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

30,335 篇 会议
4,649 篇 期刊文献
237 册 图书

馆藏范围

35,221 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

21,813 篇 工学
- 15,775 篇 计算机科学与技术...
- 13,278 篇 软件工程
- 5,816 篇 信息与通信工程
- 3,434 篇 控制科学与工程
- 2,680 篇 电子科学与技术（可...
- 2,619 篇 电气工程
- 2,354 篇 生物工程
- 1,892 篇 生物医学工程（可授...
- 1,538 篇 光学工程
- 1,348 篇 机械工程
- 1,221 篇 动力工程及工程热...
- 1,206 篇 仪器科学与技术
- 1,018 篇 化学工程与技术
- 858 篇 安全科学与工程
- 721 篇 交通运输工程
11,181 篇 理学
- 6,050 篇 数学
- 3,059 篇 物理学
- 2,573 篇 生物学
- 2,001 篇 统计学（可授理学、...
- 1,338 篇 系统科学
- 1,090 篇 化学
5,625 篇 管理学
- 3,288 篇 管理科学与工程(可...
- 2,617 篇 图书情报与档案管...
- 1,827 篇 工商管理
1,600 篇 医学
- 1,388 篇 临床医学
- 1,300 篇 基础医学(可授医学...
- 851 篇 药学(可授医学、理...
- 678 篇 公共卫生与预防医...
1,030 篇 法学
- 824 篇 社会学
645 篇 经济学
- 645 篇 应用经济学
491 篇 农学
430 篇 教育学
156 篇 文学
77 篇 军事学
39 篇 艺术学
1 篇 哲学

主题

1,099 篇 accuracy
862 篇 feature extracti...
843 篇 computational mo...
729 篇 deep learning
678 篇 computer science
678 篇 training
521 篇 real-time system...
517 篇 support vector m...
496 篇 machine learning
446 篇 predictive model...
424 篇 internet of thin...
372 篇 convolutional ne...
356 篇 data models
349 篇 computer archite...
330 篇 reliability
308 篇 optimization
289 篇 data mining
281 篇 routing
263 篇 wireless sensor ...
253 篇 conferences

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 ...
76 篇 tno technical sc...
67 篇 université de st...
67 篇 dept. of informa...
66 篇 università di ca...
65 篇 nikhef national ...
58 篇 dept. of informa...
57 篇 dept. of compute...
56 篇 dept. of compute...
53 篇 leiden universit...
52 篇 school of automa...
52 篇 dept. of compute...
49 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 kalekin o.
81 篇 chen a.
80 篇 díaz a.f.
80 篇 boumaaza j.
78 篇 coleiro a.
77 篇 gozzini s.r.
70 篇 huang f.
70 篇 dallier r.
60 篇 anguita m.
52 篇 kulikovskiy v.
44 篇 del burgo r.
41 篇 benoit d.m.
41 篇 eddymaoui a.
40 篇 gagliardini s.
40 篇 labalme m.

语言

33,307 篇 英文
1,503 篇 其他
311 篇 中文
54 篇 日文
45 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=Computer Applications in Science and Engineering dept."

共 35221 条记录，以下是1021-1030 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：

Indonesian Hate Speech and Abusive Tweets Classification with Deep Learning Pre-trained Language Models 6

Indonesian Hate Speech and Abusive Tweets Classification wit...

引用

6th International Conference on computer and Informatics engineering, IC2IE 2023

作者： Yulianto Darmawan, Bagus Tri Irnawan, Bassamtiano Renaufalgi Suzuki, Yoshimi Politeknik Negeri Jakarta Dept. of Computer and Informatics Engineering Depok Indonesia University of Yamanashi Dept. of Computer Science and Engineering Kofu Japan

ISBN: (纸本)9798350345162

Hate speech and abusive language on social media can spread massively and escalate into conflict between two or more individuals or parties. Previous studies about multi-label classification to identify whether the tweet contains hate speech, abusive language, or not have been conducted with machine learning techniques. They applied machine learning with a combination of feature extraction and achieved a good result in recognizing the tweet with hate speech content. In this research, we apply two approaches: first, we use vanilla pre-trained models of IndoBERT, IndoBERTweet, and Indonesian RoBERTa;second, we combine the three previous models with CNN. Our experiment shows that our proposed method has better results compared to previous research with the best performance achieved by IndoBERTweet+CNN with 93.9% Accuracy. © 2023 IEEE.

关键词： Abusive CNN Deep Learning Hate Speech IndoBERT IndoBERTweet Indonesian RoBERTa Indonesian Twitter

来源：评论

学校读者我要写书评

暂无评论

Mask Region-Based Convolutional Neural Network for Disease Detection in Rice Leaf 3

Mask Region-Based Convolutional Neural Network for Disease D...

引用

3rd International Conference for Advancement in Technology, ICONAT 2024

作者： Putta, Narsaiah Kumari, T. Suvarna Naik, K Jairam Vasavi College of Engineering Dept. of Computer Science & Engg. Telangana Hyderabad India Chaitanya Bharathi Institute of Technology Dept. of Computer Science & Engg. Telangana Hyderabad India National Institute of Technology Raipur Dept. of Computer Science & Engg. Chhattisgarh India

ISBN: (纸本)9798350354171

Many approaches have been proposed for the problems, like manual diagnosis of crops and soil by experts. But this one is actually a very time-consuming activity. With the advancement of technology, many approaches have been made using machine learning, like image processing techniques, deep convolutional neural networks, segmentation techniques based on neutrosophic logic, etc. However, most of these methods were slow or had implemented complex algorithms that made them unsuitable for being used as an Android app. So, in this paper, a rice leaf disease detection and classification model using region-based convolutional neural networks and deep learning has been proposed. Using this approach, we have successfully developed a model to detect and classify diseases with an accuracy of 94.4%. Determining the type of disease in crops may help the farmers take timely measures and, therefore, avoid the loss. © 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

N-Queens Convergence: A Tactical Framework for Efficient Target-Directed Drone Formations and Attacks 7

N-Queens Convergence: A Tactical Framework for Efficient Tar...

引用

7th IEEE International Conference on Computational Systems and Information Technology for Sustainable Solutions, CSITSS 2023

作者： Kumar, Preethika Ajay Pes University Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350343144

This study introduces a novel methodology for enhancing the efficiency of Unmanned Aerial Vehicle (UAV) formations in order to achieve accurate target engagements. The concept draws inspiration from the N-Queens puzzle. By incorporating unmanned aerial vehicle (UAV) positioning into a simulated chessboard and expanding it to include a target in the (N + 1)th column, the algorithm produces arrangements that guarantee effective engagement with the target. Significantly, this particular technique ensures the absence of overlapping pathways among UAVs during strikes, hence augmenting operational safety. The methodology employed in this study involves the construction of formations through the generation of permutations for all possible queen positions. Subsequently, the eligible queen configurations are determined by filtering based on the diagonal lines of attack. The method has been tested on N values as high as 10. This study explores the intersection of combinatorial problem-solving with military applications, providing novel insights and tactics for deploying UAVs that minimize collisions. © 2023 IEEE.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Oversample minority classes in Lung Ultrasound using Generative Adversarial Network

Oversample minority classes in Lung Ultrasound using Generat...

引用

2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Fatima, Noreen Mento, Federico Demi, Libertario University of Trento Dept. of Information Engineering and Computer Science Italy

ISBN: (纸本)9798350346459

The development of a strong methodological strategy focusing on class imbalance issues for Lung Ultrasound (LUS) data is lacking in the state of the art. Traditional oversampling methods such as geometric and affine transformations generate quasi-duplicates of the original data. This problem could be resolved through generative adversarial networks (GANs). However, in classic GANs the generator cannot handle mode collapse issues and the model's performance remains unstable when images in different classes look similar. To address this problem, we proposed a novel approach based on a supervised autoencoder generative adversarial network (SA-GAN), which could help to oversample the minority classes. At first, we build a latent space with the help of a supervised autoencoder (SA) to handle the mode collaspe issues. Then the trained weights of the SA are used to construct the generator and discriminator models. During the adversarial training of both models, the loss function is calculated for real and generated images through a customized gradient penalty loss function. This also allows classifying each image into real or generated, and its corresponding classes. This approach was tested on a dataset comprising 5500 LUS images, which were collected from 35 COVID-19 patients. As a result, SA-GAN provided the 900 generated LUS samples in minority classes to balance with the majority class. The proposed approach significantly improved the classification accuracy by up to 5% using synthetic augmentation through SA-GAN over the classic data augmentation method. © 2023 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Review Machine Learning Models for Managing Hotel Cancellations in the Tourism Industry 3

Review Machine Learning Models for Managing Hotel Cancellati...

引用

3rd IEEE International Conference on Intelligent Technologies, CONIT 2023

作者： Sekhon, Gursimran Ahuja, Sachin Chandigarh Univercity Dept. of Computer Science Engineering Mohali India

ISBN: (纸本)9798350338607

This survey paper is one-stop-shop for keeping up with the latest research on predicting hospitality booking cancellations using machine learning and deep learning techniques. With cancellations having such a significant impact on hospitality revenue and reputation, it's crucial to develop effective prediction models, and this paper highlights the various techniques used in recent studies. But accurate and reliable cancellation forecasting is more than just a theoretical exercise;it's essential for successful revenue management in the tourism and hospitality industry. The paper delves into the challenges associated with demand forecasting, particularly in the context of last-minute bookings and changes in customer behavior. To help navigate these challenges, this survey paper suggests the neural network method as a promising approach for predicting reservation cancellations, enabling hospitality management to make informed decisions about which reservations to accept or reject. Although cancellation policies have been put in place by hospitality management to mitigate the effects of cancellations, issues such as demand and reputation persist. The paper underscores the significance of segregating data sets and feature engineering in predictive models, which is supported by the studies reviewed. Moreover, the paper examines the importance of extracting insights from extensive databases and leveraging predictive analytics to identify the factors that influence the likelihood of booking cancellations. © 2023 IEEE.

关键词： Predictive analytics

来源：评论

学校读者我要写书评

暂无评论

Youth Unemployment Mitigation: Leveraging Machine Learning and Exploratory Data Analysis for Evidence-Driven Strategies

Youth Unemployment Mitigation: Leveraging Machine Learning a...

引用

2023 IEEE Conference on engineering Informatics, EI 2023

作者： Aarthi, S. Dharmita, A. Pragathi, G. Elakkiya, S. Srm Institute of Science and Technology Dept. of Computer Science Engineering Chennai India Srm Institute of Science and Technology Dept. Computer Science Engineering Specialization with Big Data Analytics Chennai India

ISBN: (纸本)9798350338522

Youth unemployment represents an urgent global socioeconomic challenge. This study combines machine learning and exploratory data analysis to understand and solve this problem comprehensively. Traditional approaches often rely on qualitative assessments and historical data requiring a data-driven transition to more effective solutions. Our approach integrates machine learning algorithms and Exploratory Data Analysis techniques to analyze diverse data sets, identify influencing factors, and recommend targeted interventions. The analysis process includes data collection, preprocessing, feature selection, machine learning modeling, and Exploratory Data Analysis techniques to understand the dynamics of the Better understanding unemployment among young people. Preliminary results reveal precise predictive patterns and previously unrecognized relationships, providing evidence-based solutions to inform policy and support the economic well-being of younger generations. Further research and validation are needed to increase applicability. © 2023 IEEE.

关键词： Data visualization

来源：评论

学校读者我要写书评

暂无评论

IoT-driven automatic vehicle accident rescue system implemented with Proteus 1

IoT-driven automatic vehicle accident rescue system implemen...

引用

1st International Conference on Optimization Techniques for Learning, ICOTL 2023

作者： Hemalatha, K. Ganga Devi, S.V.S. Deepika, V. Madanapalle Institute of Technology and Science Dept. of Computer Science & Engineering-Artificial Intelligence Andhra-Pradesh Madanapalle India Madanapalle Institute of Technology and Science Dept. of Computer Science & Engineering-Cyber Security Andhra-Pradesh Madanapalle India Sri Venkateswara College of Engineering Dept. of Computer Science & Engineering Andhra-Pradesh India

ISBN: (纸本)9798350328042

IoT-driven automatic vehicle accident rescue system implemented with Proteus is an inventive solution aimed at enhancing emergency response and rescue operations following vehicle accidents. Given the rising vehicle usage alongside population growth, the frequency of accidents has also surged over time, leading to unfortunate loss of life due to delays in ambulance arrival at accident scenes. Swift transportation of accident victims to medical facilities is of paramount importance. Upon occurrence of an accident, the proposed "IoT-driven automatic vehicle accident rescue system implemented with Proteus"immediately transmits accident details to the ambulance service, investigation unit, and designated emergency contacts. Simultaneously, the accident's precise location is shared via a Google Maps link to the users' smart devices equipped with mobile network connectivity. This facilitates efficient location identification for both ambulance services and police departments. Comprising elements such as accelerometers, GPS (Global Positioning System) modules, GSM (Global System for Mobile Communication) modules, motors, buzzers, LEDs, and more, the system seamlessly integrates these components with a central microcontroller unit using Proteus software. The core objective of this initiative revolves around two key goals: rescuing drivers involved in accidents and expediting victim recovery during the critical early stages of mishaps. © 2023 IEEE.

关键词： Global system for mobile communications

来源：评论

学校读者我要写书评

暂无评论

Enhancing Emergency Response Through Speech Emotion Recognition: A Machine Learning Approach 26

Enhancing Emergency Response Through Speech Emotion Recognit...

引用

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Deb, Priom Mahrin, Habiba Bhuiyan, Asibur Rahman BRAC University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350359015

applications of interaction between humans and computers, such as emergency response systems, heavily depend on emotion recognition. In this experiment, we present an investigation into Speech Emotion Recognition (SER) specifically in the context of emergency calls using a meticulously curated dataset. This dataset comprises audio recordings from 18 speakers, each expressing four distinct emotions (angry, drunk, painful, and stressful) while reading predefined emergency scenarios. We conducted comprehensive preprocessing, which involved feature extraction using Mel-Frequency Cepstral Coefficients (MFCCs), Chroma (Pitch Classes), and Mel Spectrogram Frequency. The performance of many machine learning models, such as the KNeighbors Classifier, MLP Classifier, Random Forest Classifier, Gradient Boost Classifier, SVM, and Logistic Regression, was then assessed by dividing the dataset into training and testing sets. Our results reveal that the KNeighbors Classifier outperforms other models, achieving an accuracy of 67.06% and maintaining balanced performance metrics. These results offer insightful information about whether SER is practical for emergency call applications. This research contributes to the understanding of emotion recognition in critical situations and can enhance the efficiency of emergency response systems by automating emotion assessment in distress calls. Our findings have practical implications for the development of intelligent systems that can better assist emergency service providers. © 2023 IEEE.

关键词： Emergency Call Emotion Classification Feature Extraction Human-computer Interaction Machine Learning Models Speech Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Meteorological Progress: A Comprehensive Review of Weather Prediction 3

Meteorological Progress: A Comprehensive Review of Weather P...

引用

3rd International Conference on Innovative Mechanisms for Industry applications, ICIMIA 2023

作者： Singh, Gaurav Kumar Ughara, Pawandeep Singh Ishaq, Malik Muzamil Singh, Aryan Pratap Chauhan, Kanak Chandigarh University Dept. of Computer Science & Engineering Mohali India

ISBN: (纸本)9798350343632

Weather forecasting is a crucial and essential part of modern life, spanning many industries and fulfilling a variety of functions. Weather forecasting is essential for the safety, wellbeing, and economic stability of individuals and society as a whole. Accurate predictions help us mitigate the impacts of adverse weather events and make informed decisions in various aspects of our lives. The agricultural industry also relies on weather forecasts to help farmers make decisions about planting, harvesting, and irrigation in order to maximize crop yields and lower the possibility of crop failure due to unfavourable weather conditions. Weather forecasts play a critical role in transportation planning, safety, and accident avoidance in the aviation, marine, and automotive industries. In the energy industry, weather forecasts are also essential for the effective management of renewable energy sources and the production of power. For the purpose of safety, economic planning, environmental monitoring, scientific advancement, and emergency response, weather forecasting is essential. It is essential to many facets of our life since it guarantees readiness, security, and well-informed choices. © 2023 IEEE.

关键词： Artificial Neural Network (ANN) Back Propagation Electronic Neural Network (ENN) Mean Square Error (MSE) Multilayer Feed-Forward Neural Network(MLFNN) Soft Computing

来源：评论

学校读者我要写书评

暂无评论

Early Detection of Alzheimer's Disease using CNN with PSO for parameter optimization 1

Early Detection of Alzheimer's Disease using CNN with PSO fo...

引用

1st IEEE International Conference on Contemporary Computing and Communications, InC4 2023

作者： Harwalkar, Jayant Hemankith Reddy, M. Shravani, M. Samptur, Neelesh Kamatchi Priya, L. PES University Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350335774

Alzheimer's disease (AD) is a progressive neurological disorder that causes the brain to shrink and brain cells to die. Machine learning models play an important role in early diagnosis so the patient can have an opportunity to get the treatment. This paper contains a comprehensive analysis of different machine learning methods used to detect AD. The paper proposes a model for the early detection of AD using Convolutional Neural Network (CNN) and Particle Swarm optimization (PSO) for parameter optimization. The model showed an accuracy of 94.94% which was better than the other models in comparison. © 2023 IEEE.

关键词： Neurodegenerative diseases

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 << < 99 100 101 102 103 104 105 106 107 108 > >>

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：