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

3,023 篇 期刊文献
2,052 篇 会议
30 册 图书

馆藏范围

5,105 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,252 篇 工学
- 2,382 篇 计算机科学与技术...
- 1,991 篇 软件工程
- 671 篇 信息与通信工程
- 505 篇 生物工程
- 444 篇 电气工程
- 398 篇 生物医学工程（可授...
- 391 篇 控制科学与工程
- 326 篇 光学工程
- 292 篇 电子科学与技术（可...
- 163 篇 化学工程与技术
- 162 篇 机械工程
- 131 篇 仪器科学与技术
- 130 篇 安全科学与工程
- 123 篇 动力工程及工程热...
- 110 篇 交通运输工程
2,196 篇 理学
- 1,054 篇 数学
- 723 篇 物理学
- 596 篇 生物学
- 435 篇 统计学（可授理学、...
- 204 篇 化学
- 179 篇 系统科学
- 150 篇 地球物理学
880 篇 管理学
- 539 篇 管理科学与工程(可...
- 371 篇 图书情报与档案管...
- 302 篇 工商管理
432 篇 医学
- 371 篇 临床医学
- 318 篇 基础医学(可授医学...
- 179 篇 公共卫生与预防医...
- 176 篇 药学(可授医学、理...
157 篇 法学
- 140 篇 社会学
103 篇 经济学
97 篇 农学
61 篇 教育学
9 篇 文学
9 篇 军事学
5 篇 艺术学
2 篇 历史学

主题

167 篇 deep learning
165 篇 accuracy
151 篇 machine learning
108 篇 training
98 篇 computational mo...
88 篇 feature extracti...
80 篇 real-time system...
79 篇 convolutional ne...
76 篇 predictive model...
70 篇 internet of thin...
70 篇 artificial intel...
70 篇 data models
60 篇 reinforcement le...
52 篇 federated learni...
51 篇 image segmentati...
51 篇 optimization
51 篇 semantics
47 篇 generative adver...
46 篇 graph neural net...
45 篇 forecasting

机构

169 篇 college of compu...
73 篇 department of co...
61 篇 nanyang technolo...
54 篇 department of co...
52 篇 beijing advanced...
42 篇 college of compu...
40 篇 data science ins...
39 篇 department of co...
39 篇 national enginee...
34 篇 university of ch...
33 篇 department of co...
29 篇 school of data a...
27 篇 dipartimento di ...
26 篇 the oskar klein ...
26 篇 school of comput...
26 篇 college of intel...
25 篇 the college of c...
23 篇 center for scien...
23 篇 college of infor...
23 篇 data61 csiro

作者

161 篇 niyato dusit
35 篇 sun geng
32 篇 peng hao
32 篇 chen mingzhe
27 篇 e. j. siskind
27 篇 r. bellazzini
25 篇 j. b. thayer
25 篇 p. spinelli
25 篇 m. kuss
25 篇 guo yike
25 篇 du hongyang
24 篇 li jing
23 篇 p. a. caraveo
23 篇 p. f. michelson
23 篇 s. ciprini
23 篇 s. guiriec
23 篇 wang jiacheng
22 篇 m. ackermann
22 篇 r. rando
21 篇 r. buehler

语言

4,347 篇 英文
744 篇 其他
19 篇 中文
2 篇 斯洛文尼亚文

检索条件"机构=Department of Data and Computing"

共 5105 条记录，以下是91-100 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：

Evolution of Consensus Algorithms in Blockchain Technology

Evolution of Consensus Algorithms in Blockchain Technology

引用

2023 International Conference on Intelligent Systems for Communication, IoT and Security, ICISCoIS 2023

作者： Harshini Poojaa, K. Ganesh Kumar, S. School of Computing SRM Institute of Science and Technology Department of Data Science and Business Systems Chengalpattu India

ISBN: (纸本)9798350335835

Blockchain being a decentralised, distributed ledger, has attracted industries to implement the solutions on blockchain. The transactions are agreed in a deterministic manner because of the availability of consensus algorithms. The state of the machine is concluded based on the agreement generated by the consensus algorithm. The performance of the blockchain system can be increased to the order of magnitude when the right consensus is used. In this paper, the limitations and performance of various consensus algorithms have been reviewed along with the characteristics of the same. In addition to that, this paper compares the consensus algorithms based on various parameters such as speed, double-spending, 51% attack and many more. © 2023 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Exploring Sentiment Detection in Healthcare: An Exhaustive Analysis

Exploring Sentiment Detection in Healthcare: An Exhaustive A...

引用

2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, RMKMATE 2023

作者： Bagiyalakshmi, N. Veeramakali, T. Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur India

ISBN: (纸本)9798350305708

In our daily lives, sentiment analysis is essential. People usually make decisions after seeking advice from others. We used to rely on our judgments before the internet on the advice of our friends and relatives. But now, we have high-performance source sentiment analysis, which collects and analyses opinions from a variety of channels, including social media. To correctly represent emotion in a phrase, we must concentrate on idioms, sarcasm, negations, and context terms. A range of deep learning and machine learning techniques can be used to overcome the aforementioned issues. The aforementioned parameter will be used by the algorithm to identify the polarity of a statement. This study proposal covers the problems with sentiment analysis as well as its numerous levels. The review talks about the challenges and particularities of sentiment analysis. These have to do with issues like textual information, peculiarities of language, emotional vocabulary relevant to particular domains, and security and confidentiality of data. The report also emphasizes how sentiment analysis might promote public healthcare initiatives, boost pharmaceutical methods for making choices, as well as improve patient care. © 2023 IEEE.

关键词： Deep Learning Healthcare Machine learning Recommendation system Sentiment Analysis

来源：评论

学校读者我要写书评

暂无评论

Development of an Enhanced Quality Score Calculation Method for Accurate Assessment of Hotel Quality 5

Development of an Enhanced Quality Score Calculation Method ...

引用

5th International Conference on Advancements in computing, ICAC 2023

作者： Athurugiriya, A. A. A. Gaweshini Sumathipala, Prasanna Hemachandra, K.M. Tharindu Anupa Sri Lanka Institute of Information Technology Faculty of Computing Department of Data Science Malabe Sri Lanka

ISBN: (纸本)9798350358131

In this research paper, an enhanced hotel quality scoring method (EHQSM), is presented as a revolutionary way to analyze hotel quality. The EHQSM combines sentiment analysis, HOLSERV Plus dimensions classification, and amenity scores to deliver a more thorough review. The study generates an overall sentiment score by doing sentiment analysis on reviews categorized into HOLSERV Plus dimensions then thoughtfully averaging it using dimensionspecific weights collected from a survey. The availability of necessary amenities is considered when calculating the amenity score. The novel feature of this approach is how the amenity score, and sentiment score are carefully combined and efficiently weighted using values from the survey. The result is an improved quality score that accurately and thoroughly describes the quality of hotel services. With the goal of facilitating informed decisions for both hotel owners and attentive tourists, this technique establishes an updated standard for the evaluation of hospitality quality. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Enhancing Hotel Customer Satisfaction Assessment with Semantic Search-based Scoring 5

Enhancing Hotel Customer Satisfaction Assessment with Semant...

引用

5th International Conference on Advancements in computing, ICAC 2023

作者： Hemachandra, K.M Tharindu Anupa Sumathipala, Prasanna Athurugiriya, A.A.A Gaweshini Sri Lanka Institute of Information Technology Department of Data Science Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798350358131

Within the hospitality sector, ensuring customer satisfaction takes precedence, particularly in economies such as Sri Lanka, where tourism serves as a vital growth catalyst. Interestingly, disparities often arise between customer ratings and their written evaluations. This study presents an innovative strategy that utilizes semantic search techniques to extract comprehensive insights from customer feedback, leading to the development of a robust hotel scoring system. By exploring intricate emotions via advanced linguistic analysis, this method reveals underlying cues that conventional metrics often overlook. The method's effectiveness is validated through a comparative study with established hotel ratings. This advancement not only refines precise customer satisfaction assessment for hotels but also bears strategic significance for countries aiming to fortify their tourism sectors. In this era centered around data, this research provides a pivotal standpoint for optimizing hospitality evaluation, thereby enriching guest experiences, and guiding well-informed operational choices. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Gesture Showdown: Rock Paper Scissors with AI Vision

Gesture Showdown: Rock Paper Scissors with AI Vision

引用

2025 IEEE International Conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Hemal Babu, H. Yeshwanth, C.D. Shravan, N. Bose, K. Regin Rajalakshmi Institute of Technology Department of Artificial Intelligence and Data Science Chennai India Rajalakshmi Institute of Technology Department of AI&DS and Cloud Computing Chennai India

ISBN: (纸本)9798331512965

This paper presents a gesture-based RockPaper-Scissors game that leverages computer vision and hand gesture recognition to enable intuitive human-computer interaction. Utilizing MediaPipe's pre-trained hand tracking module, the system detects and identifies 21 hand landmarks in real-time to classify gestures as rock, paper or scissors based on angular relationships between key points. OpenCV is used for webcam integration and video frame preprocessing, ensuring seamless interaction. The game compares the recognized gesture with a computer-generated move, dynamically displaying the results and resetting after each round for continuous play. The system identifies gestures through precise angle calculations, differentiating between closed fists, open palms and extended fingers. Sample outputs demonstrate real-time gameplay scenarios, highlighting gesture recognition accuracy and user engagement. Future enhancements include refining recognition accuracy, adding multiplayer functionality, introducing customizable gestures, and deploying the game on web and mobile platforms for broader accessibility. This project showcases the potential of integrating AI and computer vision in creating engaging and user-friendly applications. © 2025 IEEE.

关键词： Gesture recognition

来源：评论

学校读者我要写书评

暂无评论

From Text to Visuals: Advancements in Depression Prediction Using AI and Machine Learning Techniques

From Text to Visuals: Advancements in Depression Prediction ...

引用

2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, RMKMATE 2023

作者： Annapoorani, S. Saravanan, P. Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulatur India

ISBN: (纸本)9798350305708

Social lifestyle and COVID pandemic situation to produce a direct impact on mental health. Depression remains a primary cause of disability worldwide and contributes significantly to the global health burden. It can typically lead to suicidal ideation and have a negative impact on anyone's professional and personal life. Artificial intelligence, machine learning, and deep learning techniques can forecast depression in a timely manner utilizing a variety of resources. Different kinds of sources, such as surveys, social networking sites, video images, and speech, can be used to accurately identify depression without the assistance of a psychiatrist. People on social networking sites express their feelings through appropriate text, which may be examined using machine learning algorithms. Through visual and speech data, deep learning approaches properly provide remarkable accuracy in predicting depression. This survey study is useful in identifying depression accuracy in advanced ways utilizing diverse resources. © 2023 IEEE.

关键词： Classification Algorithm Deep Learning Depression Ensemble Method Machine Learning

来源：评论

学校读者我要写书评

暂无评论

MSNet: Momentum Spillover Network for Indian Stock Market Movement Prediction 20

MSNet: Momentum Spillover Network for Indian Stock Market Mo...

引用

20th IEEE India Council International Conference, INDICON 2023

作者： Patel, Manali Jariwala, Krupa Chattopadhyay, Chiranjoy Svnit Department of Cse Surat India Flame University School of Computing and Data Science Pune India

ISBN: (纸本)9798350305593

Investors and financial analysts require accurate predictions of stock prices to make informed decisions. We present Momentum Spillover Network (MSNet), a deep learning model that predicts stock prices on the National Stock Exchange of India by considering interdependencies existing between stocks in the same sector. Traditional approaches have focused solely on capturing hidden temporal dependencies, ignoring the impact of interconnectedness between stocks. To evaluate MSNet, we experimented with data from companies with the largest market capitalization from various sectors that covers over 70% of the NIFTY-50 index. MSNet effectively identifies the most impactful peer companies and predicts the future price movement of a target company with higher accuracy than existing deep learning approaches, highlighting the importance of incorporating relational dependency between stocks along with temporal dependency. © 2023 IEEE.

关键词： Deep Learning Momentum Spillover Effect Relational Modeling Stock Market Forecasting Temporal Modeling

来源：评论

学校读者我要写书评

暂无评论

Phylogenetic-Informed Generative Adversarial Network for Predicting Mutations in SARS-CoV-2 2

Phylogenetic-Informed Generative Adversarial Network for Pre...

引用

2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Chandar, Vijay Nair, Vishnu G. Rajeswari, D. SRM Institute of Science and Technology School of Computing College of Engineering and Technology Department of Data Science and Business Systems Chennai603203 India

ISBN: (纸本)9798350365269

In the pursuit of developing more effective vaccines against viruses like SARS-CoV-2, understanding their potential mutations is crucial. In order to generate protein sequences, this study presents a unique framework that synergistically blends phylogenetic data with Generative Adversarial Networks (GANs). The proposed method combines the strengths of two models: TEMPO, a transformer-based model proficient in leveraging phylogenetic data for mutation detection in SARS-CoV-2, and MutaGAN, a GAN-based model adept in generating synthetic protein sequences. The phylogenetic data from TEMPO is used in this novel design as the input for the MutaGAN generator, replacing the conventional random noise input used in GANs. The generator may now create synthetic protein sequences that are impacted by the evolutionary past included in the phylogenetic data resulting in the creation of artificial protein sequences that are more biologically significant and lifelike. The discriminator portion of the model, similar to MutaGAN, is still in charge of determining whether or not the input sequences comprise a valid parent-child pair and uses sequences produced by the first GAN as extra negative cases. This prevented the model from going too far off its planned route. Additional investigation into this fascinating confluence of bioinformatics and AI may be possible as a result of this study's conclusions. This approach has tremendous promise in many applications, such as the production of more powerful vaccinations, protein engineering, medication design, and improving our knowledge of biological systems, by forecasting how SARS-CoV-2 could change. A precision of 0.662 and an accuracy of around 0.671, together with a Matthews Correlation Coefficient (MCC) score of 0.313, show that the framework performs very well. These scores show that the framework performs better than a number of cutting-edge baseline techniques. The synthetic protein sequences generated by the framework not only bea

关键词： Coronavirus

来源：评论

学校读者我要写书评

暂无评论

Autoencoders in Graphical Document Retrieval: Cost Function Influence and Rotation Impact

Autoencoders in Graphical Document Retrieval: Cost Function ...

引用

2023 IEEE International Conference on Modelling, Simulation and Intelligent computing, MoSICom 2023

作者： Khade, Rasika Jariwala, Krupa Chattopadhyay, Chiranjoy SVNIT Department of CSE Surat India FLAME University School of Computing and Data Sciences Pune India

ISBN: (纸本)9798350393415

This study explores autoencoder application in graphical document retrieval, focusing on rotation's impact. Specific to this paper are scanned floor plan images. We investigate the pivotal role of cost functions-specifically, Mean Squared Error (MSE) and Consistency Loss-in shaping autoencoder behavior and retrieval accuracy. By subjecting autoencoders to the challenges posed by rotated graphical documents, we decipher the extent to which rotation impacts retrieval outcomes. Concurrently, we dissect the nuanced influence of distinct cost functions on retrieval accuracy, shedding light on their diver-gent contributions. Through rigorous experimentation, we show autoencoder adaptability to rotation and cost function effects on retrieval precision. Our findings underline the significance of cost function selection in enhancing retrieval accuracy. Our insights hold implications for optimizing, refining autoencoder-based methods, empowering digital document analysis practitioners. © 2023 IEEE.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Enhanced study on Deep learning model for kidney segmentation using DCE-MRI

Enhanced study on Deep learning model for kidney segmentatio...

引用

2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, RMKMATE 2023

作者： Nagarajan, S. Ramprasath, M. Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Chengalpattu India

ISBN: (纸本)9798350305708

Medical imaging is capturing pictures of bodily components for diagnostic or research reasons. Because of advancements in image-handling techniques, which include picture recognition, examination, and upgrading, clinical imaging is expanding swiftly. Picture division is a vital subject in picture handling and PC vision with applications, for example, scene grasping, clinical picture examination, mechanical discernment, video observation, expanded reality, and picture pressure, among numerous others. Numerous picture segmentation methods have been created and are available in the literature. There has been a lot of work done to develop techniques for segmenting pictures using deep-learning models since they have proved effective in various vision applications. Deep learning has turned into a functioning exploration point in the field of clinical picture examination. Compared to the laborious and lengthy conventional technique, deep learning (DL) automatic detection algorithms can speed up diagnostics, increase test accuracy, lower expenses, and lessen the workload on the radiologist. Kidney segmentation is an integral part of any non-intrusive computer-assisted diagnostic (CAD) system for rapidly recognising severe renal repudiation because of the intensity of inhomogeneity brought on by errors in the image capture process, efficient kidney segmentation is challenging in evaluating and therapeutic planning of kidney-related disorders. This article addresses recent developments in DL-based kidney tumor segmentation systems. We highlight their fundamental components and numerous approaches as we discuss the main medical image kinds, segmentation methods, and evaluation standards for segmentation outcomes in kidney tumor++ segmentation. © 2023 IEEE.

关键词： Automatic Detection algorithms Computer-Assisted diagnostic system Deep Learning Kidney tumor segmentation Vision applications

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 << < 6 7 8 9 10 11 12 13 14 15 > >>

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：