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641-650 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：

Security Risk Management System for the Construction and Operation of Smart Port Area Based on BP Neural Network Algorithm 3

Security Risk Management System for the Construction and Ope...

引用

3rd international conference on machine learning and Big data Analytics for IoT Security and Privacy, SPIoT2023

作者： Cui, Di Sun, Guoqing Zhan, Xiaotiao Safety and Environmental Protection Division China Waterborne Transportation Research Institute Beijing China

With the construction of smart cities, smart ports are developing rapidly, providing favorable conditions for enhancing port competitiveness, promoting industrial upgrading, and economic transformation. With the continuous progress of society and science and technology, the safety risks of intelligent ports are also increasing. In order to better address these risks, it is necessary to establish a stable and efficient management system. This paper applies data mining and fuzzy control theory technologies for large-volume, high-precision real-time information collection, based on the research of the BP neural network algorithm. By establishing and analyzing a safety risk management system model based on the BP multilayer neuron network, it provides a rationality evaluation method and design concept. After designing the safety risk management system, this paper conducts a performance test on the system. The test results show that through optimization, the accuracy, generalization ability, and reliability of the model can be improved. Its accuracy is as high as 92% or more, fully demonstrating the system's reliability and superiority! © 2023 Elsevier B.V.. All rights reserved.

关键词： data mining

来源：评论

学校读者我要写书评

暂无评论

Spatial data Analytics for Regional Planning Using GIS and RS Technologies 1

引用

3rd international conference on Artificial-Business Analytics, Quantum and machine learning: Trends, Perspectives, and Prospects, Com-IT-Con 2023

作者： Dahiya, Mamta Khushpal Kumar, Narender MRIIRS Faridabad India SGT University Gurugram India Geo Solutions Gurgaon India

ISBN: (数字)9789819748600

ISBN: (纸本)9789819748594

The modern tools and technologies, i.e., GeoAI, Drones, DGPS, and GIS platforms are being used to digitize all the villages of whole India and will be digitally mapped very soon. The process is in continuation and various organizations are playing a vital role to be a part of this Digital India project and continuously working in their respective areas to achieve it. These digital maps will be integrated with all the spatial and non-spatial information about our nation. Spatial data analytics is a technique that is used to analyze, predict, and plan geospatial data for multiple purposes by adding time and location stamps. It can be related to the demographic assessment, land-use and land cover pattern analysis, road networks, agriculture, weather analysis, forestry, and many more. Currently, in this paper, we are focusing on how spatial analytics is helpful for planning and decision-making at different levels of stake holders. Research work is carried out through a case study of Nalanda regional area using GIS technologies. Different land-use and land cover pattern are identified over the time and are superimposed on satellite images of that area to check the quality and accuracy of prediction that will be used for regional planning of study area. This work also emphasis on, "how this technology is strongly contributed to the project Digital India with speed and accuracy" particularly for regional or urban planning. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： data accuracy

来源：评论

学校读者我要写书评

暂无评论

3rd Workshop on Online and Adaptive Recommender Systems (OARS) 23

3rd Workshop on Online and Adaptive Recommender Systems (OAR...

引用

29th ACM SIGKDD conference on Knowledge Discovery and data mining (KDD)

作者： Cui, Xiquan Dave, Vachik Su, Yi Al-Jadda, Khalifeh Kumar, Srijan McAuley, Julian Yet, Tao Guo, Stephen D. Huyen, Chip Home Depot Atlanta GA 30301 USA Walmart Labs Sunnyvale CA USA Univ Calif Berkeley Berkeley CA USA Google New York NY USA Georgia Inst Technol Atlanta GA 30332 USA Univ Calif San Diego San Diego CA USA Amazon San Francisco CA USA Indeed San Francisco CA USA Claypot AI San Francisco CA USA

ISBN: (纸本)9798400701030

Recommender systems (RecSys) play important roles in helping users navigate, discover, and consume large and highly dynamic information. Today, many RecSys solutions deployed in the real world rely on categorical user-profiles and/or pre-calculated recommendation actions that stay static during a user session. However, recent trends suggest that RecSys need to model user intent in real time and constantly adapt to meet user needs at the moment or change user behavior in situ. There are three primary drivers for this emerging need of online adaptation. First, in order to meet the increasing demand for a better personalized experience, the personalization dimensions and space will grow larger and larger. It would not be feasible to pre-compute recommended actions for all personalization scenarios beyond a certain scale. Second, in many settings the system does not have user prior history to leverage. Estimating user intent in real time is the only feasible way to personalize. As various consumer privacy laws tighten, it is foreseeable that many businesses will reduce their reliance on static user profiles. Therefore, it makes the modeling of user intent in real time an important research topic. Third, a user's intent often changes within a session and between sessions, and user behavior could shift significantly during dramatic events. A RecSys should adapt in real time to meet user needs and be robust against distribution shifts. The online and adaptive recommender systems (OARS) workshop offers a focused discussion of the study and application of OARS, and will bring together an interdisciplinary community of researchers and practitioners from both industry and academia. KDD, as the premier data science conference, is an ideal venue to gather leaders in the field to further research into OARS and promote its adoption. This workshop is complementary to several sessions of the main conference (e.g., recommendation, reinforcement learning, etc.) and brings them togethe

关键词： data science recommender system machine learning artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

SmartBlend: Smart Video Recommendations on YouTube

SmartBlend: Smart Video Recommendations on YouTube

引用

Applied Artificial Intelligence and Computing (ICAAIC), international conference on

作者： Kulvinder Singh Aditya Kumar Maurya Drishti Solanki Dept of Computer Science & Engineering Chandigarh University Mohali Punjab India

ISBN: (数字)9798350375190

ISBN: (纸本)9798350375206

In the dynamic era of online education, the pursuit of a personalized and effective learning experience is paramount. A transformative approach in online education by integrating Multimodal data mining and data Synthesis to develop a Smart System for learning Video Recommendations. With a focus on Personalized learning and Adaptability, the methodology employs advanced techniques like Multimodal learning Analytics and machine learning for a comprehensive analysis of learning materials. SmartBlend introduces a novel approach to personalized learning video recommendations on YouTube, leveraging Multimodal data mining and data Synthesis. The SmartBlendEdu framework employs advanced techniques like Multimodal learning Analytics and machine learning for a comprehensive analysis of learning materials.

关键词： Video on demand Social networking (online) Semantics Education learning (artificial intelligence) Tagging data mining

来源：评论

学校读者我要写书评

暂无评论

The Integration of Stream data Models in Modern Transportation Networks 3

The Integration of Stream Data Models in Modern Transportati...

引用

3rd IEEE international conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Naval, Preeti Jain, Sandeep Kumar Krishna, K. Gopala Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Electrical Engineering Jaipur India Faculty of Engineering and Technology Department of Electronics and Communication Engineering Karnataka562112 India

ISBN: (纸本)9798350343274

The study proposal proposes an innovative strategy for managing modern transport networks, with an emphasis on the coordinated use of analytics, real-time data processing, and dynamic decision-making utilizing stream data models. To create a solid infrastructure for real-time data analysis, it is required to use a diverse set of data sources, such as sensors, GPS devices, traffic cameras, and mobile application software. A strategy for reaching this goal is described below. The real-time system that integrates transportation models, artificial intelligence, and data mining is at the core of this strategy. In addition to monitoring and assessment, one of the key responsibilities of this system is to develop the transportation network. Without this framework as a foundation, the method would be worthless. This collaborative effort provides proactive traffic control, efficient route planning, and event prediction in real time. The application of machine learning in predictive analytics and traffic analysis, which together give solid traffic forecasts, prompts the creation of tactics that cut wait times and enhance productivity. Event detection algorithms are critical for ensuring commuter safety and reducing wait times in the event of an emergency. Using cloud-hosted data processing technologies, the idea manages massive amounts of real-time data. This is critical for data collection, processing, and storage methods. Finally, we believe that the development of an intelligent transportation networkone that can continually learn, adapt, and drive itselfwill result in less traffic, more safety, shorter travel times, and environmentally friendly legislation and practices. To address the ever-increasing demands placed on dynamic urban settings, it is believed that the technique developed would transform current transport networks into more responsive, user-friendly, and efficient systems. © 2023 IEEE.

关键词： Real time systems

来源：评论

学校读者我要写书评

暂无评论

A Real-time Visual Target Detection and Automatic Tracking Algorithm Based on YOLOv3 and DWSiamRPN 3

A Real-time Visual Target Detection and Automatic Tracking A...

引用

3rd international conference on pattern recognition and machine learning, PRML 2022

作者： Zhong, Yexiu Qiu, Senhui Zhao, Zhipeng He, Fuyun Guilin Institute of Information Technology School of Electronic Engineering Guilin China Guangxi Normal University School of Electronic Engineering Guilin China

ISBN: (数字)9781665499507

ISBN: (纸本)9781665499507

The current single-target trackers cannot detect the categories of the targets, and multi-object trackers have low performances due to the missed and false detections. Most of these trackers do not have the capabilities for the interesting target selections. To overcome these problems, a real-time visual target detection and automatic tracking algorithm is proposed. First, the video image is detected by using YOLOv3. Then the interesting target is obtained by the proposed intelligent selection strategy. Finally, the selected target is tracked in real-time by the Deeper and Wider Siamese Networks (DWSiamRPN). Experiments show that the proposed YOLOv3-DWSiamRPN method can effectively detect, automatically obtain and track targets in real-time (26 frames per second), with 55.5 mean Average Precision (mAP) on COCO dataset, 0.296 Expect Average Overlaprate (EAO) on VOT-2017 and 0.66 Area Under Curve (AUC) on OTB-2015, respectively. Furthermore, it also addresses the problems of short-term and long-term target losses. © 2022 IEEE.

关键词： Target tracking

来源：评论

学校读者我要写书评

暂无评论

Shop Signboards Detection Using the ShoS dataset 3rd

Shop Signboards Detection Using the ShoS Dataset

引用

3rd international conference on pattern recognition and Artificial Intelligence, ICPRAI 2022

作者： Almuhajri, Mrouj Suen, Ching Y. Centre for Pattern Recognition and Machine Intelligence Concordia University MontrealQCH3G 2W1 Canada Department of Computer Science Saudi Electronic University Riyadh Saudi Arabia

ISBN: (纸本)9783031092817

This work was driven by the possibility of enabling beneficial applications for humans and municipal agencies utilizing deep learning techniques to detect shop signboards. data is the foundation of successful AI-based applications. Despite the abundance of data, providing datasets for such applications is a challenge as they have to be refined and characterized accurately for better performance. This paper describes the process of collecting the ShoS dataset from Google Street Views for the detection of the signboards of shops on streets. A total of 10k storefront signboards were captured and fully annotated within 7500 images. The ShoS datasets were tested by running different baseline methodology using one-stage detectors YOLO and SSD. Out of the tested methods and variances, the YOLOv3 yields the highest performance reaching 94.23% (mAP@0.5). © 2022, Springer Nature Switzerland AG.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis for Chronic Disease Prediction using Various data mining Techniques 3

Performance Analysis for Chronic Disease Prediction using Va...

引用

3rd international conference on Electronics and Sustainable Communication Systems, ICESC 2022

作者： Rajeashwari, S. Arunesh, K. Research Department of Computer Science Tamil Nadu Sattur India

ISBN: (数字)9781665479714

ISBN: (纸本)9781665479714

Early detection of chronic disease is crucial for increasing patient quality of life and lowering treatment costs. As a result, being able to predict these illnesses is critical. This study aims to identify chronic disease datasets (diabetes, heart disease, kidney disease, and breast cancer) in order to predict the beginning of the condition and provide patients with appropriate treatment options. The main purpose of this project is to use machine learning and Deep learning techniques including Logistic Regression, Naïve Bayes, Support Vector machine, K-Nearest Neighbor, Decision Tree, Random Forest, XGBoost, and Neural Network to predict chronic disease in individual patients. Among these several algorithms, the algorithm that gives more accuracy to predict chronic diseases in individual patients can be identified. Finally, an experimental study of the proposed work with various algorithms has been demonstrated in this paper. Chronic diseases such as heart disease, kidney disease, breast cancer, and diabetes are all predicted using these methods. © 2022 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Implementation of machine learning Algorithms For Human Activity recognition 3

Implementation of Machine Learning Algorithms For Human Acti...

引用

3rd international conference on Signal Processing and Communication (ICPSC)

作者： Vijayvargiya, Ankit Kumari, Nidhi Gupta, Palak Kumar, Rajesh Malviya Natl Inst Technol Dept Elect Engn Jaipur Rajasthan India Swami Keshvanand Inst Technol Dept Elect Engn Jaipur Rajasthan India

ISBN: (纸本)9781665428644

Human Activity recognition (HAR) is technically the problem of forecasting an individual's actions based on evidence of their gesture using sensors functioning as accelerometer and gyroscope. It plays a major role in contrasting sectors such as personal biometric signature, daily life monitoring, anti-terrorists along with anti-crime securities, medical-related applications, and so on. These days, smart phones are well-resourced with leading processors and built-in sensors. This comes up with the possibility to unfold a new arena of data mining. This paper signifies the analysis of HAR focused on data composed via accelerometer sensors of smart phones. Further, it illustrates the use of time-domain features which are acquired with the help of a windowing approach termed as overlapping. It is accompanied by a window size of 250ms along with overlapping of 25%. Numerous machine learning classifiers such as k-nearest neighbors, linear discriminant analysis, bagging classifier, gradient boosting classifier, decision tree, random forest, and support vector machine using three different kernels were practiced. The outcomes exhibit that random forest with 5-fold cross-validation imparts the highest accuracy (92.71%) in recognition of human activities.

关键词： Human Activity recognition machine learning Overlapping Windowing Feature Extraction

来源：评论

学校读者我要写书评

暂无评论

3rd international conference on machine Intelligence and Smart Systems, MISS 2023

3rd International Conference on Machine Intelligence and Sma...

引用

3rd international conference on machine Intelligence and Smart Systems, MISS 2023

ISBN: (纸本)9783031317224

The proceedings contain 59 papers. The special focus in this conference is on machine Intelligence and Smart Systems. The topics include: Chronic Kidney Disease Prediction and Interpretation Using Explainable AI;systematic Review and Analysis of Artificial Intelligence-Based Breast Cancer Classification and Detection;war of Tweets: Sentiment Analysis on Ukraine Russia Conflict;Implementing HRRN for Evaluating Cloud Performance Using Reinforcement learning;using machine learning for Prediction of Obstructions for Indoor Location Systems;privacy Threats and Protection in Artificial Intelligence and machine learning;Combining Linguistic Information with BERT for Span Based End-to-End Aspect Based Sentiment Analysis;a Dimensionality Reduction Model: A Retrospective Approach on Dementia Triggering Parameters and Feature Ranking;effective Identification of Lung Diseases Using Few-Shot learning;comparative Study on Classification Based-data mining Techniques in Early Diabetes Prediction;optimize machine learning Model for Sentiment Analysis of Online Education During Covid-19 Pandemic;review on the Challenges and Future Directions of Deep learning-Based Techniques for Advance Prediction of Cardiac Attack;different Techniques for Detecting Plant Leaf Disease Using machine learning;proposed Framework of Extensive Humanoid Design Cycle and Recent Developments in Bipedal Walk;natural Language Processing for Waste Management Using Public Opinions in Smart Cities;prediction of Diabetes During Pregnancy Through Fog Environment;empirical Wavelet Transform Grounded Poignant Ground Target recognition and Classification by Seismic Signal Processing;A Powered-Up Classification of Disabling Distributed Network Cloud-Based Attacks Using MLPNN-BP and MLPNN-LM;stroke Prediction Framework Based on Missing Value Information and Outlier Detection by Using machine learning Techniques in E-Healthcare;magnetic Resonance Imaging Digitization for Brain Abnormality recognition.

关键词：

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 << < 61 62 63 64 65 66 67 68 69 70 > >>

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：