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

30,832 篇 会议
5,152 篇 期刊文献
250 册 图书

馆藏范围

36,234 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

22,818 篇 工学
- 15,827 篇 计算机科学与技术...
- 13,305 篇 软件工程
- 5,810 篇 信息与通信工程
- 3,521 篇 控制科学与工程
- 2,701 篇 电子科学与技术（可...
- 2,679 篇 电气工程
- 2,347 篇 生物工程
- 1,880 篇 生物医学工程（可授...
- 1,556 篇 光学工程
- 1,466 篇 机械工程
- 1,332 篇 动力工程及工程热...
- 1,270 篇 仪器科学与技术
- 1,245 篇 化学工程与技术
- 1,121 篇 建筑学
- 1,096 篇 土木工程
- 1,035 篇 安全科学与工程
- 958 篇 材料科学与工程（可...
11,901 篇 理学
- 6,331 篇 数学
- 3,251 篇 物理学
- 2,605 篇 生物学
- 2,114 篇 统计学（可授理学、...
- 1,366 篇 系统科学
- 1,255 篇 化学
5,796 篇 管理学
- 3,468 篇 管理科学与工程(可...
- 2,614 篇 图书情报与档案管...
- 1,945 篇 工商管理
1,599 篇 医学
- 1,386 篇 临床医学
- 1,294 篇 基础医学(可授医学...
- 840 篇 药学(可授医学、理...
1,054 篇 法学
- 845 篇 社会学
693 篇 经济学
543 篇 农学
456 篇 教育学
156 篇 文学
78 篇 军事学
43 篇 艺术学
3 篇 哲学

主题

1,076 篇 accuracy
829 篇 feature extracti...
828 篇 computational mo...
714 篇 deep learning
676 篇 computer science
671 篇 training
513 篇 real-time system...
508 篇 support vector m...
503 篇 machine learning
442 篇 predictive model...
409 篇 internet of thin...
355 篇 convolutional ne...
349 篇 data models
339 篇 computer archite...
329 篇 reliability
312 篇 optimization
282 篇 data mining
277 篇 routing
254 篇 wireless sensor ...
249 篇 conferences

机构

83 篇 institut univers...
82 篇 north-west unive...
81 篇 national centre ...
79 篇 infn sezione di ...
76 篇 infn sezione di ...
76 篇 institute of inf...
75 篇 tno technical sc...
67 篇 université de st...
66 篇 università di ca...
62 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...
48 篇 dept. of compute...
48 篇 dept. of compute...
45 篇 dept. of electri...
44 篇 dept. of compute...

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.
80 篇 coleiro a.
78 篇 gozzini s.r.
69 篇 huang f.
66 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

34,205 篇 英文
1,546 篇 其他
331 篇 中文
104 篇 日文
46 篇 朝鲜文
3 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 Civil Engineering and Computer Science Engineering"

共 36234 条记录，以下是561-570 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：

FOOTBALL DATA ANALYSIS: THE PREDICTIVE POWER OF EXPECTED GOALS 25

FOOTBALL DATA ANALYSIS: THE PREDICTIVE POWER OF EXPECTED GOA...

引用

25th International Conference on Intelligent Games and Simulation, GAME-ON 2024

作者： Roccetti, Marco Berveglieri, Filippo Cappiello, Giuseppe Dept. of Computer Science and Engineering University of Bologna Italy Dept. of Management University of Bologna Italy

ISBN: (纸本)9789492859327

Major football events, such as the World Cup, have popularized the European football (i.e., soccer) beyond its traditional geographical borders, for example with a growing number of Americans who have begun to incorporate European football into their daily sport consumption. Many video game series based on this sport have further contributed to this increasing development. Not only that, but many performance indicators inspired by football computer games have become metrics that are now part of the normal conversation about real football, being used to analyse tactics, teams and players. Among these indicators, of prominent importance is the role of expected goals (xG) that measure the quality of a shot by calculating the likelihood that it will be scored from a particular position during a particular phase of play. Often, someone talks about xG leading to imprecise conclusions and to a distorded point of view on this performance indicator. In this paper, using a non-parametrical Kolmogorov Smirnov hypothesis testing method, we show that there is no statistically significant difference if, in a given football tournament, the final scores are awarded to the participating teams either with real goals or based on xGs, thus demystifying some wrong assumptions about this indicator. Data for this study come from all the matches played during the 2020 UEFA European Football Championship. © 2024 25th International Conference on Intelligent Games and Simulation, GAME-ON 2024. All rights reserved.

关键词： Predictive analytics

来源：评论

学校读者我要写书评

暂无评论

Stock Market Prediction Using Genetic Algorithm Assisted LSTM-CNN Hybrid Model 14

Stock Market Prediction Using Genetic Algorithm Assisted LST...

引用

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

作者： Nikhil, Shreyas Sah, Rahul Kumar Kumar Parki, Santosh Tamang, Til Bikram Somashekhara Reddy, D. Mahesh, T.R. Faculty of Engineering and Technology Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350335095

Stock price prediction has always been a tough task for all the stakeholders involved. This paper focusses on four different models, namely LSTM, CNN, LSTM-CNN, and Genetic Algorithm-Assisted LSTM-CNN (GA-LSTM-CNN) for stock price prediction. The day-to-day stock prices of a certain company for a period of more than 10 years make up the dataset utilized in this study. Root mean square error (RMSE) has been utilized as performance metric for each model. Outcomes of our experiment show that the GA-LSTM-CNN model performed better than other models with an RMSE value of 0.0064 upon training and an RMSE value of 0.03 upon testing. The GA-LSTM-CNN model combines the strengths of LSTM as well as CNN models with the help of a genetic algorithm, which helps in optimizing the hyperparameters. According to the results, the GA-LSTM-CNN model can be very helpful for the stakeholders in predicting future stock values. © 2023 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Optimizing Multi-Class Classification in Educational Data with Ensemble Learning and Data Balancing Techniques 5

Optimizing Multi-Class Classification in Educational Data wi...

引用

5th International Conference on Intelligent Data science Technologies and Applications, IDSTA 2024

作者： Al-Hammouri, Mohammad F. Hammouri, Ziad Akram Ali Almalkawi, Islam T. Lafee, Ansam The Hashemite University Dept. of Computer Engineering Zarqa Jordan Middle East University Dept. of Computer Science Amman Jordan

ISBN: (纸本)9798350354751

The field of education is increasingly embracing AI tools to improve student outcomes. This work aims to reduce academic failure in higher education by employing machine learning techniques to identify at-risk students early in their educational journey, enabling the implementation of supportive strategies to assist them. This study examines a dataset from a higher education institution and utilizes it to develop a classification model for predicting students' academic performance. The problem is formulated as a multi-class classification task with three categories: Graduate, Enrolled, and Dropout, with a significant imbalance skewed toward the Graduate. To improve prediction accuracy toward the minority class, the data balancing technique SMOTE with Edited Nearest Neighbor (SMOTE-ENN) is applied. Three popular classification models - Random Forest, XGBOOST and CatBoost - are employed. The findings show that SMOTE-ENN significantly improves classification results. Moreover, XGBOOST demonstrated the highest accuracy (94.6%) in correctly identifying all classes, as evidenced by the confusion matrix evaluation, achieving the highest results compared to previous work in the literature. Implementing these models allows for accurate predictions of students' performance and helps reduce dropout rates. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

VAR: An Efficient Silent Video to Speech System with Subtitle Generation using Visual Audio Recall 5

VAR: An Efficient Silent Video to Speech System with Subtitl...

引用

5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Shanmugam, Diya Dhandapani Syed, Safiya Fathima Dinesh, Sahana Chitrakala, S. College of Engineering Guindy Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350321425

In this paper, a method to generate speech from a muted video is proposed. Recent advances in computer vision and deep learning have allowed the development of lip-reading technology that can recognize and interpret lip movements in videos. However, one of the main challenges in visual-to-speech synthesis is distinguishing between homophenes, or sets of words that look identical on a person's lips but contain different sounds. To address this challenge, the proposed model utilizes a speech generation framework that uses an external memory called Visual Audio Recall (VA-Recall) to generate speech from silent video. The VA-Recall system allows the system to effectively synthesize speech from a speaker by recalling the most relevant auditory information that matches the visual input context. The proposed method further generates subtitles for the reconstructed audio. Overall, this process allows for a more natural and contextually appropriate speech synthesis system. © 2023 IEEE.

关键词： Speech synthesis

来源：评论

学校读者我要写书评

暂无评论

Comparative Study on Extractive Summarization Using Sentence Ranking Algorithm and Text Ranking Algorithm

Comparative Study on Extractive Summarization Using Sentence...

引用

2023 International Conference on Power, Instrumentation, Control and Computing, PICC 2023

作者： Majeed, Mansoora Kala, M.T. Government Engineering College Dept. of Computer Science and Engineering Thrissur India

ISBN: (纸本)9798350334463

It is possible to create an accurate and succinct summary using a method called automatic text summarising. Before creating the necessary summary sentences, the machine learning algorithms may be trained to understand documents and recognise the portions that transmit crucial facts and information. Abstractive text summa- rization and Extractive text summarization are its two methods. An extractive text summarization refers to the process of removing significant text from a text document or source manuscript. Deep learning techniques are used to train an abstractive text summarizer, which then generates new phrases and keywords based on the content of the original text. The process of acquiring and assimilation of the knowledge from numerous sources takes time. Automatic text summary is used to speed up the process of finding and consuming pertinent information. An extractive text summarising technique chooses crucial phrases, sentences, and other parts of the original text and concatenates them into a compressed form. The extractive text summarization produces grammatically correct sentences. The project is to develop a model that demonstrates extractive text summarization using sentence ranking and text rank algorithm. It shows that the text rank algorithm does a remarkable performance to extractive text summarization. Using a sentence ranking algorithm, extractive summaries are created that rate sentences according to their weights. In order to create a high-quality summary of the input document and store the summary as audio, the input document's highly scored sentences are extracted. A non-supervised, extractive text summarising method is called TextRank. While calculating the value of words and phrases in a document, the TextRank algorithm looks at how they relate to one another. According on how important the words are in each phrase, it then assigns a score to each one. The summary is formed using the algorithm's choice of the most crucial phrases. © 2023 IE

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Smart City Surveillance: Survey on Current Status and Future Trends 14

Smart City Surveillance: Survey on Current Status and Future...

引用

14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Neyaz, Hera Paul, Hrituparna Srivastava, Anima Singh, Shiksha Dept. of Computer Science and Engineering Shambhunath Institute of Engineering and Technology India

This paper presents a comprehensive survey on surveillance and security aspects of a smart city. Multiple dimensions of a smart city surveillance system have been discussed. The current trends and methodologies are thoroughly researched and presented. The algorithms of novel methods are reviewed along with analytics and methodologies. Impact of XAI in the smart city surveillance is discussed. Advantages and disadvantages of current infrastructures have been included in the broad literature survey. Lastly, the challenges and future trends are conferred to. © Grenze Scientific Society, 2023.

关键词： Smart city

来源：评论

学校读者我要写书评

暂无评论

Few-Shot Learning with Feature Pairing and Mean Discrepancy

Few-Shot Learning with Feature Pairing and Mean Discrepancy

引用

2023 International Conference on Sustainable Computing and Smart Systems, ICSCSS 2023

作者： Singh, K.K. Hima Bindu, K. Nit Andhra Pradesh and Rgukt Nuzvid Dept. of Computer Science and Engineering India Nit Dept. of Computer Science and Engineering AP India

ISBN: (纸本)9798350333602

Few-Shot Learning (FSL) is a sub-area of machine learning which mainly deals with data where there is a scarcity of training supervised samples. Few shot learning (FSL) more closely resembles the human brain in comparing new concepts to others based on prior experience rather than identifying it exactly. FSL aims to generalize the model across the tasks (in meta learning) opposed to the classical supervised learning which generalizes across the data points. In general the FSL models may suffer from underfitting because of scarcity of supervised samples and at the same time it causes overfitting as it is likely to memorize task specific features of the training set. This work aims to reduce such problems and is presented as a metric based model 'Few Shot Learning with Feature Pairing and Mean Discrepancy' (FL-FPMD). As the title suggests, feature pairing is one among various data augmentations. It is observed that flip augmentation is more suitable in the context of pairing the features within the given task. Memorizing task specific features is reduced by incorporating the discrepancy of mean distributions of the query and the support embedding in the loss function. The training and the evaluation is performed at the miniImageNet dataset and the results indicate that the proposed model outperforms the state-of-the-art models of similar complexity. © 2023 IEEE.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Advancements in Left Ventricular Myocardium Analysis: A Comprehensive Review of Myocardium Segmentation, Fibrosis Detection and Wall Motion Estimation Using Cardiac Magnetic Resonance Imaging

Advancements in Left Ventricular Myocardium Analysis: A Comp...

引用

2024 IEEE International Conference on Emerging Technologies in computer science for Interdisciplinary Applications, ICETCS 2024

作者： Sunanda, H.G. Kavitha, K.S. Bangalore Institute of Technology Dept. of Computer Science and Engineering Bengaluru560004 India Visvesvaraya Technological University Belagavi590018 India Dayananda Sagar College of Engineering Dept. of Computer Science and Engineering Bengaluru560078 India

ISBN: (纸本)9798350372502

Cardiac Magnetic Resonance Imaging (CMRI) has established itself as a cornerstone in cardiovascular diagnostics, enabling precise assessment of left ventricular (LV) myocardium. This review meticulously examines the multifaceted aspects of LV myocardium analysis, focusing on three pivotal components: myocardium segmentation, fibrosis detection, and wall motion estimation. By exploring cutting-edge techniques and methodologies in these domains, this article sheds light on the profound impact CMR has had on the accurate diagnosis, prognosis and structuring treatment plans for diseases of the heart. In the realm of cardiac diagnostics, Left Ventricular (LV) myocardium analysis utilizing CMRI has undergone a transformation advancement. This review encapsulates the comprehensive exploration of LV myocardium analysis, Myocardium segmentation techniques, ranging from traditional methods to contemporary machine learning-driven approaches, are scrutinized for their accuracy and efficiency. The detection and characterization of myocardial fibrosis, crucial in diagnosing various cardiac conditions, are dissected through cutting-edge CMR techniques such as Late Gadolinium Enhancement (LGE) imaging and quantitative mapping methods. Additionally, advanced methods of wall motion estimation, including feature tracking and strain imaging, highlighting their applications in assessing myocardial function. Real-world clinical scenarios underscore the transformation impact of these techniques on diagnosing heart diseases, guiding treatment decisions, and improving patient outcomes. The current landscape of LV myocardium analysis, emphasizing the pivotal role of CMR in revolutionizing cardiac healthcare. © 2024 IEEE.

关键词： Motion estimation

来源：评论

学校读者我要写书评

暂无评论

Breast Cancer Detection with Machine Learning-A Review 2

Breast Cancer Detection with Machine Learning-A Review

引用

2nd International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2023

作者： Meghana, Karnam Nandal, Neha Tanwar, Rohit Goel, Lipika Chhabra, Gunjan Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Computer Science and Engineering Hyderabad India University of Petroleum and Energy Studies Dept. of Computer Science and Engineering Dehradun India Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9781665491990

Malignancy in the breast is a significant public health concern, where timely identification is essential for effective treatment. Machine Learning (ML) and Deep Learning (DL) algorithms are potential tools for prompt detection og breast malignancy through examination of medical images such as mammograms. Convolutional neural networks (CNNs), transfer learning, and ensemble learning are some of the recent techniques being used in this field. Despite the advantages of ML and DL algorithms for breast cancer detection, there are still several challenges that need to be addressed. The lack of diversity in the datasets used to train algorithms is one major challenge, with many datasets based on specific populations that may not represent others. Highly annotated data is also limited in medical field. The objective of this study is to provide researchers with valuable insights and guidance. © 2023 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Investigation of Convolutional Neural Network with Motor Imagery-based Brain-computer Interface Decoding 14

Investigation of Convolutional Neural Network with Motor Ima...

引用

14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Madhan, H.K. Bindushree, V. Dept. of Computer Science and Engineering Navkis College of Engineering Hassan India

In recent years, Brain-computer Interfaces (BCI) have become increasingly popular for assisting individuals with disabilities in restoring communication and mobility. The area of research focuses on utilizing convolutional neural networks (CNNs), specifically deeper architectures with high dropout, to decode brain signals and enable users to interact with the world more naturally, particularly through motor imagination. Motor imagination involves analyzing brain signals to decipher a person's intention to perform a motor task. CNNs are well-suited for BCI decoding due to their ability to learn intricate features from raw EEG data. However, the challenge lies in preventing overfitting in deeper CNN architectures, which have a larger number of parameters. To overcome this, the proposed approach involves a high truncation CNN architecture, a regularization technique that randomly turns off neurons during training to mitigate overfitting. © Grenze Scientific Society, 2023.

关键词： Brain computer interface

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 << < 53 54 55 56 57 58 59 60 61 62 > >>

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：