vallabhadas, Dilip Kumar Sandhya, Mulagala Sarkar, Soumyadip Chandra, Y Rupesh National Institute of Technology Dept. of Computer Science and Engineering Warangal India

ISBN: (纸本)9798350310719

In this paper multimodal biometric system is developed using two traits iris and fingerprint. The features generated by iris and fingerprint images are fused at the feature level. The generated fused feature vector template cannot be stored directly on the server, if stored directly can lead to various privacy and security concerns. So, these templates are encrypted in such a way that even when applying any operations on the templates, the templates should be in encrypted form. So, the operations need to be performed in the encrypted domain without decrypting it, and the final result, when decrypted should again give back the correct result as if the operations are performed on the original data. Fully Homomorphic encryption (FHE) scheme is designed to satisfy the above conditions. FHE is used to compute the hamming distance between the reference and probe template in an encrypted domain. To improve accuracy rotational invariant technique is used, which solves rotational inconsistency problems. The computational speed is increased by using a batching scheme to reduce the number of operations during homomorphic multiplication. We have conducted our experiment on the IITD and CASIA dataset. The best EER is obtained in CASIA dataset of 0.01% with a computational time of 0.0152 sec per template. © 2023 IEEE.

关键词： Hamming distance

来源：评论

学校读者我要写书评

暂无评论

Speech To Image Translation Framework for Teacher-Student Learning 3

Speech To Image Translation Framework for Teacher-Student Le...

引用

3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Bittal, Vijaylaxmi Bachhav, Anuradha Sanjay Shahade, Makarand Chavan, Pradnya Rajendra Nikam, Bhavesh Anil Pawar, Ajinkya Anil SVKM's Institute of Technology Dept. of Computer Engineering Dhule India

ISBN: (纸本)9798350322842

Most of the technical concepts written in textual way and these are communicated orally by teachers to students through limited images. Students not able to understand some of the complex topics in expected way. This will create a gap between subject and student's subject understandability. Representing and conveying through images is a convenient and effective way for Teaching Learning process. Filling this gap is very essential because understanding through visualization will enhance learning process. Though, the combo of speech encoding and computational translation in only one model causes a huge difficulty and many complexities. In order to reduce those efforts, speech to image translation framework plays significant role. With this motivation authors designed a framework for teachers-students learning process. In this framework, authors designed framework to abstract characteristics from audio files and trained model using unsupervised machine learning algorithm. In this firstly, a speech encoder encodes the audio and extract some significant and highlighted features from it and applying algorithm on this feature, Authors perform mapping process on these parameters and features of images which are present in dataset. After this process, GAN comes into play which produce corresponding image as output. In comparison to other methods like speech-text-image, text-image, speech-text models, our model approaches on synthesized dataset and reach to higher expectations of user. © 2023 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Enhancing Depression Detection from Narrative Interviews Using Language Models

Enhancing Depression Detection from Narrative Interviews Usi...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Sood, Palak Yang, Xinming Wang, Ping Stevens Institute of Technology Dept. of Computer Science Hoboken United States

ISBN: (纸本)9798350337488

In recent years, the prevalence of mental health issues among young people has significantly increased, especially due to the consequences of COVID-19 pandemic and the widespread adoption of remote work arrangements. Depression has emerged as a major global mental health concern due to its potentially devastating consequences. However, existing methods for depression detection still face several challenges, such as limited data availability, imbalanced labels, and inadequate consideration of contextual information. To tackle these challenges, in this paper, we first create a larger dataset, namely I-DAIC, for depression detection by integrating three existing datasets in the literature. We further fine-tune and examine two pre-trained transformer-based language models by comparing them with two traditional machine learning methods on the I-DAIC dataset. To overcome the difficulty of handling lengthy texts, we explore several customized strategies in combination with the advanced language models. Moreover, we conducted the quantitative analysis of key representative keywords using topic modeling for both non-depression and depression instances. The comprehensive experimental results demonstrated the effectiveness, advantages, and significant potential of pre-trained language models for depression detection with narrative interviews. © 2023 IEEE.

关键词： Depression detection fine-tuned language models long text narrative interviews

来源：评论

学校读者我要写书评

暂无评论

Distress Detection Using a Hybrid SVM - CNN Classifier 1

Distress Detection Using a Hybrid SVM - CNN Classifier

引用

1st International Conference on Computational Intelligence for Information, Security and Communication Applications, CIISCA 2023

作者： Varsha, Modha Aithal, Yukthi R Fathima, Sufia Sen, Snigdha Global Academy of Technology Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350339727

Due to the escalating frequency of reported crimes, there has been a surge in research endeavors focused on various approaches to enhance monitoring and surveillance techniques. As opposed to vision-based applications, which are currently the most used framework for monitoring purposes, audio-based systems can be more flexible and relatively less intrusive. While current research studies predominantly utilize images as the primary input for Deep Learning (DL) algorithms, it is worth noting that sound can also serve as a valuable source of input for these models. In this paper, we propose and develop a novel hybrid deep learning model for identifying and detecting people in distress by their screams. The working of our proposed system is built by integrating sound detection module and DL model which will help us to detect if a person is in distress or not. The system uses hybridization concept consisting of Support Vector Machine (SVM) and Convolutional Neural Network (CNN) models, with the audio snippet undergoing 3 levels of classification, with the accuracy of each level found to be 93%, 100% and 92% respectively. The audio data is finally classified as an instance of distress or no-distress. © 2023 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

An Effective Hybrid Model for Skin Cancer Detection Using Transfer Learning 16

An Effective Hybrid Model for Skin Cancer Detection Using Tr...

引用

16th International Conference on Developments in eSystems Engineering, DeSE 2023

作者： Mohammed, Hussam J. Nafea, Ahmed Adil Almulla, Hussein K. Aliesawi, Salah A. S. Al-Ani, Mohammed M University of Anbar College of Computer Science and Information Technology Dept. Artificail Inteligence Ramadi Iraq University of Anbar Computer Center Ramadi Iraq University of Anbar College of Computer Science and Information Technology Dept. Computer Science Ramadi Iraq Selangor Bangi Malaysia

ISBN: (纸本)9798350381344

Skin cancer is considered one of the most fatal illnesses in the human population. Within the current healthcare system, the procedure of identifying skin cancer is time-consuming and poses a potential risk to human life if not recognized promptly. Early identification of skin cancer is imperative to maximize the likelihood of achieving complete recovery. This research proposed using a hybrid model including DenseNet201 and auto-encoder for feature extraction, and a support vector machine (SVM) as the classifier. The proposed model was evaluated in the ISIC 2016 dataset, which consists of nine different classes. The hybrid model achieved a classification accuracy of 91.09% percent in accurately identifying nine different forms of skin cancer. The findings indicate that the proposed model is competitive compared to the baseline models. This outcome offers substantial assistance to dermatologists and health professionals in the field of skin cancer detection. © 2023 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Data Visualisation of Time Tradable Assets Using Machine Learning

Data Visualisation of Time Tradable Assets Using Machine Lea...

引用

2023 IEEE International Conference on Network, Multimedia and Information technology, NMITCON 2023

作者： Mallikarjunaiah, Nirupama Jain, Rishab S. Vinay, K.R. Navada, Sharan S. Pramod, T.C. Siddaganga Institute of Technology Dept. of Computer Science and Engineering Tumkur India

ISBN: (纸本)9798350300826

Forecasting financial instruments accurately is a complex task due to the volatile, non-linear and dynamic nature of financial markets. Numerous factors, including political events, global economic conditions, and company performance, contribute to the difficulty of predicting outcomes. However, this challenge also provides a wealth of data that can be leveraged to uncover patterns. With the advancement of AI and increased computational power, programmable prediction techniques have emerged as more effective tools for forecasting tradable assets. This paper explores the application of various regression techniques, such as Linear, Support Vector, Polynomial, and Tree Regression, in financial prediction. Additionally, the study incorporates Long Short-Term Memory (LSTM), a method of recurrent neural network model, to analyse an asset's historical behaviour and generate reliable conclusions. The proposed approach aims to address the practical implementation of prediction systems in real-world scenarios while addressing challenges related to the accuracy of the provided values. Furthermore, appropriate visualization techniques are employed to enhance the interpretation and understanding of the results. By combining advanced prediction models and visualization methods, this research endeavours to improve the accuracy of financial predictions and provide valuable insights for decision-making infinancial markets. © 2023 IEEE.

关键词： Data visualization

来源：评论

学校读者我要写书评

暂无评论

Employing Redundancy to Leverage Cybersecurity Protection of Safety-Critical Systems 10

Employing Redundancy to Leverage Cybersecurity Protection of...

引用

10th International Conference on Dependable Systems and Their Applications, DSA 2023

作者： Troubitsyna, Elena Kth - Royal Institute of Technology Dept. of Computer Science Stockholm Sweden

ISBN: (纸本)9798350304770

Safety-critical systems become increasingly open and interconnected, which makes them a target of various cyberattacks. Such cyberattacks might jeopardise system safety and availability. Many safety-critical systems, such as railways, have a very long life cycle and hence, a large number of legacy components. The implementation of modern security protection mechanisms is often restricted due to the rigidness of legacy architecture and high re-certification costs. Therefore, it is desirable to efficiently utilise the potential already present in the system and enhance cybersecurity protection without major modifications. Safety-critical systems usually contain a high degree of redundancy required to achieve fault tolerance. In this paper, we investigate how to utilise redundancy to enhance cybersecurity protection. We demonstrate that by introducing diversity in the redundant architectures and implementing security monitoring, we can potentially enhance cybersecutiry protection of safety-critical systems. © 2023 IEEE.

关键词： Redundancy

来源：评论

学校读者我要写书评

暂无评论

Smart City Surveillance: Survey on Current Status and Future Trends 14

Smart City Surveillance: Survey on Current Status and Future...

引用

14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Neyaz, Hera Paul, Hrituparna Srivastava, Anima Singh, Shiksha Dept. of Computer Science and Engineering Shambhunath Institute of Engineering and Technology India

This paper presents a comprehensive survey on surveillance and security aspects of a smart city. Multiple dimensions of a smart city surveillance system have been discussed. The current trends and methodologies are thoroughly researched and presented. The algorithms of novel methods are reviewed along with analytics and methodologies. Impact of XAI in the smart city surveillance is discussed. Advantages and disadvantages of current infrastructures have been included in the broad literature survey. Lastly, the challenges and future trends are conferred to. © Grenze Scientific Society, 2023.

关键词： Smart city

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 << < 58 59 60 61 62 63 64 65 66 67 > >>

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：