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

7,090 篇 会议
48 篇 期刊文献
39 册 图书

馆藏范围

7,177 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,913 篇 工学
- 4,098 篇 计算机科学与技术...
- 2,520 篇 软件工程
- 1,048 篇 信息与通信工程
- 789 篇 控制科学与工程
- 663 篇 生物工程
- 643 篇 电气工程
- 424 篇 生物医学工程（可授...
- 285 篇 交通运输工程
- 281 篇 机械工程
- 226 篇 仪器科学与技术
- 226 篇 安全科学与工程
- 206 篇 建筑学
- 197 篇 动力工程及工程热...
- 185 篇 光学工程
- 166 篇 化学工程与技术
- 154 篇 土木工程
1,899 篇 理学
- 1,065 篇 数学
- 717 篇 生物学
- 442 篇 统计学（可授理学、...
- 285 篇 物理学
- 252 篇 系统科学
- 140 篇 化学
1,151 篇 管理学
- 655 篇 管理科学与工程(可...
- 582 篇 图书情报与档案管...
- 315 篇 工商管理
407 篇 医学
- 353 篇 临床医学
- 297 篇 基础医学(可授医学...
- 188 篇 药学(可授医学、理...
244 篇 教育学
- 243 篇 教育学
211 篇 法学
- 197 篇 社会学
119 篇 农学
111 篇 经济学
50 篇 文学
7 篇 艺术学
5 篇 军事学

主题

558 篇 machine learning
456 篇 deep learning
267 篇 training
253 篇 data mining
245 篇 data models
220 篇 feature extracti...
211 篇 accuracy
184 篇 support vector m...
178 篇 predictive model...
138 篇 neural networks
133 篇 computational mo...
131 篇 reinforcement le...
129 篇 machine learning...
110 篇 convolutional ne...
103 篇 real-time system...
92 篇 artificial intel...
89 篇 learning systems
88 篇 transfer learnin...
87 篇 forecasting
86 篇 big data

机构

69 篇 chitkara univers...
17 篇 school of electr...
15 篇 computer science...
14 篇 harbin engineeri...
13 篇 graphic era hill...
12 篇 building civil a...
12 篇 uttaranchal inst...
12 篇 computer science...
11 篇 university of ch...
10 篇 school of electr...
10 篇 school of comput...
10 篇 graphic era deem...
10 篇 school of electr...
10 篇 yonsei univ dept...
9 篇 wuhan university...
9 篇 univ chinese aca...
9 篇 school of inform...
8 篇 school of remote...
7 篇 university of sa...
7 篇 microsoft resear...

作者

17 篇 kukreja vinay
15 篇 vinay kukreja
13 篇 yin hujun
12 篇 liu yang
12 篇 corchado emilio
12 篇 cho sung-bae
10 篇 shiva mehta
10 篇 hujun yin
10 篇 mehta shiva
9 篇 notsu akira
9 篇 silva catarina
9 篇 alhajj reda
7 篇 ksieniewicz pawe...
7 篇 hammer barbara
7 篇 zhang byoung-tak
7 篇 wozniak michal
7 篇 hussain abir
7 篇 huang de-shuang
6 篇 héctor quintián
6 篇 tang ke

语言

6,195 篇 英文
971 篇 其他
31 篇 中文
1 篇 西班牙文
1 篇 俄文

检索条件"任意字段=11th International Conference on Intelligent Data Engineering and Automated Learning"

共 7177 条记录，以下是1031-1040 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：

Transformer Models in Education: Summarizing Science Textbooks with AraBART, MT5, AraT5, and mBART 1st

Transformer Models in Education: Summarizing Science Textboo...

引用

1st international conference on intelligent Systems, Blockchain, and Communication Technologies, ISBCom 2024

作者： Masri, Sari Raddad, Yaqeen Khandaqji, Fidaa Ashqar, Huthaifa I. Elhenawy, Mohammed Department of Natural Engineering and Technology Sciences Arab American University P.O. Box 240 Ramallah Palestine Civil Engineering Department Arab American University P.O. Box 240 Jenin Palestine Columbia University New YorkNY United States CARRS-Q Queensland University of Technology Brisbane Australia Centre for Data Science Queensland University of Technology Brisbane Australia

ISBN: (纸本)9783031823763

In an era of rapidly expanding digital archives, effective text summarization tools are crucial for educators and learners. this study presents an advanced text summarization system specifically designed for Arabic textbooks, leveraging state-of-the-art natural language processing (NLP) models. We trained and evaluated four models - AraBART, mBART50, AraT5, and MT5 - on biology textbook content for 11th and 12th grades in the Palestinian curriculum using the ROUGE metric to compare their performance. Our results show that AraBART and mBART50 outperformed the other models in terms of ROUGE-1 (score: 0.24), ROUGE-2 (score: 0.118–0.139) and ROUGE-L (score: 0.24), indicating their effectiveness in summarizing complex biological information while preserving essential details. To further validate the performance of these models, we conducted a subjective evaluation by an educational expert who assessed the summaries for their accuracy, relevance, and overall quality, with AraBART ranking highest due to its ability to capture key concepts and reduce noise in the original text. the study’s findings provide valuable insights into the performance of these models and contribute to the development of effective tools for understanding and generating Arabic text. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Driver Drowsiness Classification using Machine learning and Heart Rate Variability 11

Driver Drowsiness Classification using Machine Learning and ...

引用

11th international Symposium on Digital Forensics and Security, ISDFS 2023

作者： Meneses, Miguel V. P. R. Antunes, Ana Rita Goncalves, Joaquim Litec Optimizer Innovation and Knowledge Engineering Lab Porto Portugal University of Minho 2Ai-School of Technology Lasi-Associate Laboratory of Intelligent Systems Ipca Portugal Lasi-Associate Laboratory of Intelligent Systems Ipca 2Ai-School of Technology Barcelos Portugal

ISBN: (纸本)9798350336986

Drowsiness at the wheel continues to be one of the causes of road accidents with higher fatality rates and current solutions fail to mitigate the problem from a preventive viewpoint. this work contributes towards the development of a non-intrusive and low-cost system for drowsiness detection and prediction, using a wearable device and artificial intelligence for continuous and real-time monitoring and alert of the driver's state. In particular, Machine learning (ML) algorithms were used to classify drowsiness levels using Heart Rate Variability (HRV) data extracted from physiological signals collected during driving simulations, following data labeling considering three different sets of drowsiness levels' distribution. Obtained results showed promising potential, with the Extra Trees, Random Forest and K-Nearest Neighbors (KNN) classifiers achieving overall good performance, with a relative capability of distinguishing between drowsiness levels and between alert and drowsy states. However, further analysis should be made to improve the performance of the models and deal with the existing data imbalance, as well as identify the best subset of features capable of detecting drowsiness. Ultimately, it was shown that drowsiness detection using physiological data from a standalone wrist-worn wearable device in combination with ML techniques is feasible. Henceforth, prediction and forecasting of the drowsiness state should be addressed, to achieve the preventive component of the system. © 2023 IEEE.

关键词： Wearable technology

来源：评论

学校读者我要写书评

暂无评论

FinRL Contest 2025 Task 1:Market-Aware In-Context learning Framework for Proximal Policy Optimization in Stock Trading Using DeepSeek

FinRL Contest 2025 Task 1:Market-Aware In-Context Learning F...

引用

intelligent data and Security (IDS), IEEE international conference on

作者： Sahar Arshad Huma Ameer Nikhar Azhar Seemab Latif School of Electrical Engineering and Computer Science National University of Sciences and Technology (NUST) Islamabad Pakistan

ISBN: (数字)9798331596613

ISBN: (纸本)9798331596620

this paper introduces a Market-Cap Stratified Subset (MCSS) strategy. It constructs a balanced, high-quality dataset from the Financial News and Stock Price Integration dataset (FNSPID). Building on MCSS, we propose Market-Informed Sentiment for Trading (MIST). this is a two-phase framework that first generates sentiment scores through optimized prompt engineering with LLMs, then aligns market movements to deliver actionable trading signals. With a Proximal Policy Optimization (PPO)-based agent, MIST achieves better policy stability and learning efficiency than baseline methods.

关键词： Large language models Buildings Reinforcement learning Stability analysis Security Prompt engineering Optimization

来源：评论

学校读者我要写书评

暂无评论

DsetGenS: An automated Technique for Building dataset From Speech with respect to Gujarati-English 11

DsetGenS: An Automated Technique for Building Dataset From S...

引用

11th IEEE international conference on Communication Systems and Network Technologies, CSNT 2022

作者： Patel, Margi Joshi, Brijendra Kumar Indore Institute of Science and Technology Department of Computer Science and Engineering Indore India Military College of Telecommunication Engineering Department of Informatics Mhow India

ISBN: (纸本)9781665480383

the computer has seen significant evolution in recent years, with applications in variety of disciplines like Machine learning, Deep learning etc. Machine Translation (MT) technology has advanced significantly as a subfield, with many methodologies and techniques. the number of individuals using the internet has risen tremendously. Most documents are written in English since that is the most extensively used language on the internet. If a user's first dialect is Gujarati, he or she will naturally prefer to access the information in Gujarati whenever possible. Even though there are already various MT systems and tools that support Indian languages;however, the translation's quality is mediocre and might be improved. As observed, when models are trained on limited quantities of parallel data, their performance declines. Learned models often have limited performance (inaccurate translations and feature scores) along with low coverage (high out-of-vocabulary rates). Furthermore, the researchers were driven to present novel methodologies and solutions that would automatically construct datasets for MT due to the increased demand for effective technologies to process and translate information from/to Gujarati Language. Our objective of generating a Gujarati-English dataset has been met in two ways. We have already introduced GEDset, that is automatic dataset Builder for Machine Translation System with Specific Reference to Gujarati-English [1]. Here, in this paper we are proposing a model to automatically build Gujarati-English dataset from audio that is available in Gujarati Language through Speech Processing. © 2022 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

State Definition in Deep Reinforcement learning: A Smoothness Index Approach 11

State Definition in Deep Reinforcement Learning: A Smoothnes...

引用

11th RSI international conference on Robotics and Mechatronics, ICRoM 2023

作者： Dehdasthian, Soroosh Kalhor, Ahmad Masouleh, Mehdi Tale University of Tehran Human and Robot Intraction Laboratory School of Electrical and Computer Engineering Department Iran

ISBN: (纸本)9798350308105

In the pursuit of developing autonomous agents capable of learning optimal behaviors, reinforcement learning has emerged as a foundational frame-work. this paper introduces a novel approach for state definition in deep reinforcement learning systems, with a focus on solving pixel-based control scenarios. the proposed frame-work harnesses the capabilities of Convolutional Variational Auto-Encoders to extract compact and meaningful latent representations from high-dimensional pixel observations. these representations serve as the foundation for constructing an efficient state space for reinforcement learning agents. To further enhance the state construction process, the concept of the Smoothness Index is introduced. Smoothness index acts as a criterion for feature selection within the latent space, facilitating the identification of the most relevant and informative states. Demonstrating the effectiveness of iterative smoothness index-based forward selection, this process notably compresses the observation space while retaining essential information. this compression enables the creation of more efficient reinforcement learning agents. the procedure involves collecting and preprocessing observation data given by the OpenAI Gym car racing environment, encoding observations using a convolutional variational auto-encoder, and iteratively selecting features based on smoothness index. Subsequently, the Proximal Policy Optimization algorithm is employed as a policy-based controller to evaluate the effectiveness of the proposed frame-work. Results indicate that this approach yields a remarkably compact state space that either maintains or enhances reinforcement learning agent performance. this innovative frame-work paves the way for the development of more efficient and adaptive reinforcement learning agents in real-world image-based applications. © 2023 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Comparative Study of Facial Expression Recognition Using Facial Landmark in e-learning System 11

Comparative Study of Facial Expression Recognition Using Fac...

引用

11th international conference on Electrical engineering, Computer Science and Informatics, EECSI 2024

作者： Bachtiar, Fitra Abdurrachman Nainggolan, Cesilia Natasya Soetedjo, Riza Setiawan Rokhmawati, Retno Indah Muflikhah, Lailil Brawijaya University Department of Informatics Engineering Faculty of Computer Science Malang Indonesia Brawijaya University Faculty of Computer Science Department of Information Systems Malang Indonesia

ISBN: (纸本)9798350355314

the e-Iearning system or distance learning system has become important, especially during the COVID-19 pan-demic. Several tertiary institutions have made the e-Iearning system an alternative teaching and learning activity. Research on the use of e-Iearning needs to be explored to obtain innovative, creative, and fun learning. One aspect that can be examined in e-learning is students' emotional response to the learning activities. the emotional state of students directly or indirectly affects the learning process. the student's emotional responses can be measured by their facial expressions. In this study, an exploration was carried out on the facial expressions shown by students in HSS learning, an e-Iearning for learning web programming. the student's facial expressions were extracted using 68 pairs of facial landmarks and additional 6 facial feature vectors. the total number of features used is 142. Machine learning methods for classification are applied to determine the performance of several classification models, including the k-Nearest Neighbor (k- NN) algorithm, Logistic Regression, and Support Vector Machine (SVM). Machine learning performance evaluation is done using the Fl-score and confusion matrix. the results show that the accuracy of the k-NN, Logistic Regression, and SVM are 91.4%, 92.2%, and 92.1 %, respectively. However, the Fl-score macro values are relatively low due to data imbalance with the k- NN, Logistic Regression, and SVM models are 0.250, 0.272, and 0.243, respectively. While the study provides insight into the student learning experience in e-Iearning settings, this study needs to be explored more. © 2024 IEEE.

关键词： Contrastive learning

来源：评论

学校读者我要写书评

暂无评论

automated Machine learning-Algorithm Selection with Fine-Tuned Parameters 6

Automated Machine Learning-Algorithm Selection with Fine-Tun...

引用

6th international conference on intelligent Computing and Control Systems, ICICCS 2022

作者： Avinash, M. Nithya, M. Aravind, S. Sri Sairam Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9781665410359

In recent years, the impact and usage of Machine learning have increased multi-fold. To get the best outcome, it is imperative to choose the right algorithm. Hence, Algorithm Selection is one of the most important stages in the Machine learning Lifecycle. Selecting the optimal algorithm out of many possible algorithms for a given problem statement is always a tedious and time-consuming process. this project assists the researchers and Machine learning enthusiasts in selecting the appropriate algorithm by providing a comparative selection among the different machine learning algorithms available for a pre-processed dataset. Besides the best Algorithm Selection, this project also aims to provide the best hyper-parameters for the opted algorithm using a novel technique. the Algorithm Selection functionality is furnished by comparing the various accuracy metrics like Accuracy, Recall, Precision, F1 Score, R2 Score, Mean Squared Error, etc. the objective of this project is to compare numerous algorithms and suggest the best algorithm. thus, the user can instead concentrate on data Collection and data Pre-processing to achieve success in building the best model. © 2022 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Hybrid CNN-LSTM Model for automated Violence Detection and Classification in Surveillance Systems 12

Hybrid CNN-LSTM Model for Automated Violence Detection and C...

引用

12th international conference on System Modeling and Advancement in Research Trends, SMART 2023

作者： Tiwari, Raj Gaurang Maheshwari, Himani Agarwal, Ambuj Kumar Jain, Vishal Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of Computing Graphic Era Hill University Uttrakhand Dehradun India School of Engineering and Technology Sharda University Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350369861

the proliferation of digital images in recent years has prompted the development of automated algorithms that can identify violent and non-violent material in a variety of settings. this study introduces a unique method for categorising violent and nonviolent pictures using a combined Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model. Careful data collection from a publicly accessible source yielded a dataset of 11,043 original 416x416 photos. the photos were downsampled to 256x256 as part of the preprocessing phase of the suggested technique for more effective model training. the suggested model was compared against both more conventional Machine learning methods and state-of-the-art Deep learning systems to determine how well each performed. the findings reported here are for a 30-epoch value and a learning rate of 0.01. the experiment explored several hyperparameters. An outstanding 98.63 % accuracy was achieved by the suggested hybrid model, demonstrating its better performance. this proves the usefulness and promise of using the hybrid CNN-LSTM model for automated image classification, which in turn improves detection and classification skills for violent and nonviolent images. © 2023 IEEE.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Research on Classification Method of Highway Concrete Water Reducing Agent Manufacturers Based on K-means++ Clustering 11

Research on Classification Method of Highway Concrete Water ...

引用

11th Annual international conference on Material Science and Environmental engineering, MSEE 2023

作者： Ye, Haolong Fang, Shaohong Zhang, Qun School of Software Engineering Huazhong Univ. of Sci. & Tech Wuhan China

Concrete water reducing agent is an important admixture in the preparation of concrete. Machine learning has a wide range of applications in the field of material science. In this paper, machine learning is creatively applied to the classification of water reducing agent manufacturers. this is because the act of categorizing water reducing agent supply manufacturers in practical engineering relies heavily on the experience of experts, which makes it more difficult to find similar alternative manufacturers when the water reducing agent is out of stock. In order to solve this kind of problem, this paper first performs data cleaning on the original data, a total of 72-dimensional eigenvalues are selected, and missing value processing and standardization are performed to normalize the dataset. Afterwards, the K-means++ algorithm is used to analyze the clustering of manufacturers, and the optimal K value is selected by introducing three evaluation indexes, such as Silhouette Coefficient, and the optimal clustering effect is obtained when K is 3. At this time, when the manufacturers of a certain class are out of stock, similar manufacturers can be found for the replacement of the goods. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： K-means clustering

来源：评论

学校读者我要写书评

暂无评论

ATS-DDS: A General Alternating Training Strategy for Dual-Domain Sparse-view CT Reconstruction 11

ATS-DDS: A General Alternating Training Strategy for Dual-Do...

引用

11th international Symposium on Precision Mechanical Measurements

作者： Zihan, Deng Zhisheng, Wang Legeng, Lin Shunli, Wang Junning, Cui Center of Ultra-precision Optoelectronic Instrument Engineering Harbin Institute of Technology Harbin China Key Lab of Ultra-precision Intelligent Instrumentation Harbin Institute of Technology Harbin Ministry of Industry and Information Technology Harbin China

ISBN: (纸本)9781510680296

Sparse scanning methods are widely used to reduce the harmful effects of radiation doses on the human body. Recently, deep learning methods have been widely used for challenging reconstruction tasks such as sparse angles, while dual domain methods have natural advantages because they can handle information in both the sinusoidal and image domains. However, the existing methods in both fields do not pay enough attention to the allocation and strategy of training costs in both fields, but instead use the same training resources for unified training. To address this issue, this article designs a universal training strategy that can adapt to various network model structures: a general alternating training strategy for dual-domain sparse-view CT reconstruction (ATS-DDS) and conducts simulation experiments on various classic networks and the latest deep learning models. the results indicate that alternating training in dual-domain training scenarios can reduce the overall resources of network training and accelerate network training. At the same time, appropriately increasing information exchange between the two fields is beneficial for accelerating network training. © 2024 SPIE.

关键词： Image restoration Computed tomography CT reconstruction Deep learning Tunable filters data modeling Matrices Performance modeling Network architectures

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 << < 100 101 102 103 104 105 106 107 108 109 > >>

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：