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

88,320 篇 会议
38,324 篇 期刊文献
1,302 册 图书

馆藏范围

127,946 篇 电子文献
3 种 纸本馆藏

日期分布

学科分类号

72,374 篇 工学
- 45,726 篇 计算机科学与技术...
- 36,731 篇 软件工程
- 18,487 篇 信息与通信工程
- 11,999 篇 控制科学与工程
- 11,819 篇 电气工程
- 11,519 篇 电子科学与技术（可...
- 8,280 篇 生物工程
- 7,017 篇 生物医学工程（可授...
- 6,705 篇 光学工程
- 5,033 篇 机械工程
- 4,620 篇 化学工程与技术
- 4,475 篇 仪器科学与技术
- 4,368 篇 材料科学与工程（可...
- 4,334 篇 动力工程及工程热...
- 3,190 篇 网络空间安全
- 2,941 篇 安全科学与工程
43,194 篇 理学
- 19,293 篇 数学
- 16,640 篇 物理学
- 9,502 篇 生物学
- 6,340 篇 统计学（可授理学、...
- 5,177 篇 化学
- 4,677 篇 系统科学
17,504 篇 管理学
- 11,009 篇 管理科学与工程(可...
- 7,253 篇 图书情报与档案管...
- 5,347 篇 工商管理
7,083 篇 医学
- 5,864 篇 临床医学
- 5,272 篇 基础医学(可授医学...
- 3,276 篇 药学(可授医学、理...
- 3,003 篇 公共卫生与预防医...
3,449 篇 法学
- 2,824 篇 社会学
2,213 篇 经济学
1,843 篇 农学
1,142 篇 教育学
550 篇 文学
279 篇 军事学
122 篇 艺术学
14 篇 哲学
8 篇 历史学

主题

3,790 篇 accuracy
3,041 篇 deep learning
2,895 篇 feature extracti...
2,827 篇 computer science
2,702 篇 machine learning
2,649 篇 computational mo...
2,270 篇 training
1,938 篇 real-time system...
1,851 篇 internet of thin...
1,830 篇 support vector m...
1,766 篇 convolutional ne...
1,756 篇 predictive model...
1,599 篇 artificial intel...
1,441 篇 optimization
1,398 篇 neural networks
1,345 篇 wireless sensor ...
1,253 篇 data mining
1,229 篇 security
1,218 篇 bandwidth
1,213 篇 computer archite...

机构

1,093 篇 cavendish labora...
1,024 篇 department of ph...
971 篇 physikalisches i...
961 篇 oliver lodge lab...
768 篇 university of ch...
645 篇 department of el...
639 篇 chitkara univers...
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...
504 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 beiter a.
233 篇 blake t.
232 篇 j. strandberg
232 篇 d. calvet
231 篇 s. chen
224 篇 bellee v.
223 篇 amato s.
222 篇 betancourt c.
221 篇 boettcher t.
220 篇 borsato m.
219 篇 brundu d.
219 篇 bowcock t.j.v.
217 篇 bencivenni g.

语言

110,696 篇 英文
15,910 篇 其他
1,439 篇 中文
119 篇 日文
24 篇 法文
23 篇 德文
19 篇 斯洛文尼亚文
8 篇 朝鲜文
6 篇 土耳其文
4 篇 阿拉伯文
4 篇 荷兰文
3 篇 俄文
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 127946 条记录，以下是4521-4530 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：

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

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

Data Transformation, Modelling and Prediction of Customer Churn using Deep Learning 14

Data Transformation, Modelling and Prediction of Customer Ch...

引用

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

作者： Menaka, S. Ram, B. Raghu Gowtham, N.V.S. Reddy, G.V. Madhu SRM Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350335095

Client prediction of churn is a difficult field of study that adds to client retention strategies. In a saturated and competitive market, telecommunications companies must rely on a viable churn customers prediction model to retain consumers. Previous research has focused on predicting customer attrition in the present moment or next month, when telecom businesses have not got enough time to create and implement churn control solutions. The predictive performance of present machine learning algorithms, which are frequently used by churn communities, appears to be at a stalemate, owing in part to the algorithms' weak feature extraction capacity. As a result, this research proposes a unique technique, a mix of neural networks with self- attention augmentation, to increase the efficiency of features filtering and feature extraction, hence enhancing model prediction performance. This study is being undertaken in the context of forecasting customer churn (CCP) in the telecommunications industry (TCI), wherein customer attrition is a typical occurrence. For the CCP problem, we developed a unique solution that combines data transformation approaches with machine learning models. We ran our tests on publicly accessible TCI datasets and evaluated performance using widely used assessment metrics (e.g., AUC, accuracy, recall, and F-measure). In this work, we used extensive comparisons to verify the impact of modification strategies. © 2023 IEEE.

关键词： Telecommunication industry

来源：评论

学校读者我要写书评

暂无评论

Convergence of Geo-IoT with Advanced Technologies

Convergence of Geo-IoT with Advanced Technologies

引用

2023 International Conference on Disruptive Technologies, ICDT 2023

作者： Sinha, Monalisha Shalini Thejaswini, M. Indian Institute of Information Technology Department of Computer Science and Engineering Bhagalpur India

ISBN: (纸本)9798350323887

IoT is an emerging digital technology where every physical object is connected to one another via the internet. IoT devices embedded with GPS sensors are called Geo-IoT systems where spatial data is the most prominent requirement in developing any IoT services and applications. Geo-IoT data can be used in various IoT applications for optimizing routes, tracking assets, real-time traffic notification, auto-driving, precision agriculture, anti-theft prevention, etc. This paper provides a review of the convergence of Geo-IoT with advanced technologies such as artificial intelligence, machine learning, and blockchain technology. This paper mainly discusses the current status and applicability of artificial intelligence and machine learning methods in solving and computing location-based IoT data for developing new advanced Geo-IoT applications, routing protocols, and security issues. © 2023 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Breast Cancer Detection and comparative analysis of Convolutional Neural Networks and VGG-16 3

Breast Cancer Detection and comparative analysis of Convolut...

引用

3rd IEEE International Conference on Intelligent Technologies, CONIT 2023

作者： Maniraj, S.P. Gupta, Ayush Mullamuri, Venkata Yaswanth Soumya, Prateek SRM Institute of Science and Technology Department of Computer Science Engineering Chennai India

ISBN: (纸本)9798350338607

Most common machine learning algorithms were designed to tackle particular problems in seclusion. Based on the business requirements, a machine learning algorithm was employed for a particular task and these algorithms were applied to train models separately on specific feature sets. Most of the machine learning models are trained on the assumption that the test and training sets have similar features while sharing the same underlying distributions. Convolutional Neural Networks (CNNs) have demonstrated remarkable potential for breast cancer detection using histopathology images. Moving forward with the latest research, we present VGG-16 architecture for breast cancer detection, which involves the use of pooling and convolutional layers to extract high-level accuracy from histopathology images. The proposed network consists of sixteen layers, each of which performs convolutional operations on the image to detect local features and pooling operations with the aim of simplifying the feature maps' dimensionality. The test results illustrate that the VGG-16 architecture secures superior classification accuracy when compared with the previous cutting-edge models. © 2023 IEEE.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Implementing End to End Encryption to Communication Apps 7

Implementing End to End Encryption to Communication Apps

引用

7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Nalini, N. Harini, B. Nitte Meenakshi Institute of Technology Department of Computer Science & Engineering Bangalore India

ISBN: (纸本)9798350341485

This research study intends to continuously assess the security of cloud models against three types of passive attackers and one type of aggressive adversary. This study has demonstrated how some of the systems' security breaches result from the threat models and what steps are frequently taken to ensure these systems' confidentiality. This study also examines the most popular items on the market and demonstrate the degree of security. Online Social Networking (OSN) services allow users to publish "posts"that contain personal information, media, and news items. On OSN, users can create groups and send messages to one another in private conversations. A group of people can communicate privately with one another. Online discussion is another name for this. These show how these systems are open to inference attacks because of their unencrypted metadata and access patterns. And last, generic design principles for safely developing such systems. This research study defines and introduces the Virgil end-to-end encryption method, which makes use of a symmetric AES key encryption mechanism. There is now a fully functional human messaging service as a result. Instead of relying on outside programmers with questionable or undefined security standards, we created our prototype from the ground up in Java. © 2023 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Automatic Number Plate Recognition System Using Deep Learning YOLOv5 Algorithm

Automatic Number Plate Recognition System Using Deep Learnin...

引用

2023 International Conference on System, Computation, Automation and Networking, ICSCAN 2023

作者： Varalakshmi, I. Santhoshi, M. Krisha Swetha, S. Manakula Vinayagar Institute of Technology Department of Computer Science and Engineering Puducherry India

ISBN: (纸本)9798350315127

A computer vision system called Automatic Number Plate Recognition (ANPR) automates the process of reading licence plates from moving objects. Because to its capacity for precise and effective object recognition, deep learning-based object detection algorithms like YOLO (You Only Look Once) have recently demonstrated promising results in ANPR systems. This study suggests a YOLOv5 object detection model-based architecture for an ANPR system. The suggested architecture consists of a preprocessing stage for image enhancement, a YOLOv5 detector for licence plate detection, post-processing methods like NMS to fine-tune the detection results, an Optical Character Recognition (OCR) algorithm to extract characters from the licence plate, and a decoding stage to ascertain the actual plate number. Real-world datasets are used to assess the proposed design. and displays encouraging accuracy and productivity outcomes. The potential uses for the proposed ANPR system include traffic monitoring, parking management, and law enforcement. © 2023 IEEE.

关键词： Optical character recognition

来源：评论

学校读者我要写书评

暂无评论

Automated Recognition of Underwater Objects using Deep Learning 7

Automated Recognition of Underwater Objects using Deep Learn...

引用

7th International Conference on Trends in Electronics and informatics, ICOEI 2023

作者： Raavi, Sowmya Chandu, Phani Babu SudalaiMuthu, T. Hindustan Institute of Technology and Science Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397284

The underwater object detection is a difficult task due to the unclear visibility and lack of objects underwater in kovalam, it was expected to have visibility up to three to five meters but it is very complicated to detect deeper/underwater objects like shoals of anchovy and silver moony, Bluefin trevally, puffer fish, box fish, etc., The existing method focuses on identifying a single object underwater and have low accuracy (78%) to detect multiple objects in a single instance. The proposed solution intends to improve the accuracy of identifying objects underwater. The proposed work can be used in submarines, military purposes, and archeology to identify objects effectively. The proposed system employs novel techniques for precise object detection and techniques like YOLO and SSD along with precise object detection methods and algorithms like Convolutional Neural Networks (CNN). These artificial intelligence algorithms allow to detect every object in an image by the area it takes up in a highlighted rectangular box, identify every object, and tag every object. © 2023 IEEE.

关键词： Object detection

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

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

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 << < 449 450 451 452 453 454 455 456 457 458 > >>

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：