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

5,899 篇 会议
2,539 篇 期刊文献
62 册 图书

馆藏范围

8,500 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,831 篇 工学
- 3,684 篇 计算机科学与技术...
- 3,012 篇 软件工程
- 1,264 篇 信息与通信工程
- 784 篇 控制科学与工程
- 643 篇 电气工程
- 569 篇 生物工程
- 513 篇 生物医学工程（可授...
- 499 篇 电子科学与技术（可...
- 374 篇 光学工程
- 361 篇 网络空间安全
- 289 篇 动力工程及工程热...
- 275 篇 化学工程与技术
- 269 篇 机械工程
- 259 篇 仪器科学与技术
- 255 篇 安全科学与工程
3,048 篇 理学
- 1,603 篇 数学
- 854 篇 物理学
- 678 篇 生物学
- 575 篇 统计学（可授理学、...
- 310 篇 系统科学
- 309 篇 化学
- 271 篇 地球物理学
1,496 篇 管理学
- 814 篇 管理科学与工程(可...
- 732 篇 图书情报与档案管...
- 423 篇 工商管理
584 篇 医学
- 458 篇 临床医学
- 433 篇 基础医学(可授医学...
- 315 篇 公共卫生与预防医...
- 254 篇 药学(可授医学、理...
304 篇 法学
- 253 篇 社会学
171 篇 经济学
163 篇 农学
93 篇 教育学
45 篇 文学
18 篇 军事学
8 篇 艺术学
2 篇 哲学
1 篇 历史学

主题

404 篇 accuracy
309 篇 deep learning
268 篇 machine learning
246 篇 feature extracti...
234 篇 real-time system...
230 篇 computational mo...
202 篇 support vector m...
201 篇 internet of thin...
190 篇 predictive model...
164 篇 computer science
160 篇 convolutional ne...
142 篇 data mining
138 篇 optimization
136 篇 training
134 篇 application soft...
124 篇 galaxies
118 篇 security
113 篇 artificial intel...
109 篇 image segmentati...
107 篇 neural networks

机构

267 篇 department of ph...
262 篇 fermi national a...
260 篇 madrid
227 篇 department of ph...
202 篇 kavli institute ...
185 篇 department of ph...
184 篇 campus uab carre...
172 篇 school of mathem...
168 篇 george p. and cy...
159 篇 school of physic...
153 篇 department of ph...
152 篇 department of ph...
150 篇 departamento de ...
147 篇 sorbonne univers...
140 篇 institució catal...
139 篇 max planck insti...
139 篇 slac national ac...
134 篇 computer science...
134 篇 kavli institute ...
121 篇 instituto de fis...

作者

258 篇 miquel r.
249 篇 tarle g.
242 篇 smith m.
238 篇 sanchez e.
237 篇 gruendl r.a.
194 篇 carretero j.
190 篇 gruen d.
183 篇 garcía-bellido j...
179 篇 flaugher b.
171 篇 gschwend j.
164 篇 doel p.
159 篇 diehl h.t.
159 篇 james d.j.
158 篇 kuropatkin n.
145 篇 brooks d.
144 篇 suchyta e.
140 篇 da costa l.n.
139 篇 marshall j.l.
138 篇 carnero rosell a...
136 篇 aguena m.

语言

7,037 篇 英文
1,436 篇 其他
47 篇 中文
3 篇 法文
2 篇 西班牙文
1 篇 阿拉伯文
1 篇 德文
1 篇 意大利文
1 篇 俄文
1 篇 斯洛文尼亚文

检索条件"机构=Department of Computer Science and Computer Applications"

共 8500 条记录，以下是731-740 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：

Utilizing Machine Learning to Aid in Type 2 Diabetes Diagnosis 4

Utilizing Machine Learning to Aid in Type 2 Diabetes Diagnos...

引用

4th IEEE International Conference on Applied Electromagnetics, Signal Processing, and Communication, AESPC 2024

作者： Pattnayak, Parthasarathi Mishra, Debaswapna Patnaik, Sanghamitra Mohanty, Arpeeta School of Computer Applications KIIT Deemed to Be University Bhubaneswar India OUAT Department of Computer Science and Application Bhubaneswar India School of Law KIIT Deemed to Be University Bhubaneswar India School of Computer Engineering KIIT Deemed to Be University Bhubaneswar India

ISBN: (纸本)9798331528171

High blood glucose levels are a defining characteristic of diabetes, with type 2 diabetes being the most prevalent form. Early detection and treatment can prevent or delay complications. To precisely anticipate type 2 diabetes risk, we applied machine learning techniques to identify unidentified correlations with a person's health condition. In order to find potential nonlinear correlations between the beginning of type 2 diabetes with an ensemble of health factors, this research used a binary classifier that was trained from scratch. Three datasets - MIMIC-III, MIMIC-IV, and NHANES - were used. The equal number of people who had or did not have type 2 diabetes have been included in one data set that was created by combining the two sets of data. Reliability was the key metric, given the balanced dataset. The model achieved ROC AUC score of 0.934 with accuracy ratings up to 86%, which were positive results of this investigation. To increase the model's dependability, more research is required to take into account multiple readings taken throughout period for an identical person. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Enhancing Productivity and User Experience with Advanced Notepad: A Comprehensive Study 10

Enhancing Productivity and User Experience with Advanced Not...

引用

17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Solanki, Chetna Bana, Garima Singh, Royal Goyal, Mayank Kumar Sharan, Bhagwati Gupta, Raj School of Engineering and Technology Sharda University Department of Computer Science and Applications Greater Noida India School of Engineering and Sciences Srm University-AP Department of Computer Science and Engineering Amaravati India

ISBN: (纸本)9789380544472

The current work outlines the creation of a system to facilitate collaborative software design. Based on the observation of system use during real-world design sessions, an iterative development strategy has been employed. As a result, we can fix interface flaws and gain additional knowledge about collaborative design. The proposed work is based on developing an advanced Notepad using Python and Tkinter Library to enhance productivity and user experience. It will provide the user with multiple themes and Fonts. The work is experimented using Visual Studio Code. The outcomes provide better quality of user experience. Additionally, we observe how conceptions change over time, frequently resulting in quick revisions that change the structure. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

An Automated Machine Learning NLP Model for Enhancing the Translation of English Causative Sentences into Malayalam Language

An Automated Machine Learning NLP Model for Enhancing the Tr...

引用

2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent Systems, AICERA/ICIS 2023

作者： Tom, Rony Mathew, Juby Amal Jyothi College of Engineering Department of Computer Applications Kerala Kanjirappally India Amal Jyothi College of Engineering Department of Computer Science & Engineering Kerala Kanjirappally India

ISBN: (纸本)9798350303452

This research paper introduces an innovative Neural Machine Translation (NMT) model designed to accurately translate causative English sentences into Malayalam. The study comprehensively explores the various forms of causative sentences utilized in both English and Malayalam, focusing on syntactic and semantic differences. Additionally, it delves into the limitations of current translation models such as Google Translator in accurately translating causative constructs. To address these challenges and enhance translation accuracy, a collaborative effort with professional linguists in both languages led to the creation of a rich dataset. The dataset comprises a diverse collection of causative sentences, covering tense variations, singular and plural forms, noun and verb classes, as well as sentence forms involving non-human and animate-human subjects. This model integrates essential components including tokenization, Part of Speech (POS) tagging, tense identification, suffix identification and addition, and sentence reordering for improved translation. Comparative evaluations between the Google Translator and the newly developed system were conducted based on translation accuracy and fluency. The evaluation revealed that the novel NMT model consistently outperforms existing translation systems, demonstrating superior translation results. The findings underscore the effectiveness and potential of the proposed NMT model in advancing causal English to Malayalam translation, offering valuable insights for the improvement of machine translation systems. © 2023 IEEE.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

An Efficient Secure Cloud Image Deduplication with Weighted Min-Hash Algorithm 1

引用

1st International Conference on Expert Clouds and applications, ICOECA 2023

作者： Dhivya, R. Shanmugapriya, N. Department of Computer Science Dr. SNS Rajalakshmi College of Arts and Science Coimbatore641049 India Department of Computer Applications Dr. SNS Rajalakshmi College of Arts and Science Coimbatore641049 India

ISBN: (数字)9789819917457

ISBN: (纸本)9789819917440

Cloud storage services have emerged as a competitive alternative to other methods of data storage, but its operators must balance privacy with optimization. Clients would want to utilize end-to-end data encryption to protect data security;however, effective encryption nullifies the value of all established storage-optimization methods like data deduplication. To save cost and storage space, image deduplication in cloud computing is proposed. To protect the confidentiality of the image, the notion of a hybrid secure approved deduplication algorithm with a weighted min-hash pre-processing method is presented in the paper. The image will be encrypted or decrypted in the deduplication system using a weighed min-hash encryption key that is produced by computing the hash value of the image content. The ciphertext used to verify the duplicate image copy will be produced by identical image copies in the same way. This system has undergone security analysis to ensure its safety. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Security of data

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Algorithmic Trading Based on News and Events Strategies 7th

Deep Learning-Based Algorithmic Trading Based on News and Ev...

引用

7th International Conference on Soft Computing: Theories and applications, SoCTA 2023

作者： Kayathri, V. Prabakaran, P. Department of Computer Applications School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Pallavaram Chennai600 117 India

ISBN: (纸本)9789819720309

Successful stock market investors should consider these trends. This article defines price effect, optimal execution, and placement through the lens of algorithmic trading and strategies based on news and events. By using feedbacks controlled to include consideration of a stop-loss order, algorithmic trading allows traders and investors at large to liquidate or construct big securities positions in a fully automated manner, thus generalising the existing stock trading results. Trading decisions made by the AI agent could affect the asset price. We see this as a marketplace where people are bartering and swapping goods. Creating a new market is the driving force behind our research into generative models. This news sentiment does a good job of describing stocks, and AI systems that read the news and quantify them react to factors that affect prices far more quickly than humans do. All three of the stock market's underpinnings—price, volume, and volatility—respond strongly to news events. Sentiment analysis is a method for gauging the overall tone of a news piece and classifying it as optimistic, pessimistic, or neutral. The simulation is conducted in python to test the effectiveness of the model in trading in an automated manner for stocks. The results show that the proposed sentimental analysis for stock trading achieves higher rate of accuracy and precision than the other methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Financial markets

来源：评论

学校读者我要写书评

暂无评论

Face Mask detection using Mask R-CNN to control the spread of Covid-19

Face Mask detection using Mask R-CNN to control the spread o...

引用

2023 IEEE International Conference on Recent Trends in Electronics and Communication, ICRTEC 2023

作者： Mohan, V.S. Abhay Gowda, G. Nair, Rekha R Kishore, S. Babu, Tina School of Engineering Dayananda Sagar University Department of Computer Applications Banglore India School of Engineering Dayananda Sagar University Department of Computer Science and Engineering Banglore India

ISBN: (纸本)9798350396195

Business executives are developing cutting-edge digital solutions as the virus outbreak spreads. A face mask detection system is one of them, and it can be used to spot people wearing them. Face mask identification software and applications have already been released by a few businesses, and others have promised to do the same for the service. The proposed work examines face mask detection accuracy using CNN networks. Mask wear is now required in many developed and developing countries worldwide when leaving the house or entering public spaces. It will be difficult to maintain touchless access control in buildings while recognising faces wearing masks on any surveillance systems. Masks covering faces has made face detection algorithms and performance difficult. The proposed work detect face mask labeled no mask or mask with detection accuracy. The work train the system to click images of a face and provide labeled data. The work is classified using Convolution Neural Network (CNN), a Deep learning technique, to classify the input image with the help of the classification algorithm MobileNetV2. The trained system shows whether a person in the video frame is wearing a mask or not. © 2023 IEEE.

关键词： Access control

来源：评论

学校读者我要写书评

暂无评论

Secure Communication over IoT Networks using Mutual Authentication

Secure Communication over IoT Networks using Mutual Authenti...

引用

2024 International Conference on Computational Intelligence and Computing applications, ICCICA 2024

作者： Verma, Dinesh Chander Chopra, Amit Kanika Kaushik, Vinita Kaur, Jaspreet Panipat Institute Of Engineering & Technology Department Of Computer Applications Panipat India Maharaja Agrasen University Department Of Computer Science & Engineering H.P Baddi India Thompson Rivers University KamloopsBC Canada

ISBN: (纸本)9798350306446

Internet of Things (IoT) network transmit the data in an open environment and it can be intercepted by unauthorized users. Different sensors share their data with each other without authentication and it becomes a major security concern. Data privacy and integrity are other security issues. In this paper, a secure communication using mutual authentication model will be introduced to secure the transmisssion over IoT networks. It will isolate the communication between filed sensors and gateways as well as it will also protect the data exchange between gateways and server. Its performance will be analyzed using. Long Range Low powered technology (LoRa) under the constraints of intruder density that varies from 5 to 25 nodes with the legitimate sensors density (100-600) © 2024 IEEE.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Smart Intelligence-Driven Deep Learning Framework for Reliable Detection and Accurate Classification of Skin Cancer Diseases 3

Smart Intelligence-Driven Deep Learning Framework for Reliab...

引用

3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Rathish Babu, T.K.S. Chandramohan, S. Be, Hajira Niroshini Infantia, H. Srm Institute of Science and Technology Department of Computer Science Engineering Ramapuram Chennai89 India Sri Chandrasekarendra Saraswathi Viswa Maha Vidyalaya Department of Computer Science Engineering Chennai India Karpaga Vinayaga College of Engineering and Technology Department of Computer Applications Maduranthakam Taluk India St. Joseph's Institute of Technology Department of Information Technology OMR Chennai600119 India

ISBN: (纸本)9798331509675

The interest in skin cancer detection is growing remarkably because of the prevalence of this health condition worldwide. It improves the chances of survival and enhances general treatment outcomes when diagnosis has been done early. Most the traditional methods for skin lesion detection involve visual inspection performed by dermatologists;hence, it is time-consuming and, to some extent, subjective. Therefore, with the rise of deep learning-Artificial Intelligence, auto-detection of skin cancer has gained a foothold in improving diagnostic accuracy, hence treatment outcomes. The presented paper proposes a GAN-based approach for skin cancer detection by deep learning analysis of dermoscopic images, classifying them as malignant and benign. The proposed approach uses the generator and discriminator parts of GAN to obtain an effective discrimination between cancerous and non-cancerous lesions with high precision. The proposed method incorporates the native abilities of GANs for boosting diagnostic precision. GANs consist of two major components: a generator and a discriminator. These two adversaries collaborate with each other in a way to encourage the classification performance of the framework. The generator synthesizes the realistic data representations by augmenting the dataset with various variations of dermoscopic images. This helps not only to compensate for the insufficiency of annotated data but also to make the model generalize more robustly to diverse skin lesion patterns. At the same time, the discriminator learns to distinguish malignant from benign lesions with high accuracy by using the adversarial nature in GAN training. These results clearly indicate the effectiveness of the proposed GAN-based approach over state-of-the-art traditional deep learning models. GAN makes not only the detection system more robust but also reduces its dependency on large annotated datasets. © 2025 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Oil Spill Detection and Understanding Using Deep Learning and Large Language Models

Oil Spill Detection and Understanding Using Deep Learning an...

引用

2024 Abu Dhabi International Petroleum Exhibition and Conference, ADIPEC 2024

作者： Tharayil, Sarafudheen M. Al Qarni, Shouq Al Thubaiti, Leen Al Dossary, Basim Shahada, Marwa Corporate Applications Department Aramco Dhahran Saudi Arabia Department of Mathematics & Computer Science Heriot-Watt University Dubai Campus United Arab Emirates

ISBN: (纸本)9781959025498

The primary objective of this research work is to harness the advanced capabilities of Artificial Intelligence (AI), specifically Deep Learning (DL) and Large Language Models (LLMs), to develop a comprehensive system for detecting and understanding the causes of oil spills. Our approach involves utilizing deep learning algorithms to detect oil spill incidents from images, extracting relevant factors from these images, and feeding these factors into LLMs to determine the causality of the incidents. This research is motivated by the increasing frequency and environmental impact of oil spill events globally, and the lack of existing mechanisms to accurately monitor and explain these incidents. By enabling rapid detection and causality analysis, this system aims to enhance environmental protection efforts and prevent future oil spills through informed decision-making and timely intervention. The methodology of this study involves several critical steps. We began by utilizing an industrial dataset comprising labeled images of oil spills. Initial preprocessing steps included resizing and normalization of the images, followed by extensive data augmentation to enhance the dataset's robustness. We then employed advanced deep learning models, where images are considered as a grid of cells, with bounding boxes. We trained the Convolutional Neural Networks (CNNs) model to identify oil spill incidents by extracting key features from each image. These factors were then fed into a Large Language Model (LLM), to analyze and determine the underlying causes of the oil spills. The study demonstrates the effectiveness of integrating deep learning and LLMs in environmental monitoring and analysis. Our approach achieved a considerable increase in the accuracy of oil spill detection compared to traditional methods. Additionally, we attained a better accuracy rate in identifying contributory factors to oil spills. These results underscore the ecological importance of promptly identifying a

关键词： Oil spills

来源：评论

学校读者我要写书评

暂无评论

Increasing Productivity in Software Development Through the Use of Docker Technology 1

引用

3rd International Conference on Universal Threats in Expert applications and Solutions, UNI-TEAS 2024

作者： Singh, Kamred Udham Kumar, Ankit Kumar, Gaurav Singh, Teekam Kothari, Paras Sheikh, Anisha School of Computing Graphic Era Hill University Dehradun India Department of Computer Engineering and Applications GLA University UP Mathura India Department of Information Technology Guru Ghashi Das University Bilaspur Bilaspur India Department of Computer Science and Engineering Graphic Era Deemed to Be University Dehradun India Department of Computer Applications Geetanjali Institute of Technical Studies Rajasthan Udaipur India

ISBN: (数字)9789819738106

ISBN: (纸本)9789819738090

The Docker technology makes the process of developing software substantially more effective by resolving issues related to deployment and hosting. Through the use of virtualization, it is able to function independently of the underlying hardware infrastructure, and it relies on its own code to carry out the execution of programs. The encapsulation of an application's whole environment together with its source code is at the heart of Docker's methodology. This enables Docker to efficiently eliminate the problems that are associated with having a variety of working environments, but it may also result in the images having a greater file size. "Images" is the term that Docker uses to refer to these bundled environments. Docker was used in this investigation to carry out a variety of tests, which allowed identical code to be executed on a variety of platforms, so permitting extensive comparisons. Software developers made use of Docker's ability to analyze the outcomes, which enabled them to make decisions based on accurate information. This study simplifies the software development and deployment procedures for the development community by providing significant insights into the benefits and considerations of Docker across numerous platforms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Python

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 << < 70 71 72 73 74 75 76 77 78 79 > >>

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：