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

3,117 篇 会议
141 册 图书
24 篇 期刊文献

馆藏范围

3,281 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,141 篇 工学
- 1,954 篇 计算机科学与技术...
- 1,095 篇 软件工程
- 405 篇 信息与通信工程
- 287 篇 电气工程
- 267 篇 生物工程
- 217 篇 控制科学与工程
- 172 篇 生物医学工程（可授...
- 79 篇 化学工程与技术
- 73 篇 光学工程
- 72 篇 机械工程
- 68 篇 仪器科学与技术
- 65 篇 电子科学与技术（可...
- 62 篇 安全科学与工程
- 55 篇 动力工程及工程热...
- 54 篇 网络空间安全
777 篇 理学
- 430 篇 数学
- 296 篇 生物学
- 151 篇 统计学（可授理学、...
- 147 篇 物理学
- 127 篇 系统科学
- 90 篇 化学
505 篇 管理学
- 306 篇 图书情报与档案管...
- 231 篇 管理科学与工程(可...
- 95 篇 工商管理
218 篇 医学
- 193 篇 临床医学
- 125 篇 基础医学(可授医学...
- 87 篇 药学(可授医学、理...
- 55 篇 公共卫生与预防医...
72 篇 法学
- 70 篇 社会学
52 篇 教育学
- 47 篇 教育学
35 篇 经济学
31 篇 农学
6 篇 艺术学
4 篇 军事学
1 篇 文学

主题

568 篇 data mining
542 篇 machine learning
241 篇 pattern recognit...
195 篇 deep learning
174 篇 feature extracti...
154 篇 artificial intel...
153 篇 support vector m...
113 篇 accuracy
113 篇 machine learning...
111 篇 training
93 篇 data models
80 篇 neural networks
77 篇 data mining and ...
65 篇 classification
62 篇 sentiment analys...
61 篇 classification a...
59 篇 big data
57 篇 predictive model...
50 篇 face recognition
48 篇 prediction algor...

机构

7 篇 maharishi school...
6 篇 guangdong univer...
5 篇 galgotias univer...
5 篇 centre of interd...
5 篇 pune
5 篇 chitkara univers...
5 篇 uttaranchal univ...
5 篇 uttaranchal inst...
5 篇 institute of aut...
4 篇 shanghai jiao to...
4 篇 chitkara univers...
4 篇 school of inform...
4 篇 indian statistic...
4 篇 south china univ...
4 篇 zhejiang univers...
4 篇 maharishi school...
4 篇 department of cs...
4 篇 university of ca...
4 篇 school of comput...
4 篇 department of co...

作者

9 篇 de-shuang huang
7 篇 coenen frans
7 篇 venkatesh svetha
7 篇 petra perner
7 篇 tianrui li
6 篇 ryszard tadeusie...
6 篇 marcin korytkows...
6 篇 jacek m. zurada
6 篇 krasotkina olga
6 篇 lotfi a. zadeh
6 篇 mottl vadim
6 篇 leszek rutkowski
5 篇 vitoantonio bevi...
5 篇 sankar k. pal
4 篇 waiyamai kitsana
4 篇 sozo inoue
4 篇 sergei o. kuznet...
4 篇 duoqian miao
4 篇 shengli xie
4 篇 hepu deng

语言

3,063 篇 英文
209 篇 其他
38 篇 中文
1 篇 西班牙文
1 篇 土耳其文

检索条件"任意字段=3rd International Conference on Machine Learning and Data Mining in Pattern Recognition"

共 3282 条记录，以下是1001-1010 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：

Analysis of Student learning pattern in learning Management System (LMS) using Heuristic mining a Process mining Approach 3

Analysis of Student Learning Pattern in Learning Management ...

引用

3rd international conference on Electronics Representation and Algorithm, ICERA 2021

作者： Chanifah, Sabila Andreswari, Rachmadita Fauzi, Rokhman Telkom University School of Industrial Engineering Information System Department Bandung Indonesia

ISBN: (纸本)9781665434003

The COVID-19 pandemic has had a significant impact on educational organizations, one of which is the Telkom University educational institute. Telkom University using learning Management System (LMS) during pandemic covid-19. The use of an LMS will have a huge number of data records stored in the form of event logs. Opportunities to process data recorded in event logs must be maximized to improve Telkom University's LMS continuously. In this study, the process mining method conducted using event logs from Website Application Development (WAD) and Enterprise System (ES) courses to compare student learning patterns between programming courses and non-programming courses. Process mining conducted using PROM 5.2 and the Heuristic Miner plugins. The modeling process uses a heuristic miner algorithm because of its ability to present the main behavior recorded in the event log well by analyzing conformance checking. The result of conformance checking shows a fitness value of 0.887 for WAD and 0.847 for ES. It means the process model can represent the event log well. WAD's value of advanced behavioral appropriateness and degree of model flexibility are 0.594 and 0.411, whereas ES 0.181 and 0.155. The value of the structure shows 1.0 for the two subjects. After obtaining a process model, the next step is to analyze student learning patterns based on the frequency of access to the LMS. With this research, it is hoped that this research can contribute to adding new insights regarding the use of event logs in the field of education and knowing the activities carried out by students through LMS learning media, as well as providing visualization of student behavior patterns in the LMS (learning Management System) of Telkom University. © 2021 IEEE.

关键词： Miners

来源：评论

学校读者我要写书评

暂无评论

Object Size Prediction from Hand Movement Using a Single RGB Sensor 3rd

Object Size Prediction from Hand Movement Using a Single RGB...

引用

3rd international conference on Artificial Intelligence in HCI (AI-HCI) Held as Part of the 24th international conference on Human-Computer Interaction (HCII)

作者： Dagioglou, Maria Soulounias, Nikolaos Giannakopoulos, Theodoros Natl Ctr Sci Res Demokritos Neapoleos 27 & Patriarchou Grigoriou E Aghia Paraskevi 15341 Attica Greece Natl & Kapodistrian Univ Athens Ilissia 15772 Attica Greece

ISBN: (纸本)9783031056437;9783031056420

Human intention prediction is essential, among others, for safe and fluent human-robot collaboration. Prediction of the intention from human movement offers the advantage of a context-free paradigm. Naturally, such robot capabilities require high spatial and temporal resolution. While certain sensing devices, such as the motion capture systems, satisfy these requirements, in many applications visual sensors might be preferable. However, the information regarding human movement from RGB-D cameras is noisy and of lower frequency. In the present work, we study if it is possible to predict human intentions from hand movements observed by a single RGB-D sensor. We collected data from eight participants as they were grasping objects of three different sizes. OpenPose was used to extract the 2D hand and arm joint pixel coordinates that were then processed to extract human movement kinematic information and engineer appropriate features. Traditional machine learning methods were applied to evaluate the usability of our dataset. Overall, the results were significantly above chance level and showed that it is possible to predict the size of the object a human intents to grasp using hand kinematics extracted from a single visual sensor. Finally, it is feasible, under certain conditions, to use this prediction in real-time human-robot collaboration.

关键词： Human action prediction Human intention recognition User studies datasets machine learning Robot vision Human-robot interaction Human-robot collaboration

来源：评论

学校读者我要写书评

暂无评论

Sliding Window-Based Anomaly Detection

Sliding Window-Based Anomaly Detection

引用

3rd international conference on machine learning and data Engineering, ICMLDE 2024

作者： Farheen Kumar, Rajeev Lab School of Computer & Systems Sciences Jawaharlal Nehru University New Delhi110 067 India

Anomaly detection is a significant research problem requiring the ability to recognize patterns in data that differ from their original pattern. There are many machine learning and deep learning models for anomaly detection. We are working with k-Nearest Neighbours(kNN), Support Vector machine (SVM), Decision Tree (DT), Long Short Term Memory (LSTM), 1D Convolutional Neural Network with LSTM (CLSTM), and Encoder-Decoder LSTM (ED LSTM). In this work, we have used sliding windows employed with these models. This technique puts the data into slices of the same size and processes them sequentially. We have applied different window sizes [24, 48, 96, 196]. We have compared the performance of our models with or without sliding window-based techniques, analyzed the results, and found that deep learning models' performance increases after applying the sliding window technique. The ED LSTM model has shown the highest performance increase with a sliding window for the Okhla Phase2 dataset;the performance gain is approx. 10 percent. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Electronic Music Type Identification Based on Multimodal learning Optimized Residual Neural Networks

Electronic Music Type Identification Based on Multimodal Lea...

引用

Cloud Computing, Big data Applications and Software Engineering (CBASE), international conference on

作者： Jingying Guo Peng Wang School of Media and Performing Arts Coventry UniversityCoventry CV1 5RW UK Beijing City University Beijing China

ISBN: (数字)9798331506582

ISBN: (纸本)9798331506599

The classification effect of electronic music may be low due to the complexity of its type branches. Therefore, a research on electronic music type identification method based on multimodal learning optimization residual neural network is proposed. This paper analyzes the characteristics of electronic music from three perspectives of short-time energy, time-domain distribution and frequency-domain distribution, divides the original continuous music signal into several short segments (frames), and extracts the corresponding short-time energy, time-domain variance and frequency-domain variance information. In the stage of classification and recognition, the residual module is introduced into the neural network, and three characteristic modes are fitted to determine the final classification results. In the test results, the AUC of the recognition results of rhythmic electronic music and atmospheric electronic music is basically above 0.7, and the minimum value is also above 0.68. On the overall perspective, the AUG mean is 0.0783 and 0.0615 lower than that of the control group, respectively.

关键词： Training Accuracy Frequency-domain analysis Feature extraction User experience Electronic music data mining Time-domain analysis Residual neural networks Software engineering

来源：评论

学校读者我要写书评

暂无评论

Analysis of Changing Trends in Textual data Representation 3rd

Analysis of Changing Trends in Textual Data Representation

引用

3rd international conference on Recent Trends in Image Processing and pattern recognition, RTIP2R 2020

作者： Singh, Ksh. Nareshkumar Dorendro, A. Devi, H. Mamata Mahanta, Anjana Kakoti Department of Computer Science Manipur University Imphal India Department of Computer Science Gauhati University Guwahati India

ISBN: (纸本)9789811605062

The most efficient way to convey human knowledge is through natural language text. In order to manage the exponential growth of digital data, it is high time to build a robust text information system. The system performs various techniques such as classification, clustering, summarization, etc. to organize the huge unstructured text data into well-defined forms. Text representation is the fundamental task in text mining and text retrieval. Just like a backbone gives structure to human body, text representation lays the foundation step for various other downstream tasks of Natural Language Processing (NLP), text mining and text retrieval. This paper concentrates on the analysis of various text representation models and also discusses major changing trends in textual data representation. This paper could be beneficial to those who wish to study and work on text data in NLP domain. The challenges and drawbacks of the existing text representation models are also discussed in this paper. © 2021, Springer Nature Singapore Pte Ltd.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

Automated Helmet Detection and Fine Issuance System Using YOLOv8 & OpenCV

Automated Helmet Detection and Fine Issuance System Using YO...

引用

Intelligent data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： Hirald Dwaraka Praveena Goruva Vardhan Babu Jinka Muni Sai Yateesh Degasikshi Guna Guduru Vamsi Krishna Dept. of ECE Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College) Tirupati India Dept of ECE Sree Vidyanikethan Engineering College Tirupati India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

In densely populated countries like India, traffic violations are a major concern, especially among motorcyclists, leading to accidents and significant loss of life and property. A prevalent issue is the failure to wear helmets. To address this, a system called “Helmet Detection for Motorcyclists using YOLOv8 and OpenCV” is proposed, leveraging deep learning to automatically identify and penalize violators in real-time through traffic cameras. The system employs the You Only Look Once (YOLO) algorithm, a deep neural network-based object detection model, to identify riders without helmets. Subsequently, it detects the number plate of violators, extracting its text using the EasyOCR(Optical Character recognition) library. This extracted data is cross-referenced with a pre-existing database to retrieve the owner's contact details. For automation, an SMS API(Application Programming Interface) is integrated to send fine notifications to the violator's registered mobile number. By encouraging helmet use, the system aims to minimize head injuries during accidents and improve road safety. This automated approach enhances traffic law enforcement, provides evidence of violations, and ensures efficient penalty issuance. Ultimately, the system supports safer roads by promoting compliance with traffic regulations and protecting motorcyclists' lives.

关键词： YOLO Deep learning Helmets Real-time systems Road safety Libraries data models data mining License plate recognition Injuries

来源：评论

学校读者我要写书评

暂无评论

Design and Application of Personalized Recommendation Algorithm for Electricity Marketing

Design and Application of Personalized Recommendation Algori...

引用

data Analytics, Computing and Artificial Intelligence (ICDACAI), international conference on

作者： Yu Yu Lin Bai Xinpo Zhu Hua Liu Tao Zhou Jianbo Wang Beijing China-Power Information Technology Co. Ltd. Beijing China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519049

With the rapid development of the current economy and technology, the electricity consumption behavior of power users has shown an unprecedented trend of diversification, with diverse and rapidly changing demand patterns. To effectively respond to this market change, power companies urgently need to transform and upgrade, and use innovative marketing strategies to accurately meet user needs, improve service quality, and enhance market competitiveness. In response to the significant drawbacks of traditional power marketing methods, such as rigid strategies, difficulty in accurately matching personalized user needs, uneven distribution of power resources, and serious waste, this article explores and proposes a personalized recommendation algorithm for power marketing based on big data analysis and artificial intelligence (AI) technology. This algorithm utilizes advanced machine learning (ML) models to achieve precise prediction of users' electricity habits, preferences, and future demand through deep mining of massive user electricity data. The experimental results show that the algorithm proposed in this paper performs well in improving user satisfaction and enhancing user stickiness, while significantly reducing the operating costs of power enterprises and reducing resource waste, providing strong support for the sustainable development of the power industry.

关键词： data privacy machine learning algorithms Costs Electricity Biological system modeling Big data Prediction algorithms Power industry data models Sustainable development

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Deep learning Model for Violence Detection

A Hybrid Deep Learning Model for Violence Detection

引用

Intelligent data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： S Chandira Prabha S Kaviyadharshini A Annie Micheal Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

Current violence detection systems often face challenges such as high computational costs, real-time processing difficulties, and limited precision in detecting violent activities in dynamic environments. This research addresses these issues by proposing a hybrid deep learning model that integrates MobileNetV2 for efficient spatial feature extraction and ConvLSTM (Convolutional Long Short-Term Memory) for capturing temporal patterns. The model effectively discriminates between aggressive and non-aggressive behaviours in real-time video streams. Using the Kaggle Violence dataset, which comprises 1,000 video clips of violent and non-violent activities, the system achieved an accuracy of 96%, showcasing its high performance. Additionally, an integrated alert system enhances practical application by sending real-time notifications via a Telegram bot, including details such as location, timestamp, and camera ID. This solution ensures timely responses to violent incidents, addressing the core issues of computational efficiency and real-time precision, while offering scalability and applicability in diverse scenarios.

关键词： Training Accuracy Computational modeling Streaming media Feature extraction Real-time systems data models Computational efficiency pattern recognition Streams

来源：评论

学校读者我要写书评

暂无评论

Fake News Detection of Live Media using Speech to Text Conversion 3

Fake News Detection of Live Media using Speech to Text Conve...

引用

3rd IEEE international Virtual conference on Innovations in Power and Advanced Computing Technologies, i-PACT 2021

作者： Dixit, Yashashwini Sanjay, Aiswarya Kaarthik, E. Shridevi, S. Center for Advanced Data Science Vellore Institute of Technology Chennai India

ISBN: (纸本)9781665426916

A made-up tale with the goal to deceive or mislead is characterized as fake news. After translating the live media stream audio into text, detecting false news using machine learning techniques are used to solve the problem. The aim of this work is to create a model that can detect false news by identifying the most optimal parameter that can yield the greatest accuracy. Additional investigation on how different hyper parameters affect the performance of the model and summed up the details for future work. The work emphasizes various kinds of classifiers as well as Speech recognition techniques which could be used. It gives an understanding of which classifier is better suited for Real time Fake News Detection. Two different kinds of Speech recognition techniques have been identified and have been incorporated. These act as the input for the machine learning Model. This is then followed by data pre-processing, and passed onto various classifiers which would then identify whether the news retrieved is fake or not. © 2021 IEEE.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

A Novel Secure Vector Product for Protecting the Privacy of data in Vertically Partitioned dataset 3rd

A Novel Secure Vector Product for Protecting the Privacy of ...

引用

3rd international conference on machine learning, Advances in Computing, Renewable Energy and Communication, MARC 2021

作者： Sharma, Vibhor Bhushan, Shashi Singh, Anuj Kumar Kumar, Pramod HSST Swami Rama Himalayan University Dehradun India School of Computer Science University of Petroleum and Enegy Studies Dehradun India Krishna Engineering College Ghaziabad India

ISBN: (纸本)9789811928277

The contemporary advancements in the field of data collecting, storage and networking have resulted in data being saved and kept at many locations. data mining methods allow hidden knowledge to be extracted from massive data sources. data on the centralized server are not always present. data might be obtained at individual or several places. data are divided vertically, horizontally or at both sites and disseminated between places. The sharing of data repositories existing at many stages in the mining process leads to discomfort in data privacy. data mining protection is a technology that prevents sensitive information from being disclosed to others during a mining operation. Simple multiparty calculations and anonymization are the most common privacy protecting technology for data mining. Secure multiparty (SMC) computing allows parties to do distributed data mining activities in separate places without disclosing more personal data. The SMC protocol employs mostly encryptions that offer high security and enhance the complexity of protocols. Before it is utilized for mining, perturbation alters the original sensitive data. Distortion of the data may diminish the mining performance accuracy to decrease the usefulness. A novel vector scalar product is suggested to save execution time and to protect privacy data privacy in the vertically partitioned dataset, retaining the induction of decision tree. A downward approach to the safe scalar product is taken. Each node is a radix or fewer party groups. The binary vector is divided as well. Each group discovers a safe sum of binary vectors with the secret sharing of Shamir. The running time of the CPU was established between sequences and when running downstream. The execution time was determined. The proposed bottom-up approach results in comparison with following sequential approach. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Decision trees

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329页 << < 97 98 99 100 101 102 103 104 105 106 > >>

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：