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

22,150 篇 会议
3,542 篇 期刊文献
209 册 图书

馆藏范围

25,901 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

15,856 篇 工学
- 11,170 篇 计算机科学与技术...
- 9,359 篇 软件工程
- 4,303 篇 信息与通信工程
- 2,516 篇 控制科学与工程
- 2,157 篇 电子科学与技术（可...
- 2,132 篇 电气工程
- 1,540 篇 生物工程
- 1,323 篇 生物医学工程（可授...
- 1,142 篇 光学工程
- 1,028 篇 机械工程
- 882 篇 仪器科学与技术
- 834 篇 动力工程及工程热...
- 744 篇 化学工程与技术
- 626 篇 安全科学与工程
- 525 篇 交通运输工程
- 469 篇 材料科学与工程（可...
- 446 篇 建筑学
8,234 篇 理学
- 4,525 篇 数学
- 2,421 篇 物理学
- 1,707 篇 生物学
- 1,385 篇 统计学（可授理学、...
- 917 篇 系统科学
- 759 篇 化学
4,001 篇 管理学
- 2,399 篇 管理科学与工程(可...
- 1,836 篇 图书情报与档案管...
- 1,259 篇 工商管理
1,077 篇 医学
- 952 篇 临床医学
- 887 篇 基础医学(可授医学...
- 574 篇 药学(可授医学、理...
714 篇 法学
- 562 篇 社会学
444 篇 经济学
348 篇 教育学
320 篇 农学
110 篇 文学
72 篇 军事学
26 篇 艺术学
4 篇 哲学
3 篇 历史学

主题

723 篇 accuracy
540 篇 feature extracti...
501 篇 deep learning
491 篇 computational mo...
386 篇 training
383 篇 support vector m...
365 篇 computer science
323 篇 internet of thin...
299 篇 real-time system...
288 篇 machine learning
282 篇 computer archite...
247 篇 predictive model...
227 篇 reliability
222 篇 routing
221 篇 convolutional ne...
220 篇 optimization
209 篇 data mining
207 篇 neural networks
200 篇 throughput
195 篇 image segmentati...

机构

85 篇 dept. of compute...
84 篇 institut univers...
84 篇 université de st...
83 篇 north-west unive...
83 篇 tno technical sc...
82 篇 infn sezione di ...
81 篇 national centre ...
80 篇 nikhef national ...
76 篇 infn sezione di ...
67 篇 university würzb...
66 篇 università di ca...
53 篇 leiden universit...
51 篇 dept. of compute...
50 篇 school of automa...
50 篇 university of jo...
48 篇 university moham...
44 篇 university moham...
43 篇 in2p3 lpc campus...
42 篇 infn lnf via enr...
42 篇 university of gr...

作者

95 篇 ardid m.
93 篇 ferrara g.
92 篇 kalekin o.
92 篇 díaz a.f.
91 篇 boumaaza j.
90 篇 coleiro a.
89 篇 calvo d.
83 篇 gal t.
82 篇 bozza c.
80 篇 chen a.
78 篇 gozzini s.r.
76 篇 huang f.
75 篇 dallier r.
72 篇 anguita m.
61 篇 enzenhöfer a.
60 篇 kulikovskiy v.
60 篇 boettcher m.
58 篇 celli s.
53 篇 aly z.
52 篇 dornic d.

语言

23,073 篇 英文
2,461 篇 其他
272 篇 中文
75 篇 日文
21 篇 朝鲜文
4 篇 斯洛文尼亚文
1 篇 阿拉伯文
1 篇 德文
1 篇 法文
1 篇 土耳其文

检索条件"机构=Dept. Computer Technology and Computer Graphics"

共 25901 条记录，以下是671-680 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：

Generative AI Models for Virtual Interviewers: Applicability and Performance Comparison

Generative AI Models for Virtual Interviewers: Applicability...

引用

2023 International Conference on Innovation, Communication and Engineering, ICICE 2023

作者： Si, Jongwook Song, Jaeyong Woo, Minsik Kim, Daemin Lee, Yonghwan Kim, Sungyoung Dept. of Computer AI Convergence Engineering Kumoh National Institute of Technology Korea Republic of Dept. of Computer Engineering Kumoh National Institute of Technology Korea Republic of Dept. of Electronic Engineering Kumoh National Institute of Technology Korea Republic of

ISBN: (纸本)9781839539954

Interviewing processes are considered crucial steps in job hunting or college admissions, and effective practice plays a significant role in successfully navigating these stages. Although various platforms have recently emerged for practicing virtual interviews, they often lack the tension and realism of actual interviews due to repetitive and formal content. This study aims to analyze and compare the performance of different generative AI models for creating a diverse set of virtual interviewers. Specifically, we examine the characteristics and applicability of each model, as well as the differences and advantages between them, and evaluate the performance of the generated virtual interviewers. Through this analysis, we aim to propose solutions for enhancing the practicality and efficiency of virtual interviews. © The Institution of Engineering & technology 2023.

关键词： Virtual environments

来源：评论

学校读者我要写书评

暂无评论

OBDTL: Under Water Object Classification Using Transfer Learning 4

OBDTL: Under Water Object Classification Using Transfer Lear...

引用

4th International Conference on computer, Communication, Control and Information technology, C3IT 2024

作者： Roy, Sarthak Ghosh, Partha Goto, Takaaki Sen, Mainak Techno India University Computer Sc. & Engg. Dept. West Bengal Kolkata India Academy of Technology Adisaptagram Dept. of Computer Science & Engg. India Toyo University Dept. of Information Sciences and Arts Saitama Japan

ISBN: (纸本)9798350389128

Underwater object classification is a critical task in domains such as marine research, underwater exploration, maintenance of underwater structures and deep-sea oil industries etc. Accurate detection of underwater objects is a task of vital importance for autonomous underwater vehicles (AUVs). Tasks such as obstacle avoidance and autonomous navigation become easier when underwater obstacles can be recognized. A learningbased, robust object detection model capable of processing images at a high rate is beneficial for real-time object detection. This project focuses on developing a robust underwater object classification system utilizing machine learning techniques to classify objects present in underwater imagery. In this paper, we explore the efficacy of transfer learning using VGG16. VGG16 offers valuable pre-trained weights that encapsulate knowledge about fundamental image features. Here, we have trained a convolutional neural network and a VGG-16 based neural network classifier on three datasets and received 84.89% of accuracy with VGG-16 based classifier using transfer learning. © 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

Stock Market Prediction Using Deep Learning

Stock Market Prediction Using Deep Learning

引用

2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Johnshaida, S.K. Kumar, G. Shiva Vignan's Foundation for Science Technology & Research Deemed to be University Dept. Information Technology & Computer Applications Guntur India

ISBN: (纸本)9798350379525

This project focuses on leveraging One kind of deep learning model is the Long Short-Term Memory (LS TM) networks., to forecast stock prices by analyzing historical data and technical indicators. The methodology involves comprehensive steps such as data collection, preprocessing, feature selection, model selection (including LSTM networks), training, and evaluation taking advantage of performance indicators such as Mean Squared Error (MSE) and Mean Absolute Error (MAE). It utilizes a dataset comprising historical gold stock prices and trading volume to train and test the LSTM model. Furthermore, Naive Bayes, Support Vector Machine (SVM), Linear Regression, and other machine learning algorithms are examined in the study, along with more complex methods like Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN). Results reveal diverse accuracy levels across models, with LSTM demonstrating a tendency to overpredict stock prices. Future endeavors aim to refine model performance, investigate ensemble methods, and integrate additional data sources like economic news and sentiment analysis to bolster prediction accuracy, thereby offering investors and analysts enhanced decision-making tools in the dynamic stock market landscape. © 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

Electricity Generation From Food Waste Using IOT 3

Electricity Generation From Food Waste Using IOT

引用

3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Arunkumar, M. Agalya, S. Bhuvanaeshwari, M. IFET College of Engineering Dept. of Information Technology Villupuram India Surya Group of Institutions Dept. of Computer Science and Engineering Villupuram India

ISBN: (纸本)9798350372120

One inventive solution is to turn food waste into power using the Internet of Things (IoT) to meet the growing need for sustainable energy sources. It turns thermal energy from trash into electricity by utilizing thermoelectric devices and the Seebeck effect. Real-time monitoring and control are made possible with IoT integration. By improving the extraction of energy from liquid or semi-solid waste, this technique reduces waste and promotes a circular energy economy. The system makes use of hardware components such as transformers and voltage regulators. The outcomes of experiments demonstrate its efficacy and possible role in renewable energy. This creative idea, which provides a sustainable route ahead for the production of power from food waste, highlights the importance of IoT in improving waste-to-energy systems. © 2024 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Scaling Compute-Intensive Telehealth Monitoring in IoT-Enabled Smart Spaces: A Personal-Space-State Approach

Scaling Compute-Intensive Telehealth Monitoring in IoT-Enabl...

引用

2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024

作者： Alhassoun, Nailah Venkatasubramanian, Nalini Dept. of Information Technology King Saud University Riyadh Saudi Arabia Dept. of Computer Science University of California Irvine United States

ISBN: (纸本)9798350350548

IoT has created smart spaces that integrate sensory data, processes, objects, and people to enable continuous monitoring that provides knowledge for diverse services. These optimized spaces are essential for many safety and mission-critical monitoring applications, e.g. assisted living and healthcare. In this paper, we address a key challenge in monitoring smartspace at scale, i.e. that of energy expenditure associated with continuous compute-intensive operations. Diverse individuals need monitoring applications at different levels of quality based on their needs;we exploit these quality/needs tolerances by modeling them as a"personal-space-state", a unique abstraction for spaces/individuals contexts. Then, we intelligently leverage the dynamic personal-space-state to provision services (multiple algorithms with different configurations) to reduce energy overhead while ensuring application quality. We propose an efficient IoT strategy that triggers actions and personal-space-state shifts to drive energy-optimized services for each individual. To validate our approach, we derive use-cases from real-world assisted living facilities with multiple monitoring applications such as fall detection and gait monitoring. Through detailed testbed measurements and larger simulated scenarios, we show that our personal-space-state transition approach can achieve greater than 2X reductions in energy dissipation and computational overhead without loss of accuracy. © 2024 IEEE.

关键词： Assisted living

来源：评论

学校读者我要写书评

暂无评论

Evaluating Machine Learning Methods for Bangla Text Emotion Analysis

Evaluating Machine Learning Methods for Bangla Text Emotion ...

引用

2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Akter, Tahmina Akter, Mst. Sharmin Mahmud, Tanjim Islam, Dilshad Hossain, Mohammad Shahadat Andersson, Karl Port City International University Dept. of Computer Science and Engineering Chittagong Bangladesh Rangamati Science and Technology University Dept. of Computer Science and Engineering Rangamati4500 Bangladesh Chattogram Veterinary and Animal Sciences University Dept. of Physical and Mathematical Sciences Bangladesh University of Chittagong Dept. of Computer Science and Engineering Chittagong4331 Bangladesh Luleå University of Technology Cybersecurity Laboratory Luleå97187 Sweden

ISBN: (纸本)9798350361537

Text-based emotion identification goes beyond simple sentiment analysis by capturing emotions in a more nuanced way, akin to shades of gray rather than just positive or negative sentiments. This paper details our experiments with emotion analysis on Bangla text. We collected a corpus of user comments from various social media groups discussing socioeconomic and political topics to identify six emotions: sadness, disgust, surprise, fear, anger, and joy. We evaluated the performance of four widely used machine learning algorithms - RF, DT, k-NN, and SVM - alongside three popular deep learning algorithms - CNNs, LSTM, and Transformer Learning - using TF-IDF feature extraction and word embedding techniques. The results showed that among the machine learning algorithms, DT, RF, k-NN, and SVM achieved accuracy scores of 82%, 84%, 73%, and 83%, respectively. In contrast, the deep learning models CNN and LSTM both achieved higher performance with an accuracy of 85% and 86% respectively. These findings highlight the effectiveness of traditional ML and DL approaches in detecting emotions from Bangla social media texts, indicating significant potential for further advancements in this area. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Image Enhancement for Iris Analysis Using Deep Learning Algorithms - A Brief Survey 2

Image Enhancement for Iris Analysis Using Deep Learning Algo...

引用

2nd International Conference on Emerging Trends in Information technology and Engineering, ic-ETITE 2024

作者： Poovayar Priya, M. Ezhilarasan, M. Pondicherry Engineering College Dept. of Computer Science and Engineering Puducherry India Pondicherry Engineering College Dept. of Information Technology Puducherry India

ISBN: (纸本)9798350328202

With applications including medical image analysis, picture sharpening and restoration, robot vision, pattern recognition, and video processing, among many others, image enhancement is the main topic in image processing and computer vision. There have been many algorithms for improving images established in the past. More extensive work on image-enhancing techniques has been done utilizing deep learning models in recent years, as these algorithms have achieved their peak in vision applications. In this study, we present a thorough analysis of machine learning, deep learning, and literature. The literature on image enhancement is then summarised, and future approaches for iris analysis are discussed. © 2024 IEEE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Digital Image Encryption Based On Elliptic Curve Cryptography 4

Digital Image Encryption Based On Elliptic Curve Cryptograph...

引用

4th IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer Engineering, MI-STA 2024

作者： Hasan, Mahmoud H. S. Ahmed, Medht H. S. H. Alasmarya Islamic University College of Information Technology Dept. Computer Science Zliten Libya Higher Institute of Engineering Technology Dept. Communication Engineer Zliten Libya

ISBN: (纸本)9798350372632

Information security is currently a major problem for data communication. Cryptography has emerged as a treatment and is essential to information security systems. Techniques for encryption can effectively prevent attacks on images. Elliptic curve cryptography (ECC) is an approach of public-key encryption, depends on the algebraic grouping of elliptic curves over finite fields. The present study introduces an intriguing elliptic curve cryptography-based image encryption approach and applied it to various images. The proposed technique was tested. We computed the number of pixels change rate (NPCR), unified average changing intensity (UACI), and peak signal to noise ratio (PSNR) to assess the effectiveness of the suggested technique. © 2024 IEEE.

关键词： Geometry

来源：评论

学校读者我要写书评

暂无评论

Dynamic Checkpointing: Fault Tolerance in High-Performance Computing 3

Dynamic Checkpointing: Fault Tolerance in High-Performance C...

引用

3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Bhowmik, Biswajit Verma, Tushar Dineshbhai, Navdeep Dadhania Reddy, Manideep Raya Vsrs Girish, K.K. National Institute of Technology Karnataka Maharshi Sushrut Cas Lab Brics Laboratory Dept. of Computer Science and Engineering Mangalore India National Institute of Technology Karnataka Maharshi Kanad Qc Lab Brics Laboratory Dept. of Computer Science and Engineering Mangalore India National Institute of Technology Karnataka Ishwarchandra Vidyasagar Ait Lab Brics Laboratory Dept. of Computer Science and Engineering Mangalore India

ISBN: (纸本)9798331528201

Parallel computing has become a cornerstone of modern computational systems, enabling the rapid processing of complex tasks by utilizing multiple processors simultaneously. However, the efficiency and reliability of these systems can be significantly compromised by inherent challenges such as hardware failures, communication delays, and uneven workload distribution. These issues not only slow down computations but also threaten the dependability of applications reliant on parallel processing. To address these challenges, researchers have developed strategies like dynamic checkpointing and load balancing, which are crucial for enhancing fault tolerance and optimizing performance. Dynamic checkpointing periodically saves the computational state, allowing for recovery from failures without significant data loss, while load balancing ensures that tasks are evenly distributed across processors, preventing bottlenecks and underutilization of resources. By integrating these mechanisms, this paper proposes a robust framework that improves the reliability and efficiency of parallel systems, particularly in high-performance computing environments where the ability to handle large-scale data processing with minimal downtime is critical. © 2024 IEEE.

关键词： Parallel processing systems

来源：评论

学校读者我要写书评

暂无评论

Multi-Agent H-Learning Based Cooperative Spectrum Sensing for Cognitive Radio Networks 32

Multi-Agent H-Learning Based Cooperative Spectrum Sensing fo...

引用

32nd International Conference on Electrical Engineering, ICEE 2024

作者： Fard, E. Karimpour Nouri, M. Behroozi, H. Sobhi-Givi, S. Sharif University of Technology Dept. of Electrical Engineering Tehran Iran University of Mohaghegh Ardabili Dept. of Electrical and Computer Engineering Ardabil Iran

ISBN: (纸本)9798350376340

Fast and accurate methods for spectrum sensing (SS) are the key elements in cognitive radio networks (CRNs) that achieve high SS. This paper proposes a reinforcement learning (RL) scheme for secondary users (SUs) in a massive multiple-input multiple-output (MIMO) CRN to determine occupation and emptiness of scanned wideband channels. In the proposed H-learning method, the clustered neighboring SUs collect data to check the status of channels that improve reliability of measured sensing. Then, they share information about different frequency channels with other clusters and the status of channel occupation is determined for all SUs. This model-based learning method increases finding free channels and enhances spectral efficiency (SE) in presence of large probability of missing detection. Furthermore, each SU learns the presence pattern of primary user (PU) and gather a dynamic scan priority list to decrease scan overhead and access delays. Simulation results demonstrate the multi-agent reinforcement modified H-learning (MH-learning) method can achieve better performance in terms of PU usage percent, number of attempts, call block rate, and probability of detection in comparison to H-learning and some state-of-art learning methods. © 2024 IEEE.

关键词： Reinforcement 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 << < 64 65 66 67 68 69 70 71 72 73 > >>

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：