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

30,446 篇 会议
4,810 篇 期刊文献
239 册 图书

馆藏范围

35,495 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

21,962 篇 工学
- 15,889 篇 计算机科学与技术...
- 13,363 篇 软件工程
- 5,852 篇 信息与通信工程
- 3,466 篇 控制科学与工程
- 2,672 篇 电子科学与技术（可...
- 2,625 篇 电气工程
- 2,373 篇 生物工程
- 1,913 篇 生物医学工程（可授...
- 1,553 篇 光学工程
- 1,354 篇 机械工程
- 1,225 篇 动力工程及工程热...
- 1,208 篇 仪器科学与技术
- 1,017 篇 化学工程与技术
- 874 篇 安全科学与工程
- 743 篇 交通运输工程
11,267 篇 理学
- 6,105 篇 数学
- 3,069 篇 物理学
- 2,601 篇 生物学
- 2,043 篇 统计学（可授理学、...
- 1,327 篇 系统科学
- 1,086 篇 化学
5,695 篇 管理学
- 3,319 篇 管理科学与工程(可...
- 2,659 篇 图书情报与档案管...
- 1,833 篇 工商管理
1,632 篇 医学
- 1,413 篇 临床医学
- 1,320 篇 基础医学(可授医学...
- 864 篇 药学(可授医学、理...
- 693 篇 公共卫生与预防医...
1,051 篇 法学
- 846 篇 社会学
652 篇 经济学
- 652 篇 应用经济学
494 篇 农学
428 篇 教育学
158 篇 文学
79 篇 军事学
39 篇 艺术学
2 篇 哲学

主题

1,140 篇 accuracy
869 篇 computational mo...
862 篇 feature extracti...
740 篇 deep learning
694 篇 training
676 篇 computer science
541 篇 real-time system...
536 篇 machine learning
527 篇 support vector m...
477 篇 predictive model...
420 篇 internet of thin...
375 篇 convolutional ne...
357 篇 data models
348 篇 computer archite...
339 篇 reliability
305 篇 optimization
298 篇 data mining
276 篇 routing
260 篇 wireless sensor ...
249 篇 visualization

机构

83 篇 institut univers...
82 篇 north-west unive...
81 篇 national centre ...
79 篇 infn sezione di ...
77 篇 institute of inf...
76 篇 infn sezione di ...
74 篇 tno technical sc...
66 篇 università di ca...
65 篇 université de st...
63 篇 dept. of informa...
60 篇 nikhef national ...
58 篇 dept. of informa...
58 篇 dept. of compute...
56 篇 dept. of compute...
53 篇 leiden universit...
52 篇 school of automa...
50 篇 dept. of compute...
48 篇 dept. of compute...
46 篇 university würzb...
45 篇 dept. of electri...

作者

85 篇 ferrara g.
85 篇 ardid m.
85 篇 gal t.
85 篇 bozza c.
84 篇 calvo d.
82 篇 chen a.
81 篇 kalekin o.
79 篇 díaz a.f.
78 篇 boumaaza j.
78 篇 coleiro a.
76 篇 gozzini s.r.
68 篇 huang f.
68 篇 dallier r.
62 篇 anguita m.
52 篇 kulikovskiy v.
43 篇 del burgo r.
41 篇 benoit d.m.
41 篇 eddymaoui a.
40 篇 gagliardini s.
40 篇 labalme m.

语言

33,514 篇 英文
1,568 篇 其他
309 篇 中文
56 篇 日文
50 篇 朝鲜文
2 篇 德文
2 篇 斯洛文尼亚文
1 篇 法文
1 篇 葡萄牙文

检索条件"机构=Dept. of Computer Science and Engineering With Data Science"

共 35495 条记录，以下是921-930 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：

Bidirectional Communication System for Deaf-Blind Individuals 8

Bidirectional Communication System for Deaf-Blind Individual...

引用

8th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2024

作者： Saralaya, Sridevi Jijo, Jeevan V. Serrao, Lavisha Andri D'Souza, Flaivin Vaz, Jane Oveita St Joseph Engg. College Dept. of Computer Science & Engineering Mangalore India

ISBN: (纸本)9798350350593

In a world that thrives on connectivity and communication, we often take for granted the power of simple yet profound interactions. For individuals with sensory impairments, particularly the deaf-blind community, these fundamental human connections are often limited, making everyday life a challenge. In response to this challenge, we propose an innovative and transformative project that aims to bridge the communication gap for the deaf-blind community, enabling them to engage in text-based conversations with ease. While advancements in technology have greatly improved communication for many, those who are both deaf and blind remain largely excluded from the digital world. This exclusion hinders their ability to engage in meaningful conversations, access information, and connect with others, leading to social and informational isolation. While existing solutions often focused on either blindness or deafness, this project aimed to provide a holistic communication solution for individuals with both impairments. Through rigorous testing, the bidirectional communication system demonstrated its ability to accurately transcribe speech-to-text, translate text-to-braille, and facilitate seamless interaction between users and hardware peripherals. The project's novel solution for deaf-blind communication brings significant advantages namely cost saving, streamlined labor, efficient space utilization, and energy conservation. The integration of speech-to-text with real-time braille hardware interaction enhances user experience, reducing the need for extensive manual interpretation. © 2024 IEEE.

关键词： Ability testing

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Approach for Parkinson' s disease Prediction through Quantum Computing Techniques 2

Machine Learning Approach for Parkinson' s disease Predictio...

引用

2nd IEEE International Conference on Advances in Information Technology, ICAIT 2024

作者： Arpitha, K. Lohith, H.R. Nemmadi, H.K. Sujan, K. Yashwanth, C.L. Dept. of Computer Science Engineering BGS Institute of Technology Adichunchanagiri University Mandya India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383867

One of the most serious illnesses that may impact the neurological system in humans is dementia, of which Parkinson' s disease is a major subtype. Patients with Parkinson' s disease have significant behavioural changes. The suggested system uses quantum computing and machine learning to build a speech signal-based method for Parkinson' s disease prediction. Four main machine learning methods are used in this prediction: Artificial Neural Networks, KNN, Decision Trees, and Naïve Bayes. Furthermore, different ensemble learning models are used to combine numerous models and improve the accuracy. An industry standard dataset from the UCI Machine Learning Repository is used to assess the model' s performance. Ensemble models have proven to outperform extremely efficient techniques like neural networks in terms of accuracy. A multi-layer perceptron, a very significant machine learning optimization technique, is incorporated into the suggested system. © 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 Athletic Performance:2D Human Pose Estimation Using Deep Neural Networks for Movement Analysis 7

Enhancing Athletic Performance:2D Human Pose Estimation Usin...

引用

7th International Conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Devi, Pothreddypally Jhansi Sumani, Aleshwaram Chandra, Chenna Mukesh Thrisha, Battu Bhanu Vamshi, Arkatala Sai B V Raju Institute of Technology Dept. of Computer Science Engineering Telangana India

ISBN: (纸本)9798350372816

computer vision is a field that is used to build many neural network-based prototypes efficiently. It analyses images and videos effectively and processes them digitally. Human Pose estimation (HPE) is one of the computer vision applications which additionally uses neural networks for prediction. Human pose estimation is used widely in many fields which includes action recognition, fitness, gaming, and motion capture. HPE identifies and locates the key points on the body joints of a person's body. These body points are connected to form a Skeletal Structure. This skeletal representation helps to easily visualize the image in 2-D. Focusing on Sports domain, HPE plays major role in estimating athlete movements. It helps in analyzing the feedback on the posture which allows to make adjustments during training. It also helps viewers to analyse the insights of athlete performance. To achieve the model that contains all these features, requires involvement of few frameworks. OpenPose is utilised for fast processing of videos and can detect the multiple people in one frame. OpenPose has the capability of handling the occulsion. On the Other hand, the model also import the capabilities of HRNet, which is used for analyzing athlete movements and tracks the gestures. After detecting the keypoints on the body joints, these points must be integrated to form 2-D images. To achieve the spatial relationship between the bodypoints Joint Graph Convolutional Neural Networks (JGCN) framework is used. The proposed model is estimated to generate approximately (4- 5)percent more efficiency and accuracy in its output 2-D image compared with the previous models. © 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

Machine Learning based Real Estate Price Prediction 8

Machine Learning based Real Estate Price Prediction

引用

8th International Conference on Inventive Systems and Control, ICISC 202

作者： Mukherjee, Anupam Nambiar, Rtwik Choudhury, Deepjyoti Manipal University Jaipur School of Computer Science and Engineering Dept. of Aiml Jaipur India

ISBN: (纸本)9798350386578

The dynamic nature of real estate markets gives rise to huge challenges for buyers and sellers in accurately predicting property prices. This paper presents a detailed study on real estate price predictions, focusing on using machine learning techniques to forecast property prices effectively. Using a dataset from Bengaluru, as a case study, it explored the intricacies of Real Estate markets and developed a predictive model to estimate the property prices. Our studies consist of data preprocessing, featuring engineering, model selection, and evaluations, giving insights into the factors that affect property prices and the performances of various regression algorithms. After performing multiple experiments, we showcase the efficiency of our approaches in predicting property prices. Existing techniques that have tried to predict house prices have often struggled to deal with nonlinear relationships present among the factors. Recent techniques such as Linear regression, Ridge and Lasso Regression and Support Vector Machines(SVM) have come up short of being perfect when it comes to dealing with computational intensity and these techniques require extensive hyperparameter tuning. However, our predictive model is able to deal with these challenges by leveraging the strengths of Random Forest regression. This is done with high accuracy and the implications for real estate stakeholders are discussed, subsequently. This paper also highlights the various avenues through which the performance of real estate estimation models can be improved in the future. © 2024 IEEE.

关键词： Support vector regression

来源：评论

学校读者我要写书评

暂无评论

DeepStock Forecast: Unveiling Market Movements through Advanced Deep Learning Models 4

DeepStock Forecast: Unveiling Market Movements through Advan...

引用

4th International Conference on Emerging Systems and Intelligent Computing, ESIC 2024

作者： Das, Smruti Rekha Mishra, Debahuti Lenka, Arundhati Shaw, Kailash Gitam Deemed to Be University Dept. Computer Science and Engineering Andhra Pradesh Visakhapatnam India Siksha 'o' Anusandhan Deemed to Be University Odisha Dept. Computer Science and Engineering Odisha India Dept. of Aiml Symbiosis Institute of Technology Pune India

ISBN: (纸本)9798350349856

This study uses deep neural network (DNN) methodologies, including auto encoder, deep belief network (DBN), and backpropagation neural network (BPNN), to predict stock prices over 15 and 30 days. Utilizing BSE Sensex and NSE Sensex datasets with diverse technical indicators, the research highlights DNN's superior training accuracy, measured by minimal mean squared error (MSE). The study's key contribution is applying DNN to predict stock market volatility. While acknowledging the limitation of relying solely on training error, the study incorporates additional measures like RMSE, MAPE, MAE, and ARV during testing. Notably, DNN's MAPE results fall within a narrow range (0.0221 to 0.0255), indicating minimal error deviation. In a comprehensive evaluation across all datasets, DNN consistently outperforms DBN and BPNN in both training and testing performance. © 2024 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

SPEI Based Drought Prediction and Validation Using Machine Learning Algorithm in Bangladesh from 1981 to 2017

SPEI Based Drought Prediction and Validation Using Machine L...

引用

2024 IEEE International Conference on Signal Processing, Information, Communication and Systems, SPICSCON 2024

作者： Mashuq, Md Farhan Akther, Juthy Das, Krishna Dept. of Computer Science and Engineering International University of Business Agriculture and Technology Dhaka Bangladesh

ISBN: (纸本)9798331510213

A natural event known as a drought is defined by a long period of insufficient rainfall and limited access to water supplies, which means there isn't enough water for many uses, including agriculture, industry and domestic consumption. The Standardized Precipitation Evapotranspiration Index (SPEI) is a frequently utilized indicator in drought monitoring. In this work, from 1981 to 2017, temporal variation at Ishwardi upazila was used to evaluate and analyze the SPEI's performance at 1, 3, 6 and 12-month timeframes. An analysis is carried out to see how well machine learning approach such as Support Vector Machine (SVM), Random-Forest (RF), Decision-Tree (DT), Extreme Gradient Boosting (XGB) and K-Nearest Neighbors (KNN) work in forecasting drought conditions. The prediction outcomes of all five techniques were assessed using four performance measures: the Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE) and Nash-Sutcliffe Model Efficiency Coefficient (NSE). The proposed methods provided good results and can serve as a quick decision-making tool for water management. © 2024 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Multi-Trajectory Drone Surveillance: Amplifying Monitoring Capabilities in Disaster Management

Multi-Trajectory Drone Surveillance: Amplifying Monitoring C...

引用

2024 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2024

作者： Mourya, Gojja Sree Jami, Abhinav Ajith, Abhinav Seikh, Ayan Habib Kumar, J. Sathish Motilal Nehru National Institute of Technology Dept. of Computer Science and Engineering Allahabad India

ISBN: (纸本)9798350348460

In the disaster-affected area, whether it's a search and rescue operation, mock drill, managing food distribution, issuing warnings or anything else, the key to successfully carrying out these activities is preparation. To ensure that plans are accurate, one needs to know what actually happened in the disaster-affected area and for this purpose thoroughly and quickly the entire area need to be studied. To address this issue, we use UAV or drone navigation autonomously in required trajectories. By using UAVs you can cover surveillance across the vast acres of land quickly and know what happened and plan rescue operations accordingly. In this paper, we presented our work on moving the drones in multiple trajectories and swarm, thus amplifying surveillance capabilities. Each trajectory is maneuvered autonomously and a corresponding trajectory-algorithm running at the back end is presented along with the simulation results. © 2024 IEEE.

关键词： Disaster management Drones Multi-Agent Systems Surveillance Swarm Trajectories Unmanned Aerial Vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Enhancing Decentralized Finance for Scalability, Interoperability, and User Experience 8

Enhancing Decentralized Finance for Scalability, Interoperab...

引用

8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Nalini, N. Rao, Vishak Rao, Karthik Shobha, P. Nitte Meenakshi Institute of Technology Dept. of Computer Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798331505462

This research explores Decentralized Finance (DeFi) through the lens of enhanced applications, introducing the concept of Decentralized Finance Enhanced (DeFine). It examines the transformative potential of DeFi, analyzing its evolution and the innovative solutions driving its progress. The objective is to investigate how DeFine addresses scalability, interoperability, security, and user experience challenges in the DeFi ecosystem. Through case studies and analysis, this proposed work provides insights into the implications, opportunities, and risks associated with the adoption and maturation of DeFi enhancements. © 2024 IEEE.

关键词： Decentralized finance

来源：评论

学校读者我要写书评

暂无评论

AI Sentries: Evaluating Machine Learning Models for Superior Phishing Email Detection 8

AI Sentries: Evaluating Machine Learning Models for Superior...

引用

8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Sahit, S. Vaishnavi, S. Vaibhav Reddy, A. Chaitra, M. Bnm Institute of Technology Affiliated to Vtu Dept. of Computer Science and Engineering Bengaluru India

ISBN: (数字)9798331505462

ISBN: (纸本)9798331505462

Email Phishing Detection focuses on studying how to process emails and spot threats using machine learning and advanced natural language processing. It aims to shield people and businesses from real email misuse. This study tries to fix some problems that earlier research had faced. It does this by making better machine learning detectors to spot fake emails. These detectors use different data sets and look at how to pull out key info. They also try to adapt to new tricks scammers use. The solutions put forward use new methods. These include tweaking features, combining different learning models, and using deep learning to boost accuracy while checking emails in real-time. The study also looks at how to use natural language processing (NLP) to understand what emails mean. This helps catch more fake emails. By looking at both how emails are written and what they mean, the system can spot scams more. This cuts down on false alarms and makes the system more reliable. This well-rounded approach not pushes the boundaries of spotting fake emails but also creates a strong system that can change as cyber threats do. This ensures protection that lasts and can bounce back from attacks. © 2024 IEEE.

关键词： Phishing

来源：评论

学校读者我要写书评

暂无评论

Distributionally Robust Clustered Federated Learning: A Case Study in Healthcare 63

Distributionally Robust Clustered Federated Learning: A Case...

引用

63rd IEEE Conference on Decision and Control, CDC 2024

作者： Konti, Xenia Riess, Hans Giannopoulos, Manos Shen, Yi Pencina, Michael J. Economou-Zavlanos, Nicoleta J Zavlanos, Michael M. Duke University School of Medicine United States Duke University Dept. of Computer Science United States Duke University Dept. of Electrical and Computer Engineering United States Duke University Dept. of Mechanical Engineering & Materials Science United States

ISBN: (纸本)9798350316339

In this paper, we address the challenge of heterogeneous data distributions in cross-silo federated learning by introducing a novel algorithm, which we term Cross-silo Robust Clustered Federated Learning (CS-RCFL). Our approach leverages the Wasserstein distance to construct ambiguity sets around each client's empirical distribution that capture possible distribution shifts in the local data, enabling evaluation of worst-case model performance. We then propose a model-agnostic integer fractional program to determine the optimal distributionally robust clustering of clients into coalitions so that possible biases in the local models caused by statistically heterogeneous client datasets are avoided, and analyze our method for linear and logistic regression models. Finally, we discuss a federated learning protocol that ensures the privacy of client distributions, a critical consideration, for instance, when clients are healthcare institutions. We evaluate our algorithm on synthetic and real-world healthcare data. © 2024 IEEE.

关键词： Federated learning

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 << < 89 90 91 92 93 94 95 96 97 98 > >>

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：