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

89,152 篇 会议
38,592 篇 期刊文献
1,303 册 图书

馆藏范围

129,047 篇 电子文献
3 种 纸本馆藏

日期分布

学科分类号

72,939 篇 工学
- 46,491 篇 计算机科学与技术...
- 37,158 篇 软件工程
- 18,985 篇 信息与通信工程
- 12,507 篇 控制科学与工程
- 11,938 篇 电气工程
- 11,515 篇 电子科学与技术（可...
- 8,313 篇 生物工程
- 7,068 篇 生物医学工程（可授...
- 6,829 篇 光学工程
- 5,177 篇 机械工程
- 4,684 篇 化学工程与技术
- 4,565 篇 仪器科学与技术
- 4,448 篇 动力工程及工程热...
- 4,147 篇 材料科学与工程（可...
- 3,451 篇 网络空间安全
- 3,090 篇 安全科学与工程
43,612 篇 理学
- 19,436 篇 数学
- 16,770 篇 物理学
- 9,558 篇 生物学
- 6,365 篇 统计学（可授理学、...
- 5,287 篇 化学
- 4,683 篇 系统科学
17,902 篇 管理学
- 11,310 篇 管理科学与工程(可...
- 7,404 篇 图书情报与档案管...
- 5,398 篇 工商管理
7,305 篇 医学
- 5,947 篇 临床医学
- 5,320 篇 基础医学(可授医学...
- 3,283 篇 药学(可授医学、理...
- 3,158 篇 公共卫生与预防医...
3,535 篇 法学
- 2,902 篇 社会学
2,242 篇 经济学
1,869 篇 农学
1,155 篇 教育学
595 篇 文学
282 篇 军事学
123 篇 艺术学
14 篇 哲学
8 篇 历史学

主题

3,891 篇 accuracy
3,173 篇 deep learning
2,932 篇 feature extracti...
2,829 篇 computer science
2,793 篇 machine learning
2,666 篇 computational mo...
2,291 篇 training
1,993 篇 real-time system...
1,881 篇 internet of thin...
1,849 篇 support vector m...
1,794 篇 convolutional ne...
1,776 篇 predictive model...
1,638 篇 artificial intel...
1,470 篇 optimization
1,405 篇 neural networks
1,350 篇 wireless sensor ...
1,261 篇 security
1,254 篇 data mining
1,219 篇 bandwidth
1,216 篇 computer archite...

机构

1,093 篇 cavendish labora...
1,022 篇 department of ph...
970 篇 physikalisches i...
961 篇 oliver lodge lab...
770 篇 university of ch...
680 篇 chitkara univers...
650 篇 department of el...
615 篇 infn laboratori ...
606 篇 infn sezione di ...
585 篇 infn sezione di ...
568 篇 infn sezione di ...
561 篇 fakultät physik ...
550 篇 school of physic...
540 篇 horia hulubei na...
528 篇 department of ph...
526 篇 school of physic...
515 篇 h.h. wills physi...
510 篇 imperial college...
502 篇 nikhef national ...
501 篇 stfc rutherford ...

作者

263 篇 barter w.
256 篇 a. gomes
245 篇 c. alexa
241 篇 j. m. izen
235 篇 j. wang
234 篇 c. amelung
233 篇 g. bella
233 篇 blake t.
232 篇 j. strandberg
232 篇 d. calvet
231 篇 s. chen
229 篇 beiter a.
224 篇 bellee v.
223 篇 amato s.
222 篇 betancourt c.
221 篇 boettcher t.
220 篇 borsato m.
219 篇 bowcock t.j.v.
218 篇 brundu d.
217 篇 bencivenni g.

语言

105,757 篇 英文
21,997 篇 其他
1,509 篇 中文
119 篇 日文
26 篇 斯洛文尼亚文
25 篇 法文
24 篇 德文
8 篇 朝鲜文
6 篇 土耳其文
5 篇 阿拉伯文
4 篇 俄文
2 篇 荷兰文
1 篇 爱沙尼亚文
1 篇 意大利文
1 篇 波兰文
1 篇 葡萄牙文

检索条件"机构=Department of Computer Engineering and Informatics Computer Technology Institute"

共 129047 条记录，以下是4841-4850 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：

LIFELINE-A Unified Solution for Healthcare Donation

LIFELINE-A Unified Solution for Healthcare Donation

引用

2023 International Conference on Advancement in Computation and computer Technologies, InCACCT 2023

作者： Bavyaa, R. Raja Mohamed, S. Sathyanarayanan, K. Mithun, V. KIT-Kalaignarkarunanidhi Institute of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350396485

Over the years, the healthcare sector has found its boom and requirement increase under the category of donation. The only source of blood and blood components such as plasma and platelets for patients in need of the same is open-handed donors. The issue here is not lack of people willing to donate;rather, it is the difficulty in finding an ardent supporter or donor at the ideal moment. A necessity arises where one should gather several global health groups so that people could be connected during a crisis. A one stop facilitation towards healthcare donation is LIFELINE-A Centralized system for Donation of Blood, Plasma, Platelets and Human Organs. It is an extended web application to unify the needs of the healthcare world by merging in the donation of blood and its components along with specified organ transplant notification and organ donation volunteership. Although there are several applications for blood donation, the major drawback was figured out when issues raised to find out other donors like plasma during an instance of COVID. The main focus is to create a fully functional system that integrates all kinds of health-oriented donation with timely updated information thus by establish a direct connection between the donor and recipient irrespective of the odds of technology at both ends. Distinctive features like, notification specific to the locale range of the patient, exemption according to donor's donation interval, activity status of the donor, authenticity of information furnished, location tracking of the donor until the donor reaches the recipient and further other enhancements are being focused on. © 2023 IEEE.

关键词： Platelets

来源：评论

学校读者我要写书评

暂无评论

Adoption of Blockchain technology in Land Registry Systems 3

Adoption of Blockchain Technology in Land Registry Systems

引用

3rd International Conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Sah, Chandan Kumar Chandavarkar, B.R. National Institute of Technology Karnataka Department of Computer Science & Engineering Surathkal India

ISBN: (纸本)9798350300710

The adoption of blockchain technology in land registry systems has gained significant attention in recent years due to its potential to increase efficiency, transparency, and security. This paper provides an overview of the current state of land registry systems and the challenges they face, in-cluding issues related to fraud, corruption, and a lack of trust. Then it discusses how blockchain technology can address these challenges by providing a decentralized, tamper-proof, and transparent platform for recording land transactions. The paper also examines some of the existing blockchain-based land registry systems and their features, using approaches and methodologies, including the use of smart contracts and digital signatures. Finally, the paper discusses the potential benefits and limitations of adopting blockchain technology in land registry systems and provides recommendations for policymakers and stakeholders interested in implementing these systems. © 2023 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Based Approach to Disinformation Detection Using Twitter Data 2

Machine Learning Based Approach to Disinformation Detection ...

引用

2nd International Conference for Advancement in technology, ICONAT 2023

作者： Yadav, Sanjeev Kumar, C.R.S. Defence Institute of Advanced Technology Computer Science and Engineering Department Pune India

ISBN: (纸本)9781665475174

Fake news detection on social media has assumed enhanced importance and is a trending research topics for data analysts around the world. While most of fake news may be aimed at commercial or personal gains, some of it may cause deliberate harm to a nation's progress. Twitter, as part of social media platforms (SMPs) is a leading portal being used by everyone for gaining access and giving out information. Leading the spread of disinformation propagation via fake news, twitter has emerged as one of the leading SMPs. The sheer quantum of tweets makes it very challenging to sort the news and remove anomalies. Various machine learning techniques have been devised to identify fake tweets. This report aims at studying prominent machine learning techniques for detection of disinformation propagation on Twitter. Generally, researchers have identified detection of fake tweets as a classification problem but some unsupervised and unconventional learning models are also available. Major effort for any supervised learning technique is creation of data corpus. The paper highlights some techniques for the same. Consequently, inclusion of context as part of feature extraction has been achieved to align the intent behind the tweet with the text. As a first step towards the solution, a sentiment analysis of tweets from a set of users has been recommended details have been illustrated in subsequent sections. Various context based technique have been studied and implemented on data corpus and results produced have been compared. The report also studies various NLP techniques for data pre-processing and feature extraction before using classifiers to draw the outcome. © 2023 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Ensemble Model of U-Net EfficientNet-B3, U-Net EfficientNet B6, CoaT, SegFormer for Segmenting Functional Tissue Units in Various Human Organs 14

Ensemble Model of U-Net EfficientNet-B3, U-Net EfficientNet ...

引用

14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Bharadwaj, Guda Venkat Sree, Yaramala Ramya Varshita, Jammigumpula Lakshmi Chebrolu, Srilatha National Institute of Technology Department of Computer Science and Engineering Andhra Pradesh India

ISBN: (纸本)9798350335095

Accurately identifying and segmenting functional tissue units is critical for comprehending the structure and function of human organs. This work presents a pioneering method for identifying and semantically segmenting functional tissue units in diverse human organs using an ensemble model. The proposed approach initially extracts features from medical images using a pre-trained U-Net with a backbone as EfficientNet-B3, U-Net with a backbone as EfficientNet-B6, SegFormer MiT-B3, CoaT lite small, and CoaT lite medium, which is then ensembled and utilized to forecast the pixel-wise segmentation mask. Additionally, attention mechanisms were integrated to capture the contextual dependencies of tissue units within the images. To assess the performance of the proposed ensemble model, images from data sources Human Bio-Molecular Atlas Program (HuBMAP) and Human Protein Atlas (HPA) consisting of biopsy slides from various organs were considered. Experiments indicate that the proposed ensemble model outperforms individual models when evaluated using the Dice Co-efficient metric. This innovative approach has the potential to be utilized in other medical imaging tasks that involve functional tissue units for disease diagnosis and treatment planning. © 2023 IEEE.

关键词： Biopsy

来源：评论

学校读者我要写书评

暂无评论

Detection of Motion Vector-Based Stegomalware in Video Files 1

引用

International Conference on computer Vision and Machine Intelligence, CVMI 2022

作者： Nair, Sandra V. S. Arun Raj Kumar, P. Department of Computer Science and Engineering National Institute of Technology Calicut Kozhikode India

ISBN: (数字)9789811978678

ISBN: (纸本)9789811978661

Cybercriminals are increasingly using steganography to launch attacks on devices. The cyberattack is more threatening as steganography hides the embedded malware, if any, making it harder to detect by various anti-virus tools. Such malware is called stegomalware. Since video files are larger and have a complex structure, they also have a high capacity for hiding malware. Motion vector (MV)-based steganography techniques do not cause much distortion in video files. Therefore, it remains to be one of the leading video steganography techniques. This paper deals with a lightweight solution for MV-based stegomalware detection in video files. Our model is compatible with state-of-the-art video coding standards having variable macroblock sizes and different motion vector resolutions. The proposed method obtained an accuracy of 95.8% on testing H.264 videos with various embedding rates. The 81-D spatial and temporal features result in the high performance of the proposed model. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Video signal processing

来源：评论

学校读者我要写书评

暂无评论

Facial Emotion Detection using Machine Learning and Deep Learning Algorithms 2

Facial Emotion Detection using Machine Learning and Deep Lea...

引用

2nd International Conference on Edge Computing and Applications, ICECAA 2023

作者： Bhogan, Snehal Sawant, Kedar Gondalekar, Nidhi Carvalho, Rachel Kalangutkar, Vassant Mathew, Alleena Agnel Institute of Technology and Design Department of Computer Engineering Goa Assagao India

ISBN: (纸本)9798350347579

Emotion recognition plays a critical role in various domains, such as human-computer interaction, psychology, and market research. With the growing popularity of social media platforms and the increasing use of multimedia content, the ability to automatically recognize emotions from images has become a significant research area. In this research, through a pre-trained CNN model, rich and high-level features that effectively capture the emotional content present in the images are extracted. The dataset for the same is FER2013 which is downloaded through Kaggle and the data to test emotion will be taken live feed through a webcam. The extracted features are then fed into three classifiers namely: CNN, KNN, and random forest. Conducted experiments on a publicly available emotion recognition dataset named FER-2013. It illustrates the efficacy of change in accuracy by achieving a vast difference between the CNN, KNN, and Random Forest. Moreover, compared the performance with other state-of-the-art methods, demonstrating its superior performance in accurately recognizing emotions from images. © 2023 IEEE.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Quantum Machine Learning Techniques based on Nurturing Agri-Ontology Framework in Agricultural Science 3

Quantum Machine Learning Techniques based on Nurturing Agri-...

引用

3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Deepa, R. Jayalakshmi, V. Thilakavathy, P. Bennet Prabhu, A. Surendran, R. Srm Institute of Science and Technology School of Computing Department of Computing Technologies Chennai India Drbccc Hindu College Department of Computer Applications Chennai India Computer Science and Engineering Vels Institute of Science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Kone Elevator India Technology & Engineering Centre Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350375190

The absence of a consistent ontological framework often impedes efficient knowledge organization and sharing within the agricultural community, despite the quantity of data created in agricultural research. The lack of defined vocabulary and conceptual frameworks hinders data integration, agricultural research, and innovation by preventing interoperability between databases and systems. To address these issues, this research work proposes the Nurturing Agri-Ontology Framework (NAOF), which offers a systematic approach to creating and updating agricultural ontologies. Ontologies that faithfully portray agricultural ideas and connections can be more easily created with the help of NAOF, which combines ideas from knowledge management, agricultural science, and ontology engineering. NAOF aims to ensure that the ontologies produced reflect the wide range of viewpoints and terminology used in agricultural research by encouraging cooperation among stakeholders, ontology engineers, and domain specialists. In this study, the improvement of knowledge organization, sharing and integration in the agricultural area is shown with the application of NAOF. Using this research study, scientists can build ontologies that improve agricultural decision-making, data interoperability, and the discovery of new information. Using quantum machine learning techniques, a strong foundation of knowledge can be laid for several agricultural applications, such as precision agriculture, crop management, and the formulation of agricultural policies. Ontology coverage, interoperability, scalability, and usability are established evaluation parameters that are used to assess the efficacy of NAOF in this research work. The analysis shows that NAOF effectively solves the problems and creates a better agricultural knowledge ecosystem by thoroughly evaluating it using these standards. © 2024 IEEE.

关键词： Ontology

来源：评论

学校读者我要写书评

暂无评论

Enhanced capsule generative adversarial network with Blockchain fostered Intrusion Detection System for Enhancing Cyber security in Cloud 2

Enhanced capsule generative adversarial network with Blockch...

引用

2nd International Conference on Smart Technologies and Systems for Next Generation Computing, ICSTSN 2023

作者： Ravi Kanth, R. Prem Jacob, T.P. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350348002

Cloud computing (CC) is vulnerable to existing information technology attacks, since it extends and utilizes information technology infrastructure, applications and typical operating systems. In this manuscript, an Enhanced capsule generative adversarial network (ECGAN) with blockchain based Proof of authority consensus procedure fostered Intrusion detection (ID) system is proposed for enhancing cyber security in CC. The data are collected via NSL-KDD benchmark dataset. The input data is fed to proposed Z-Score Normalization process to eliminate the redundancy including missing values. The pre-processing output is fed to feature selection. During feature selection, extracting the optimum features on the basis of univariate ensemble feature selection (UEFS). Optimum features basis, the data are classified as normal and anomalous utilizing Enhanced capsule generative adversarial networks. Subsequently, blockchain based Proof of authority (POA) consensus process is proposed for improving the cyber security of the data in cloud computing environment. The proposed ECGAN-BC-POA-IDS method is executed in Python and the performance metrics are calculated. The proposed approach has attained 33.7%, 25.7%, 21.4% improved accuracy, 24.6%, 35.6%, 38.9% lower attack detection time, and 23.8%, 18.9%, 15.78% lower delay than the existing methods, like Artificial Neural Network (ANN) with blockchain framework, Integrated Architecture with Byzantine Fault Tolerance consensus, and Blockchain Random Neural Network (RNN-BC) respectively. © 2023 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Automatic extraction of sequence diagram semantic information 5

Automatic extraction of sequence diagram semantic informatio...

引用

5th International Conference on Machine Learning, Big Data and Business Intelligence, MLBDBI 2023

作者： Wang, Kai Liu, Wei Mu, Yongan Gao, Sheng Wuhan Institute of Technology Department of Computer Science and Engineering Dcse Wuhan China

ISBN: (纸本)9798350359930

In the realm of software reuse, particular attention has been devoted to the reuse of software design. The UML (Unified Modeling Language) sequence diagram, serving as a dynamic representation, adeptly reflects the evolution and progression of a system. During the software verification phase, it proves instrumental in examining the correctness and consistency of the system. Consequently, the automatic identification and extraction of semantic elements within UML sequence diagrams have become imperative. To address this issue, a Sequence Diagram Extraction (SDE) method based on object detection and text extraction is proposed. This method employs grayscale processing coupled with morphological operations to preprocess distorted images, thereby reducing noise from the original images. The You Only Look Once-version 5 (YOLOv5) algorithm, a deep learning model, is applied to detect each role, object, control focus, and message on the image. Precise localization, segmentation, and cropping of each region are performed. The results are input into the EasyOCR(A text recognition model that has been trained many times) algorithm to execute accurate optical character recognition for every extracted block region. Finally, the detection outcomes undergo semantic merging to obtain comprehensive semantic information for the entire sequence diagram. The effectiveness of the proposed approach is validated through the application of the method to fifty different sequence diagrams, affirming its viability. © 2023 IEEE.

关键词： Software design

来源：评论

学校读者我要写书评

暂无评论

Harnessing the Power of CNN to Detect Late and Early Blight in Potato with Enhanced Accuracy 3

Harnessing the Power of CNN to Detect Late and Early Blight ...

引用

3rd International Conference for Advancement in technology, ICONAT 2024

作者： Tripathi, Kaustubh Taneja, Neeti Ahmed, Ibrar Soni, Dhruv Kumar Taneja, Ashu Noida Institute of Engineering and Technology Department of Computer Science and Engineering Uttar Pradesh Greater Noida India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350354171

Potatoes are a ubiquitous vegetable in every household. Potato planting has been widespread in India for the past decades. However, potato output is being impeded by diseases such as late blight and early blight [1], which result in higher production costs. The objective of this project is to develop a rapid disease detection procedure using deep learning techniques. The goal is to diagnose diseases in potato crops at an early stage, hence increasing potato production. The diagnosis will be done using digital methods. Our primary objective is to identify and diagnose potato diseases by utilizing leaf images that have been enhanced and trained using the Convolutional Neural Network (CNN) technique. This study provides a comprehensive explanation of image processing and deep learning algorithms used in automated systems to detect and classify potato leaf diseases. Image processing is the optimal choice for the detection and diagnosis of agricultural illnesses. This study involves the division of around 2100 images of healthy and afflicted potato leaves, which were obtained via Kaggle and other pre-prepared models. The program forecasts an accuracy of 97.27% when tested with 20% test and validation data and 80% training data. Our results demonstrate that we successfully completed all essential duties in detecting potato diseases. © 2024 IEEE.

关键词： Convolutional neural networks

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 << < 481 482 483 484 485 486 487 488 489 490 > >>

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：