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

3,135 篇 会议
171 册 图书
28 篇 期刊文献

馆藏范围

3,333 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,241 篇 工学
- 2,038 篇 计算机科学与技术...
- 1,087 篇 软件工程
- 401 篇 信息与通信工程
- 357 篇 电气工程
- 249 篇 生物工程
- 169 篇 控制科学与工程
- 157 篇 生物医学工程（可授...
- 73 篇 光学工程
- 73 篇 化学工程与技术
- 68 篇 机械工程
- 63 篇 仪器科学与技术
- 59 篇 电子科学与技术（可...
- 58 篇 安全科学与工程
- 47 篇 交通运输工程
- 38 篇 材料科学与工程（可...
- 38 篇 动力工程及工程热...
718 篇 理学
- 377 篇 数学
- 273 篇 生物学
- 169 篇 物理学
- 147 篇 统计学（可授理学、...
- 104 篇 系统科学
- 70 篇 化学
460 篇 管理学
- 298 篇 图书情报与档案管...
- 200 篇 管理科学与工程(可...
- 96 篇 工商管理
300 篇 医学
- 273 篇 临床医学
- 125 篇 基础医学(可授医学...
- 70 篇 药学(可授医学、理...
- 53 篇 公共卫生与预防医...
64 篇 法学
- 57 篇 社会学
32 篇 经济学
31 篇 教育学
28 篇 农学
6 篇 艺术学
3 篇 军事学
1 篇 文学

主题

546 篇 data mining
545 篇 machine learning
286 篇 pattern recognit...
240 篇 deep learning
188 篇 feature extracti...
160 篇 support vector m...
156 篇 artificial intel...
120 篇 training
118 篇 accuracy
115 篇 machine learning...
95 篇 data models
91 篇 data mining and ...
75 篇 classification
72 篇 neural networks
70 篇 convolutional ne...
68 篇 predictive model...
67 篇 big data
64 篇 computational mo...
57 篇 sentiment analys...
55 篇 learning systems

机构

10 篇 chinese academy ...
9 篇 chitkara centre ...
8 篇 zhejiang univers...
7 篇 guangdong univer...
7 篇 centre of resear...
6 篇 central south un...
6 篇 unsw sydney
6 篇 college of compu...
5 篇 badji mokhtar un...
5 篇 xi'an university...
5 篇 indian statistic...
5 篇 southwest jiaoto...
5 篇 kobe university ...
5 篇 southern univers...
4 篇 columbia univers...
4 篇 chitkara univers...
4 篇 shanghai jiao to...
4 篇 institute of big...
4 篇 centre for patte...
4 篇 shandong institu...

作者

12 篇 de-shuang huang
12 篇 venkatesh svetha
8 篇 petra perner
7 篇 phung dinh
7 篇 jacek m. zurada
7 篇 krasotkina olga
7 篇 mottl vadim
6 篇 zheng-guang wu
6 篇 ryszard tadeusie...
6 篇 marcin korytkows...
6 篇 hongyi li
6 篇 chaojie li
6 篇 biao luo
6 篇 lotfi a. zadeh
6 篇 kang-hyun jo
6 篇 leszek rutkowski
6 篇 long cheng
6 篇 zhongzhi shi
5 篇 zhang yan
5 篇 vitoantonio bevi...

语言

3,197 篇 英文
120 篇 其他
32 篇 中文

检索条件"任意字段=4th International Conference on Machine Learning and Data Mining in Pattern Recognition"

共 3334 条记录，以下是671-680 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：

A Hybrid Feature Selection Approach for data Clustering Based on Ant Colony Optimization 29th

A Hybrid Feature Selection Approach for Data Clustering Base...

引用

29th international conference on Neural Information Processing

作者： Dwivedi, Rajesh Tiwari, Aruna Bharill, Neha Ratnaparkhe, Milind Indian Inst Technol Indore Indore 453552 India Mahindra Univ Ecole Cent Sch Engn Hyderabad 500043 India ICAR Indian Inst Soybean Res Indore 452001 India

ISBN: (纸本)9783031301100;9783031301117

machine learning, data mining, and pattern recognition all require feature selection when working with high-dimensional data. Feature selection helps in improving the prediction accuracy and significantly reduces the computation time. the problem is that many of the feature selection algorithms use a sequential search strategy to choose the most important features. this means that each time you add or remove a feature from the dataset, you get stuck in a local optimum. this paper proposes a hybrid feature selection technique based on ant colony optimization that randomly selects features and quantifies their quality using K-means clustering in terms of silhouette index and laplacian score. the proposed hybrid feature selection technique allows for random selection of features, which facilitates a better exploration of feature space and avoids the problem of being trapped in a local optimal solution, while also generating a global optimal solution. Furthermore experimental investigation shows that the proposed method outperforms the state-of-the-art method.

关键词： Ant Colony Optimization Jaccard index K-means clustering Laplacian Score Silhouette Index

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis on Amazon Product Review 4

Sentiment Analysis on Amazon Product Review

引用

4th international conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022

作者： Kamalesh, B. Vijayalakshmi, S. Data Science Pune India

ISBN: (纸本)9781665474368

Users throughout the world may now access massive amounts of data thanks to the internet and social media platforms. [5] In every facet of human existence, electronic commerce (e-commerce) plays a crucial role. E-commerce is a marketing approach that enables businesses and consumers to buy and sell things via the internet. When buyers look for product information and compare alternatives online, they generally have access to dozens or hundreds of product reviews from alternative shoppers. machine learning is the most appropriate approach to training a neural network in today's age of practical artificial intelligence. So implementing a model to polarize those reviews and learn from them would make passing hundreds of comments a lot easier. [24] the interpretation will be a very basic product with positive, neutral, and negative polarization. the product is checked. this study suggests a sentiment evaluation model for shopper reviews based on the object and emotive word mining for emotional level analysis using machine learning approaches. © 2022 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

A Closet Fit Algorithm to Recover Missing data in data mining

A Closet Fit Algorithm to Recover Missing Data in Data Minin...

引用

Soft Computing for Security Applications (ICSCSA), international conference on

作者： Nidhi S Bhavsar Khushbu Madhav University Rajsthan

ISBN: (数字)9798331515720

ISBN: (纸本)9798331515737

Missing data can lead to inaccurate results and bad decisions. the proposed Closet Fit Algorithm(CFA) solves this problem by identifying the closest match for missing data, Refining the match until it's the best fit, working well with different types of data and missing values, improving data quality for better analysis and decision-making. Key benefits of A Closet fit Algorithm are improved accuracy, easy to use, works with different data types, helps make better decisions.

关键词： machine learning algorithms Accuracy Sensitivity Refining Noise machine learning Imputation data mining Security Reliability

来源：评论

学校读者我要写书评

暂无评论

A Computational Approach to Identify Normal and Abnormal Persons Gait Using Various machine learning and Deep learning Classifier 4th

A Computational Approach to Identify Normal and Abnormal Per...

引用

4th international conference on machine learning, Image Processing, Network Security and data Sciences (MIND)

作者： Yadav, Ram Kumar Neogi, Subhrendu Guha Semwal, Vijay Bhaskar Amity Univ Gwalior India MANIT Bhopal India

ISBN: (纸本)9783031243516;9783031243523

Walking based human identification is a looming method. Maximum biometric structure needs more high resolution and a variety of sensors. Walking base human recognition can be classifying abnormal or normal walks. In recent times by utilizing a computer vision-oriented approach to recognize abnormal and normalwalk cycles. Nowadays machinelearning procedures have beaten and supplemented the utilization of conventional techniques in bio-clinical frameworks. In this exploration, kinetic and wearable sensors are introduced. this research paper examines the walking cycle of humans after background extraction of the image;features are extracted with gait analysis of human motion using machine learning and neural network models. these models are able to classify abnormal and normal with extending accuracy from 70 to 93% using various machine learning, deep learning algorithms and CNN classifier. the novelty of this paper is to increase the classification accuracy with fast processing and reduce the time complexity of the dataset.

关键词： Biometric Abnormal Normal Gait analysis machine learning Neural network

来源：评论

学校读者我要写书评

暂无评论

Design of Hybrid Energy Storage and Management System in Hybrid Electric Vehicle Using machine learning Approach 4

Design of Hybrid Energy Storage and Management System in Hyb...

引用

4th international conference on Smart Electronics and Communication, ICOSEC 2023

作者： Kamalakannan, J. Reddy, K. Rajasekhara Kumar, N.M.G. Shafee, S.M. Dewangan, Kunal Kannan, V. Sri Sai Ram Institute of Technology Department of Mechanical Engineering Tamil Nadu Chennai600044 India Santhiram Engineering College Department of Electrical and Electronic Engineering Andhra Pradesh Nandyala518501 India Mohan Babu University Sree Vidyanikethan Engineering College Department of Electrical and Electronic Engineering Andhra pradesh 517102 India Sree Venkateswara College of Engineering Department of Mechanical Engineering Andhra pradesh 524316 India Kalinga University Department of Mechanical Engineering Chhattisgarh 492101 India K. Ramakrishnan College of Engineering Department of Physics Tamil Nadu Tiruchirapalli621112 India

ISBN: (纸本)9798350300888

the growing concern for reducing carbon emissions and the depletion Using fossil fuels has led to a considerable increase in the development of hybrid electric vehicles (HEVs) and their associated Controlling and storing energy systems. the blueprint of an efficient and effective System for storing and managing energy is crucial for the optimal performance of HEVs. In this context, this study proposes a novel strategies for designing mixed-source power storage and management system for HEVs using recurrent neural network (RNN)-based machine learning. the proposed approach involves the integration of RNN-based predictive models with the energy storage and management system of the HEV. the RNN-based predictive model is developed using historical driving data to predict the future driving pattern of the vehicle. the predicted driving pattern is then used to optimize the energy management system, which includes the control of the battery charging and discharging operations as well as the allocation of power between the battery and other power sources. Specifically, the suggested approach, simulations are carried out using a high-fidelity HEV model the actual world driving numbers. the end outcome of the simulations show that the proposed RNN-based energy storage and management system outperforms traditional rule-based control strategies in terms of energy efficiency, battery lifespan, and vehicle performance. In conclusion, the proposed approach of using RNN-based predictive models for designing hybrid energy storage and management systems in HEVs provides a promising avenue for the creation of more efficient and effective energy management systems for HEVs. this could lead to significant improvements in the fuel economy, reduced emissions, and extended battery lifespan of HEVs, thereby contributing to a greener and more sustainable future. © 2023 IEEE.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

DynamicDeepFlow: An Approach for Identifying Changes in Network Traffic Flow Using Unsupervised Clustering 1

引用

4th international conference on machine learning for Networking (MLN)

作者： Shen, Sheng Kiran, Mariam Mohammed, Bashir Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Tula Technol San Jose CA 95131 USA

ISBN: (数字)9783030989781

ISBN: (纸本)9783030989781;9783030989774

Understanding flow changes in network traffic has great importance in designing and building robust networking infrastructure. Recent efforts from industry and academia have led to the development of monitoring tools that are capable of collecting real-time flow data, predicting future traffic patterns, and mirroring packet headers. these monitoring tools, however, require offline analysis of the data to understand the big versus small flows and recognize congestion hot spots in the network, which is still an unfilled gap in research. In this study, we proposed an innovative unsupervised clustering approach, DynamicDeep-Flow, for network traffic pattern clustering. the DynamicDeepFlow can recognize unseen network traffic patterns based on the analysis of the rapid flow changes from the historical data. the proposed method consists of a deep learning model, variational autoencoder, and a shallow learning model, k-means++. the variational autoencoder is used to compress and extract the most useful features from the flow inputs. the compressed and extracted features then serve as input-output pairs to k-means++. the k-means++ explores the structure hidden in these features and then uses them to cluster the network traffic patterns. To the best of our knowledge, this is one of the first attempts to apply a real-time network clustering approach to monitor network operations. the real-world network flow data from Energy Sciences Network (a network serving the U.S. Department of Energy to support U.S. scientific research) was utilized to verify the performance of the proposed approach in network traffic pattern clustering. the verification results show that the proposed method is able to distinguish anomalous network traffic patterns from normal patterns, and thereby trigger an anomaly flag.

关键词： Network traffic pattern clustering Unsupervised learning Flow recognition Wide area network

来源：评论

学校读者我要写书评

暂无评论

4th international conference on machine learning, Image Processing, Network Security and data Sciences, MIND 2022

4th International Conference on Machine Learning, Image Proc...

引用

4th international conference on machine learning, Image Processing, Network Security and data Sciences, MIND 2022

ISBN: (纸本)9783031243660

the proceedings contain 64 papers. the special focus in this conference is on machine learning, Image Processing, Network Security and data Sciences. the topics include: Sensorless Control Algorithm of Permanent Magnet Synchronous Motor on Account of Neural Network;a Techno Aid to Ease in e-Rehabilitation;a Novel Approach to Analyse Lung Cancer Progression and Metastasis Using Page Rank Technique;homomorphic Encryption of Neural Networks;an Empirical Study to Enhance the Accuracy of an Ensemble learning Model for Crop Recommendation System by Using Bit-Fusion Algorithm;bayesian learning Model for Predicting Stability of System with Nonlinear Characteristics;Novel ABC: Aspect Based Classification of Sentiments Using Text mining for COVID-19 Comments;topic Modeling, Sentiment Analysis and Text Summarization for Analyzing News Headlines and Articles;bioBodyComp: A machine learning Approach for Estimation of Percentage Body Fat;a Computational Approach to Identify Normal and Abnormal Persons Gait Using Various machine learning and Deep learning Classifier;wearable Technology for Early Detection of Hyperthermia Using machine learning;intelligent Evaluation Framework of English Composition Based on Intelligent Algorithm;multimedia English Teaching System Based on Computer Information Technology;Correlation Analysis of Central Bank Communication Behavior and Monetary Policy Independence Based on VR Technology and machine learning;power Demand data Analysis and Recovery for Management of Power Distribution Systems;Optimization Design of Green Building Landscape Space Environment Based on LM-BP Algorithm;design of Computational thinking Intelligent Training System Under Big data Technology;creative Graphic Design System Based on Multi-objective Firefly Algorithm;next Generation Ultra-sensitive Surface Plasmon Resonance Biosensors.

关键词：

来源：评论

学校读者我要写书评

暂无评论

4th international conference on machine learning, Image Processing, Network Security and data Sciences, MIND 2022

4th International Conference on Machine Learning, Image Proc...

引用

4th international conference on machine learning, Image Processing, Network Security and data Sciences, MIND 2022

ISBN: (纸本)9783031243516

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design Methodology for Single-Channel CNN-Based FER Systems 6

Design Methodology for Single-Channel CNN-Based FER Systems

引用

6th international conference on Information and Computer Technologies, ICICT 2023

作者： Parra, Dorfell Camargo, Carlos Universidad Nacional Department of Electric and Electronic Engineering Bogota Colombia

ISBN: (纸本)9798350300956

Facial Expression recognition (FER) systems classify emotions by using geometrical approaches or machine learning (ML) algorithms such as Convolutional Neural Networks (CNNs). Due to their complexity, these FER systems need to be implemented on high-performance hardware, which makes them unsuitable for embedded devices. To address this challenge, we propose a methodology for the design of low-complexity, CNN-based FER systems. Our methodology includes data preprocessing, Local Binary pattern (LBP) implementation, data Augmentation (DA), and CNN design. Here, we also introduce the Model M6, a single-channel CNN that reaches an accuracy of 94% in less than 30 epochs. M6 has 306,182 parameters that correspond to 1.17 MB of memory. therefore, our methodology and M6 model are feasible for implementation onto embedded systems capable of computing floating point operations. We validated our methodology and M6 model using 66 tests with 6 CNN models and 4 training parameters (batch size, learning rate, number of epochs, optimizer). this validation was performed using the Japanese Female Facial Expression (JAFFE) dataset and TensorFlow. In each test, the relationship between parameters, layers, overfitting, and underfitting was studied. Moreover, we present a step-by-step guideline on how to design the single-channel CNN and provide open-source code for readers interested in reproducing our work. © 2023 IEEE.

关键词： Local binary pattern

来源：评论

学校读者我要写书评

暂无评论

4th international conference on Emerging Technology Trends in Electronics, Communication and Networking, ET2ECN 2021

4th International Conference on Emerging Technology Trends i...

引用

4th international conference on Emerging Technology Trends in Electronics, Communication and Networking, ET2ECN 2021

ISBN: (纸本)9789811967368

the proceedings contain 26 papers. the special focus in this conference is on Emerging Technology Trends in Electronics, Communication and Networking. the topics include: GUI Development of IRNSS Receiver;A 1 Gbps VLC System Based on Daylight and Intensity Modulator;Performance of MISO Systems with Alamaouti Transmit Diversity and Antenna Selection in TDD and FDD;Performance Analysis of OFDM-Based Optical Wireless Communication System;Performance Comparison of Different Diversity and Combining Techniques Over Gamma–Gamma FSO Link;abstract data Models and System Design for Big data Geospatial Analytics;circularly Polarized Sector Patch Antenna with Fractal Defected Ground Structure;Two-Element MIMO Antenna with Polarization Diversity for 5G Application;machine learning-Based Investigation of Employee Attrition Prediction and Analysis;Millimeter Wave Overmoded Circular Waveguide Tapers for ECRH Applications;CNN-Based Leaf Wilting Classification Using Modified ResNet152;Deep learning-Based COVID-19 Detection Using Transfer learning through ResNet-50;OCR for Devanagari Script Using a Deep Hybrid CNN-RNN Network;a dataset Preparation Framework for Education data mining;Generative Adversarial Network-Based Improved Progressive Approach for Image Super-Resolution: ImProSRGAN;community Detection Using Label Propagation Algorithm with Random Walk Approach;comparative Analysis of Generative Adversarial Network-Based Single-Image Super-Resolution Approaches;analysis of Logical Effort-Based Optimization in the Deep Submicron Technologies;a Single Electron Transistor-Based Floating Point Multiplier Realization at Room Temperature Operation;Comparison of Total Ionizing Dose Effect on Tolerance of SCL 180 nm Bulk and SOI CMOS Using TCAD Simulation;performance Analysis of Corrugated Horn Antenna for Liquid Level Measurement Application;Quad-Element with Penta-Band MIMO Antenna for 5G Millimeter-Wave Applications;Quad Band Planar Monopole Antenna with Polarization Diversity for FSS

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334页 << < 64 65 66 67 68 69 70 71 72 73 > >>

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：