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

20,082 篇 会议
13,063 篇 期刊文献
314 册 图书

馆藏范围

33,459 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

20,763 篇 工学
- 14,511 篇 计算机科学与技术...
- 11,958 篇 软件工程
- 4,832 篇 信息与通信工程
- 3,339 篇 控制科学与工程
- 2,704 篇 生物工程
- 2,695 篇 电气工程
- 2,163 篇 电子科学与技术（可...
- 2,052 篇 生物医学工程（可授...
- 1,773 篇 光学工程
- 1,369 篇 机械工程
- 1,257 篇 化学工程与技术
- 1,193 篇 动力工程及工程热...
- 1,047 篇 网络空间安全
- 1,027 篇 仪器科学与技术
- 951 篇 安全科学与工程
- 922 篇 材料科学与工程（可...
11,935 篇 理学
- 5,844 篇 数学
- 3,859 篇 物理学
- 2,998 篇 生物学
- 1,983 篇 统计学（可授理学、...
- 1,385 篇 化学
- 1,248 篇 系统科学
5,597 篇 管理学
- 3,418 篇 管理科学与工程(可...
- 2,398 篇 图书情报与档案管...
- 1,511 篇 工商管理
2,212 篇 医学
- 1,769 篇 临床医学
- 1,587 篇 基础医学(可授医学...
- 1,060 篇 公共卫生与预防医...
- 954 篇 药学(可授医学、理...
1,167 篇 法学
- 960 篇 社会学
600 篇 经济学
514 篇 农学
366 篇 教育学
208 篇 文学
65 篇 军事学
44 篇 艺术学
9 篇 哲学
5 篇 历史学

主题

1,129 篇 accuracy
1,111 篇 deep learning
733 篇 machine learning
726 篇 computational mo...
692 篇 training
667 篇 feature extracti...
514 篇 predictive model...
498 篇 real-time system...
464 篇 internet of thin...
454 篇 convolutional ne...
433 篇 support vector m...
408 篇 data models
335 篇 semantics
298 篇 computer science
278 篇 reliability
272 篇 artificial intel...
269 篇 optimization
263 篇 neural networks
257 篇 scalability
256 篇 computer archite...

机构

232 篇 school of comput...
194 篇 department of co...
153 篇 key laboratory o...
150 篇 university of ch...
125 篇 university of sc...
120 篇 department of co...
119 篇 school of comput...
116 篇 school of comput...
115 篇 school of comput...
112 篇 department of co...
111 篇 school of comput...
111 篇 institute of com...
104 篇 college of compu...
102 篇 department of co...
101 篇 school of comput...
100 篇 school of comput...
97 篇 school of comput...
94 篇 north-west unive...
92 篇 national enginee...
90 篇 department of co...

作者

172 篇 niyato dusit
104 篇 bastieri d.
97 篇 ferrara g.
97 篇 ardid m.
96 篇 chen a.
95 篇 calvo d.
83 篇 gal t.
82 篇 zheng wei-shi
82 篇 bozza c.
80 篇 anjali t.
74 篇 fang j.
74 篇 feng c.f.
72 篇 li xin
69 篇 li cheng
68 篇 jiang k.
67 篇 kuleshov d.
64 篇 liu d.
63 篇 kalekin o.
61 篇 chen m.j.
60 篇 min z.

语言

30,086 篇 英文
3,117 篇 其他
295 篇 中文
6 篇 日文
4 篇 法文
3 篇 德文
1 篇 西班牙文
1 篇 朝鲜文
1 篇 俄文

检索条件"机构=School of Computing Science and Engineering School Of Computing Science & Engineering"

共 33459 条记录，以下是4891-4900 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：

Automated Regional Language News Article Classification System for Kannada and Telugu 5

Automated Regional Language News Article Classification Syst...

引用

5th IEEE International Conference on Advances in Electrical, computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Gupta, Deepa Thejaa, K. Nair, Aarathi Rajagopalan Katti, Panduranga Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350356236

The increasing amount of digital news content has created a pressing need for automated systems that can efficiently organize and categorize articles. This study focuses on developing an automated classification system for Kannada and Telugu news articles, targeting predefined categories. For Kannada, the categories include Entertainment, Sports, and Lifestyle, while for Telugu, the categories are Sports, Business, and Entertainment. With the help of the techniques available in natural language processing and the available models in machine learning, the system preprocesses the textual data in both languages to extract meaningful features for classification. Several classification algorithms are explored, with a focus on evaluating model performance using standard metrics. The results demonstrate that embeddings like KannadaSBERT and TeluguSBERT significantly improve classification accuracy, showing a clear advantage in understanding and categorizing regional language text. This work addresses a critical gap in the field of NLP for regional Indian languages by providing a structured approach to classifying Kannada and Telugu news articles. It contributes to enhancing the organization and accessibility of information for Kannada - and Telugu-speaking communities, thereby advancing research in low- resource language processing. © 2025 IEEE.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Understanding Graph Neural Networks Models for Healthcare Fraud Detection in Insurance Claims

Understanding Graph Neural Networks Models for Healthcare Fr...

引用

Intelligent and Innovative Technologies in computing, Electrical and Electronics (IITCEE), International Conference

作者： Archana Reddy P. Divya Jyothi G. Velumury Varshita Chennupati Akshitha Aiswariya Milan K. Department of Computer Science & Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

This study suggests using graph algorithms to detect healthcare fraud, a serious issue that can lead to significant financial losses and compromise patient care. Health care fraud is a representation of deceitful acts carried out by health providers, patients, or other individuals for the purpose of gaining undue financial profit from the health insurance program. It includes false billing, misrepresentation of diagnosis and procedure, and kickbacks at the expense of substantial financial loss and deterioration of patient care. Our approach models the relationships between patients, healthcare providers, physicians, and procedures as a graph to identify unusual patterns that may indicate fraud. We utilize publicly available tabular datasets, including beneficiary data and claims from inpatient stays and outpatient visits, transforming them into a graph structure to create a unified dataset. The system employs algorithmic analysis and graph construction techniques to identify significant nodes, abnormal clusters, and outliers within the healthcare network. This strategy offers a viable method for reducing healthcare fraud, enhancing the integrity of insurance systems, and ensuring that funds are appropriately allocated to legitimate medical needs. Ultimately, this study aims to decrease the rate of fraud in society.

关键词： Java Biological system modeling Insurance Medical services Predictive models Data models Fraud Medical diagnostic imaging Stress Python

来源：评论

学校读者我要写书评

暂无评论

Automated Semantic Segmentation of Cervical Cells Using High-Resolution Network

Automated Semantic Segmentation of Cervical Cells Using High...

引用

Advances in Electrical, computing, Communication and Sustainable Technologies (ICAECT), International Conference on

作者： Resmi S Rimjhim Padam Singh Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

With an emphasis on the Cx22 dataset, this work offers a novel method of semantic segmentation applied to cervical cytology images. To precisely segment cervical cell structures within the images, the study makes use of deep learning techniques. In this work we are proposing different deep network models, U-Net, LinkNet, PSPNet and HRNet to perform semantic segmentation of the cells in the cervical cytology images. The performance evaluation of all the models are done using the high quality Cx22 dataset with 14,946 finely annotated cellular instances and the HRNet deep model gives better segmentation results and shows its effectiveness in accurately drawing cell boundaries. The outcomes demonstrate how our method can improve automated cervical cytology analysis with a very good F-score of 92% which leads to improvements in diagnostic support and medical image processing.

关键词： Deep learning Performance evaluation Instance segmentation Image analysis Semantic segmentation Biomedical image processing Medical diagnostic imaging

来源：评论

学校读者我要写书评

暂无评论

Effective Complaint Detection in Financial Services through Complaint, Severity, Emotion and Sentiment Analysis

Effective Complaint Detection in Financial Services through ...

引用

3rd International Conference on Machine Learning and Data engineering, ICMLDE 2024

作者： Athira Adith, M. Gupta, Deepa Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

Sentiment analysis plays a crucial role in understanding customer feedback and opinions within the financial domain. This research addresses the problem of sentiment-aware complaint identification using the FINancial Complaint CORpus (FINCORP) dataset, which provides annotated complaints along with sentiment, emotion and severity labels. The dataset encompasses various sentiment classes including Negative, Neutral, and Positive, enabling a wide understanding of customer sentiment towards financial products and services. Leveraging natural language processing (NLP) techniques such as text classification and sentiment analysis, this study aims to develop models capable of accurately detecting and categorizing sentiment, emotion of customers and the severity level of financial complaints. Effectively analyzing these factors allows financial institutions to gain valuable insights into customer satisfaction levels, pinpointing areas for improvement and enhance both customer experience and service quality. This research contributes to the advancement of sentiment analysis methodologies in the financial domain, facilitating better decision-making and customer relationship management strategies. DistilBERT, Glove and RoBERTa has outperformed in classifying the sentiment, emotion and severity of complaints, achieving F1-scores of 0.71, 0.74, and 0.86, respectively using logistic regression and Bi-LSTM classifiers. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Enhancing Career Guidance for Students Through Retrieval Augmented Generation

Enhancing Career Guidance for Students Through Retrieval Aug...

引用

International Conference on Inventive Computation Technologies (ICICT)

作者： Akhil Swarop S Ganeshkaran M Hanish K R Hidesh Balaji C U Bindu K R Department of Computer Science and Engineering Amrita School of Computing Coimbatore Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331512248

ISBN: (纸本)9798331512255

In today's scenario, providing specialized career guidance according to one's own unique skill set is very vital for guiding young professionals in fields which they are most suitable for and well equipped with the required skill set to excel in a specific field. Nevertheless, there is a significant obstacle due to the proliferation of areas of work, and this proves to be very big difficulty in identifying a person's niche. We provide an AIbased approach based on Retrieval Augmented Generation (RAG) to tackle this problem. This tool helps professionals find unique and personalized jobs and job listings based on their resumes by utilizing cutting-edge natural language processing and retrieval techniques. The required skill set, education and prior work experience of the user will be easily acquired by parsing their provided resumes. The system offers tailor made recommendations by giving the extracted data from the resumes as prompts to a LLM which utilizes retrieval techniques which retrieves matched job titles from our database. The system then provides the user with live job listings based on the recommended job which are the most suitable for the user, from top job hiring sites to which the user can apply to. The system also provides suggestions on areas the user can develop their abilities to be well equipped for the current job market.

关键词： Performance evaluation Analytical models engineering profession Databases Jobs listings Resumes Retrieval augmented generation Semantics Education Data mining

来源：评论

学校读者我要写书评

暂无评论

Secured Data Access for Alzheimer’s Patients Using Blockchain And Machine Learning: A Novel Approach

Secured Data Access for Alzheimer’s Patients Using Blockcha...

引用

Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： M Diviya Siva Sandeep Yenumula Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

Accessing and managing Alzheimer patient data provided by the patients themselves poses a challenge to both the research and healthcare community as it is necessary to protect the privacy of the patient. In this paper, we are proposing a decentralized, secure storage and access control system, based on smart contracts and Interplanetary File System (IPFS), that makes use of a blockchain based architecture. Access permissions are granted through the use of smart contracts ensuring that sensitive information is only accessed by approved parties. The patient’s data is kept off-chain using IPFS enhancing the efficiency and integrity of the data management. Additionally, there is an integrated model of machine learning, namely XGBoost, which is used to model and forecast the progression of Alzheimer disease with an aim of providing tailored medical insights. This technique is applied in providing enhanced security of the data and more advanced analytic insight into Alzheimer care.

关键词： Access control Data privacy Data security Smart contracts Medical services Machine learning Predictive models Blockchains InterPlanetary File System Alzheimer's disease

来源：评论

学校读者我要写书评

暂无评论

Enhancing Dysarthric Speech with Short-Time Fourier Transform and Fully Connected Neural Networks

Enhancing Dysarthric Speech with Short-Time Fourier Transfor...

引用

Next Generation Communication & Information Processing (INCIP), International Conference on

作者： Bandaru Sai Kiran K. Ashwini Bontala Abhiram Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9798331528140

ISBN: (纸本)9798331528157

Denoising and enhancement of speech signals are in general a critical process in fixing speech signals that are noisy due to noise interference in real-life situation. They are highly important to transform speech is understandable forms. In this paper, a speech denoising process that makes use of the Short-Time Fourier Transform (STFT) which is a widely recognized method used for non-stationary signals is used. The concept of STFT is converting the noisy speech from the time domain into the frequency domain, which allows for a more productive parting of the noise and speech elements. The noise frequency is recognized and decreased, using a reverse STFT (ISTFT) process thereafter. The importance of speech enhancement for the sake of persons with speech disorders lies in the following: it helps them to improve their communication skills and quality of life in general. This paper presents a deep learning-based system that uses STFT for extraction of features and trains a FCNN for the purpose of enhancing dysarthric speech. Our model was trained on the TORGO dataset and developed with recorded samples of dysarthric speech, optimized to increase intelligibility and clarity without disturbing naturalness. The experiment results are outstandingly high, showing quality improvements in our model, and will successfully compete with the state-of-the-art approaches in real-time tasks for speech enhancement. With the result of successful experimentation, we will prepare an Android application involving the model in order to offer users a comfortable platform for real-time speech enhancement. It shows promise for actual implementations in assistive communication devices that may help people with impairments of speech.

关键词： Time-frequency analysis Fourier transforms Operating systems Noise reduction Noise Speech recognition Speech enhancement Feature extraction Real-time systems Noise measurement

来源：评论

学校读者我要写书评

暂无评论

Leveraging Machine Learning to Predict Obesity Trends: Insights from Lifestyle and Biometric Data

Leveraging Machine Learning to Predict Obesity Trends: Insig...

引用

Computational, Communication and Information Technology (ICCCIT), International Conference on

作者： Rishi Manikanta Adapala Yaswanth Kancharla Baba Ameer Shaik Jyotsna C Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bangalore India

ISBN: (数字)9798331512965

ISBN: (纸本)9798331512972

This is increasingly important as global obesity rates continue to rise: the causes need to be understood, and the ability to predict trends determined. In this study, we use machine learning techniques to predict obesity trends given lifestyle and biometric data from a large obesity dataset. Our methodology starts with data preprocessing that includes transforming categorical variables into numerical variables and standardizes the numerical variables into such a form so that machine learning algos can work with them properly. Supervised machine learning models, such as tree based methods, neural networks and various ensemble techniques are applied, and evaluated. For determining the most effective predictive approach, these models are evaluated by several performance metrics such as accuracy, precision, recall, and F1 score; the best model is chosen based on these metrics. In addition, the study includes explainable AI technique (SHAP—SHapley Additive exPlanations; LIME—Local Interpretable Model-Agnostic Explanations) to make the results more interpretable. The results from these methods provide insight into how different lifestyle and biometric factors contribute to the prediction of obesity; such as physical activity, diet patterns, and body mass index. The results from this work demonstrate not only how machine learning can improve prediction accuracy but also how these methods can provide actionable insights into the many contributing factors to obesity.

关键词： Biometrics Obesity Accuracy Biological system modeling Machine learning Predictive models Market research Data models Real-time systems Random forests

来源：评论

学校读者我要写书评

暂无评论

Gaining Perspective into Cloud computing: A Business-Oriented Approach 4

Gaining Perspective into Cloud Computing: A Business-Oriente...

引用

4th IEEE International Conference on computing, Communication, and Intelligent Systems, ICCCIS 2023

作者： Ahmad, Javed Ahmad, Shahnawaj Arif, Mohd. Nazim, Mohd Sharda School of Engineering and Technology Sharda University Department of Computer Science and Engineering Greater Noida201110 India Bennett University Department of Computer Science and Engineering Uttar Pradesh Greater Noida201310 India School of Computing Science and Engineering Department of Computer Applications Uttar Pradesh Greater Noida203201 India Noida Institute of Engineering and Technology Department of CSE Uttar Pradesh Greater Noida201306 India

ISBN: (纸本)9798350306118

computing may be a profoundly examined subject within the technological and financial world, and numerous huge players in the software industry are working for the improvement of computing services. With the help of a literature review, this work has identified that the classification of cloud computing (CC) does not specify how to classify CC based on industry-driven professional articles, as most of this study has been based on academic distributions. This may limit the ability of the research study to provide a consolidated view of the most current advances in this topic. CC has recently captured the attention of scholars, financial professionals, and specialists. Many of these experts have proposed a variety of applications based on various cloud-based techniques, frameworks, and essentials, which have led to different interpretations, specifications, deployment models, and service models. Therefore, a complete characterization and classification of CC are needed to address the above issue. The ultimate purpose of this research is to classify CC in the literature, including the set of security concerns, history, concepts, technologies, and challenges. © 2023 IEEE.

关键词： Cloud security

来源：评论

学校读者我要写书评

暂无评论

Digital Guardians: Exploring Video Analytics in Autonomous Classroom Surveillance Systems

Digital Guardians: Exploring Video Analytics in Autonomous C...

引用

Machine Learning and Autonomous Systems (ICMLAS), International Conference on

作者： K Sreekar G Jeyakumar Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

The growing prevalence of intelligent surveillance systems has expedited progress in video analytics, particularly in learning environments. This survey article analyzes various methods for assessing student behavior and extracting features from classroom videos, with a focus on identifying test malpractices. We look at many existing systems that use techniques like facial identification, tracking, gesture recognition, and engagement analysis to monitor student activities. Here we shed light on the research needs by showing the benefits and limitations of several strategies that involve coping with occlusions, variable lighting, and small face sections in video frames. Our goal is to develop a strong system that uses live video feeds to detect test malpractices in a better and accurate manner while being efficient.

关键词： Surveys Surveillance Visual analytics Face recognition Lighting Gesture recognition Machine learning Feature extraction Security Feeds

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 << < 486 487 488 489 490 491 492 493 494 495 > >>

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：