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

2,938 篇 会议
174 册 图书
25 篇 期刊文献

馆藏范围

3,136 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,026 篇 工学
- 1,813 篇 计算机科学与技术...
- 948 篇 软件工程
- 329 篇 电气工程
- 312 篇 信息与通信工程
- 214 篇 控制科学与工程
- 207 篇 生物工程
- 149 篇 生物医学工程（可授...
- 70 篇 光学工程
- 64 篇 机械工程
- 61 篇 化学工程与技术
- 50 篇 电子科学与技术（可...
- 48 篇 仪器科学与技术
- 42 篇 安全科学与工程
- 35 篇 交通运输工程
644 篇 理学
- 350 篇 数学
- 244 篇 生物学
- 138 篇 物理学
- 134 篇 统计学（可授理学、...
- 95 篇 系统科学
- 62 篇 化学
399 篇 管理学
- 240 篇 图书情报与档案管...
- 176 篇 管理科学与工程(可...
- 76 篇 工商管理
261 篇 医学
- 240 篇 临床医学
- 122 篇 基础医学(可授医学...
- 74 篇 药学(可授医学、理...
- 39 篇 公共卫生与预防医...
43 篇 法学
- 40 篇 社会学
37 篇 教育学
- 31 篇 教育学
31 篇 经济学
- 29 篇 应用经济学
23 篇 农学
6 篇 艺术学
4 篇 文学

主题

572 篇 machine learning
563 篇 data mining
320 篇 pattern recognit...
202 篇 deep learning
201 篇 feature extracti...
154 篇 support vector m...
145 篇 artificial intel...
128 篇 machine learning...
120 篇 training
116 篇 accuracy
90 篇 data models
89 篇 data mining and ...
71 篇 neural networks
71 篇 classification
67 篇 predictive model...
66 篇 face recognition
61 篇 learning systems
52 篇 computer imaging...
50 篇 convolutional ne...
48 篇 classification a...

机构

9 篇 school of comput...
9 篇 chinese academy ...
8 篇 zhejiang univers...
8 篇 chitkara univers...
7 篇 guangdong univer...
7 篇 school of inform...
6 篇 xi'an university...
6 篇 indian statistic...
6 篇 central south un...
6 篇 department of co...
6 篇 unsw sydney
6 篇 xi'an university...
6 篇 southern univers...
5 篇 study group aust...
5 篇 peking universit...
4 篇 centre for patte...
4 篇 chongqing univer...
4 篇 national laborat...
4 篇 sun yat sen univ...
4 篇 school of inform...

作者

11 篇 de-shuang huang
8 篇 petra perner
7 篇 krasotkina olga
7 篇 mottl vadim
7 篇 ying tan
6 篇 zheng-guang wu
6 篇 ryszard tadeusie...
6 篇 marcin korytkows...
6 篇 phung dinh
6 篇 venkatesh svetha
6 篇 hongyi li
6 篇 jacek m. zurada
6 篇 chaojie li
6 篇 biao luo
6 篇 ilias maglogiann...
6 篇 lotfi a. zadeh
6 篇 leszek rutkowski
6 篇 lazaros iliadis
6 篇 long cheng
5 篇 vitoantonio bevi...

语言

3,044 篇 英文
79 篇 其他
19 篇 中文
1 篇 土耳其文

检索条件"任意字段=5th International Conference on Machine Learning and Data Mining in Pattern Recognition"

共 3137 条记录，以下是181-190 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：

Dynamic data Augmentation with Gating Networks for Time Series recognition 26

Dynamic Data Augmentation with Gating Networks for Time Seri...

引用

26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)

作者： Oba, Daisuke Matsuo, Shinnosuke Iwana, Brian Kenji Kyushu Univ Dept Adv Informat Technol Fukuoka Japan

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

data augmentation is a technique to improve the generalization ability of machine learning methods by increasing the size of the dataset. However, since every augmentation method is not equally effective for every dataset, you need to select an appropriate method carefully. We propose a neural network that dynamically selects the best combination of data augmentation methods using a Gating Network and a mutually beneficial feature consistency loss. the Gating Network is able to control how much of each data augmentation is used for the representation within the network. the feature consistency loss gives a constraint that augmented features from the same input pattern should be in similar. In the experiments, we demonstrate the effectiveness of the proposed method on the 12 largest time-series datasets from 2018 UCR Time Series Archive and reveal the relationships between the data augmentation methods through analysis of the proposed method.

关键词： Histograms Analytical models Time series analysis Neural networks Radar machine learning pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Enhanced Approaches to Kingfisher Species Identification Using machine learning and Deep learning 5

Enhanced Approaches to Kingfisher Species Identification Usi...

引用

5th international conference on Advanced Research in Computing, ICARC 2025

作者： Vidanagamachchi, C.S. Chathuranga, W.G.D. Chathuranga, L.L.G. Jayathilake, K.T.A.S. Yeshani, R.B. Vidanagamachchi, S.M. University of Ruhuna Dept. of Computer Science Matara Sri Lanka University of Ruhuna Dept. of Zoology Matara Sri Lanka

ISBN: (纸本)9798331530983

this study addresses the critical challenge of bird species recognition within the domains of deep learning, emphasizing its significant ecological and conservation implications. Focusing on Sri Lanka's avian biodiversity, particularly the Kingfisher family, this research systematically analyzes bird identification methodologies. the methodology encompasses data collection, pre-processing, feature extraction, classification, and analysis of results. the study employs various deep learning models, including VGG16, VGG19, SVM, a custom CNN, and a hybrid CNN-SVM model. the custom CNN model, specifically optimized for kingfisher species identification, achieved a testing accuracy of 81.21%, outperforming traditional models. However, the hybrid CNN-SVM model demonstrated slightly lower testing accuracy at 79.35%. these findings highlight the effectiveness of the proposed deep learning models in identifying Kingfisher species, particularly when dealing with complex variations in plumage and environmental factors. the results indicate that the custom CNN model is highly reliable for ornithological applications, especially for nonspecialists. the research highlights the complexity of Kingfisher species identification and underscores the critical role of advanced machine learning techniques in addressing these challenges. the findings have significant implications for wildlife conservation, enabling enhanced monitoring and preservation of bird populations. Additionally, the results reveal the potential for developing a mobile application for bird species recognition, particularly for Kingfishers, addressing the lack of existing computer-based identification solutions. © 2025 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption 26

Discovery of New Multi-Level Features for Domain Generalizat...

引用

26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)

作者： Frikha, Ahmed Krompass, Denis Tresp, Volker Siemens Technol Mumbai Maharashtra India Univ Munich LMU Munich Germany

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

machine learning models that can generalize to unseen domains are essential when applied in real-world scenarios involving strong domain shifts. We address the challenging domain generalization (DG) problem, where a model trained on a set of source domains is expected to generalize well in unseen domains without any exposure to their data. the main challenge of DG is that the features learned from the source domains are not necessarily present in the unseen target domains, leading to performance deterioration. We assume that learning a richer set of features is crucial to improve the transfer to a wider set of unknown domains. For this reason, we propose COLUMBUS, a method that enforces new feature discovery via a targeted corruption of the most relevant input and multi-level representations of the data. We conduct an extensive empirical evaluation to demonstrate the effectiveness of the proposed approach which achieves new state-of-the-art results by outperforming 18 DG algorithms on multiple DG benchmark datasets in the DOMAINBED framework.

关键词： Training machine learning Benchmark testing data models pattern recognition

来源：评论

学校读者我要写书评

暂无评论

5th international conference on Advances in Information Communication Technology and Computing, AICTC 2024

5th International Conference on Advances in Information Comm...

引用

5th international conference on Advances in Information Communication Technology and Computing, AICTC 2024

ISBN: (纸本)9789819761050

the proceedings contain 86 papers. the special focus in this conference is on Advances in Information Communication Technology and Computing. the topics include: Universal Representation theory—Rigour II;revolutionizing Smart Cities: A data-Driven Traffic Monitoring System for Real-Time Traffic Density Estimation and Visualization;Assessing the Influence of Self-service Technology on WOM: the Role of Customer Satisfaction;Universal Representation theory—Applications II;enhancing Performance of machine learning Models in Healthcare: An Analytical Framework for Assessing and Improving data Quality;evaluating the Enhancement of Cognitive Skills and Acquisition of New Skills in an Environment of Different Video Game Genres;hySeg-Net: A Robust Interactive Hybrid Technique for Image Segmentation and Classification in Hand Gesture recognition;web Vulnerability Scanner;digitalization of Educational Resources in Pre-tertiary Education in Ghana: Assessing Impact, Challenges, and Opportunities in Enhancing learning Outcomes;interconnected through Robotic System in English Foreign Language Education;transferability Cybersocialization as a Digital Civility through Artificial Intelligence-Based Design thinking Mindset to Modern Pedagogy;fog Computing in Healthcare: Enhancing Recommendations and Real-Time Monitoring;enhancing Bank Consumer Retention: A Comprehensive Analysis of Churn Prediction Using machine-learning and Deep learning Techniques;a Contemporary Model of Kazakh National Pedagogy in the Era of Technology: theory-Based Design Framework;the Future of Post-harvest Logistics: the Cold Chain Practices with Blockchain, IoT, and FinTech;diagnosing Sexually Transmitted Disease in Females: Leveraging Dimensionality Reduction and machine learning;a Systematic Review of Optimal Task Scheduling Methods Using machine learning in Cloud Computing Environments;Intelligent Urban Futures: Exploring AI and machine learning Applications in Smart Cities.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhanced Soft Fault Diagnosis in DC-DC Converters Using Sparse Representation and Markov Transition Fields 5

Enhanced Soft Fault Diagnosis in DC-DC Converters Using Spar...

引用

5th international conference on Artificial Intelligence and Computer Engineering

作者： Umar, Muhammad Ibrahim Zhang, Guoqing Md, Masud Rana Martinez, Jean-Baptiste Liu, Yang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Peoples R China ENSEIRB MATMECA Comp Sci Bordeaux France Guangdong HUST Ind Technol Res Inst Dongguan 523808 Peoples R China

ISBN: (纸本)9798331528911;9798331528928

Faults in DC-DC converters are a major cause of power electronics equipment breakdowns, often due to the malfunction of semiconductor devices caused by aging and temperature effects. Although multiple studies highlight the potential of image recognition for fault diagnosis in DC-DC converters, there is limited information on how these techniques mature over time. this research examines capacitor and inductor degeneration, represented by a decrease in capacitance (C) and inductance (L). A capacitor is considered to have failed when C decreases by 5%. Similarly, inductor failure is characterized by a 5% decrease in inductance (L). this paper proposes a model to diagnose and identify faults using a time series of DC-DC converter data as input. the model performs sparse representation to extract the feature and clean noise on the data before encoding the raw signal into a two-dimensional representation and performs recognition and classification by a deep convolutional neural network. Traditional methods often struggle with distinguishing subtle variations in signal patterns under different fault conditions. the proposed method achieved 100% accuracy in simulated data and 97.00% in experimental data. Our findings demonstrate the effectiveness of this approach in diagnosing faults in a buck DC-DC converter, as validated by both simulations and laboratory experiments.

关键词： machine learning Power Electronics DC-DC Converter Soft Fault Diagnosis Markov Transition Field

来源：评论

学校读者我要写书评

暂无评论

Feature Extraction and recognition of Fingerprint Using KNN-SIFT Algorithm 5

Feature Extraction and Recognition of Fingerprint Using KNN-...

引用

5th international conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Rajput, Shweta Singh Manimaran, S. Satapathy, Sandeep Kumar Mishra, Shruti Mohanty, Sachi Nandan School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai600127 India VIT-AP University Andhra Pradesh Amaravati522503 India Yonsei University Department of Computer Science Seoul03722 Korea Republic of Centre for Advanced Data Sciences Vellore Institute of Technology Tamil Nadu Chennai600127 India

ISBN: (纸本)9798350385649

the biometric identification method of fingerprint recognition is quite popular because of its uniqueness and durability. the KNN-S 1FT algorithm is used in this research work to present a novel method for extracting and recognizing fingerprint features. the extraction of fingerprint feature information and fingerprint matching are the two main topics of the article. For the purpose of handling image differences brought on by scale, rotation, and affine transformations, a number of fingerprint feature extraction techniques are explored, with a focus on the SIFT algorithm. the KNN-S 1FT technique boosts the precision and dependability of fingerprint matching by combining the power of machine learning with pattern recognition. Experimental tests on a benchmark fingerprint database show that the proposed algorithm outperforms other cutting-edge methods in terms of accuracy and reliability. the findings of this study have broad ramifications for fields requiring safe identification procedures, including forensic investigations, access control systems, and law enforcement. the KNN-S 1FT technique that has been suggested helps to create sophisticated, effective fingerprint identification systems. © 2024 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Smart campus data management platform based on microservice architecture 5

Smart campus data management platform based on microservice ...

引用

5th international conference on machine learning, Big data and Business Intelligence, MLBDBI 2023

作者： Duan, XinRui Li, LeLe Peng, Feng Dalian Polytechnic University No.1 Qinggongyuan Ganjingzi District Dalian City116034 China

ISBN: (纸本)9798350359930

At present, the management dimension of colleges and universities is getting wider and wider, students' expectations are getting higher and higher, and their demands are becoming more and more diverse. the traditional management mode has been unable to solve the new challenges brought by the digital age. this paper aims to share the design and implementation ideas of the platform, and provide a new solution for the data management and application of smart campus. the platform will adopt distributed storage to ensure the reliability and security of data, realize the mining and utilization of data through big data analysis technology, and establish a process service development mechanism with fast, low cost and sustainable maintenance. © 2023 IEEE.

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

INDISCON 2024 - 5th IEEE India Council international Subsections conference: Science, Technology and Society

INDISCON 2024 - 5th IEEE India Council International Subsect...

引用

5th IEEE India Council international Subsections conference, INDISCON 2024

ISBN: (纸本)9798350376753

the proceedings contain 135 papers. the topics discussed include: LearnSync: navigating learning opportunities;ultra-wideband pattern reconfigurable antenna for base station applications;finite-time frequency control of an islanded microgrid system;blockchain-enabled distributed payment card tokenization system;probabilistic free riding attack in federated learning;dual-band MIMO array for 5G wireless networks;CFD and thermal analysis of electric vehicle battery pack;revolutionizing sentiment analysis: accelerated data science approaches for reddit submissions;defect mediated Sc2CO2 MXene monolayer for sensing small gas molecules: a first principle study;enhancing financial market analysis bitcoin vs gold through machine learning algorithms: a study on risk assessment and portfolio management;two step federated learning approach in brain stroke identification and classification via fine-tuning EfficientNetB0 network at edge nodes;and privacy-preserved stress detection from wearables using federated learning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A review of deep learning based methods for 2D human pose estimation 5

A review of deep learning based methods for 2D human pose es...

引用

5th international conference on Computer Vision and data mining, ICCVDM 2024

作者： Yang, Bo Zhang, Hong Hou, Xiaodong Tao, Qing Lv, Chunguang Zhao, Min Li, Wei Xinjiang Jiruixiang Technology Stock Limited Company Postdoctoral Research Workstation Xinjiang Changji831100 China Xinjiang University Xinjiang Urumqi830000 China

ISBN: (纸本)9781510682863

Human posture estimation is an important content in computer vision, which is the research basis of action recognition, human-computer interaction and other directions, and the traditional manual feature approach has certain problems in terms of accuracy, robustness and computation. In recent years, deep learning-based pose estimation methods have achieved high performance in human pose estimation. According to the number of people, this paper classifies deep learning-based 2D human pose estimation methods into single-person pose estimation methods and multi-person pose estimation methods, and summarizes and analyzes each method. A brief overview of the current mainstream datasets and evaluation metrics is provided. Finally, the development of 2D human pose estimation methods is summarized and possible future trends are listed. © 2024 SPIE.

关键词： machine vision

来源：评论

学校读者我要写书评

暂无评论

Extracting Rules from Event data for Study Planning 5th

Extracting Rules from Event Data for Study Planning

引用

5th international conference on Process mining (ICPM)

作者： Rafiei, Majid Bayrak, Duygu Pourbafrani, Mahsa Park, Gyunam Helal, Hayyan Lakemeyer, Gerhard van der Aalst, Wil M. P. Rhein Westfal TH Aachen Chair Proc & Data Sci Aachen Germany Rhein Westfal TH Aachen Knowledge Based Syst Grp Aachen Germany

ISBN: (纸本)9783031561061;9783031561078

In this study, we examine how event data from campus management systems can be used to analyze the study paths of higher education students. the main goal is to offer valuable guidance for their study planning. We employ process and data mining techniques to explore the impact of sequences of taken courses on academic success. through the use of decision tree models, we generate data-driven recommendations in the form of rules for study planning and compare them to the recommended study plan. the evaluation focuses on RWth Aachen University computer science bachelor program students and demonstrates that the proposed course sequence features effectively explain academic performance measures. Furthermore, the findings suggest avenues for developing more adaptable study plans.

关键词： Event data Decision Trees Campus Management Systems machine learning

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314页 << < 15 16 17 18 19 20 21 22 23 24 > >>

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：