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

2,973 篇 会议
176 册 图书
24 篇 期刊文献

馆藏范围

3,172 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,043 篇 工学
- 1,825 篇 计算机科学与技术...
- 960 篇 软件工程
- 329 篇 电气工程
- 313 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...
- 71 篇 光学工程
- 64 篇 机械工程
- 62 篇 化学工程与技术
- 51 篇 电子科学与技术（可...
- 47 篇 仪器科学与技术
- 46 篇 安全科学与工程
- 36 篇 交通运输工程
648 篇 理学
- 352 篇 数学
- 244 篇 生物学
- 140 篇 物理学
- 135 篇 统计学（可授理学、...
- 95 篇 系统科学
- 62 篇 化学
408 篇 管理学
- 244 篇 图书情报与档案管...
- 182 篇 管理科学与工程(可...
- 83 篇 工商管理
262 篇 医学
- 241 篇 临床医学
- 123 篇 基础医学(可授医学...
- 74 篇 药学(可授医学、理...
- 40 篇 公共卫生与预防医...
46 篇 法学
- 42 篇 社会学
38 篇 教育学
- 32 篇 教育学
33 篇 经济学
- 31 篇 应用经济学
23 篇 农学
6 篇 艺术学
4 篇 文学

主题

575 篇 machine learning
564 篇 data mining
323 篇 pattern recognit...
212 篇 deep learning
201 篇 feature extracti...
154 篇 support vector m...
145 篇 artificial intel...
129 篇 machine learning...
120 篇 accuracy
120 篇 training
91 篇 data mining and ...
90 篇 data models
72 篇 neural networks
71 篇 classification
69 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 indian institute...
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...

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

2,869 篇 英文
290 篇 其他
34 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 3173 条记录，以下是931-940 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 Model of Multiple CNNs with Attention Mechanism for Optimized Facial Expression recognition

A Hybrid Model of Multiple CNNs with Attention Mechanism for...

引用

Artificial Intelligence and Computer Engineering (ICAICE), international conference on

作者： Wanqiu Chen Yuting Sun Yihao Yang Jiaxu Yu Multimedia Mobile and Web Development Fuzhou University Fuzhou China Data Science and Big Data Technology Fuzhou University Fuzhou China Software Engineering Fuzhou University Fuzhou China

ISBN: (数字)9798331528911

ISBN: (纸本)9798331528928

Facial expression recognition is integral to enhancing human-machine interactions, applicable across security, advertising, and social media. Traditionally, these systems relied on handcrafted features or basic algorithms, but advancements in computational power and neural network architecture like Convolutional Neural Networks (CNNs) have shifted this trend. this study presents a hybrid model combining multiple CNNs-MobileNetV1, MobileNetV2, and ResNet50-with an attention mechanism to improve the robustness and accuracy of facial expression recognition. Utilizing the strengths of these networks, the model utilizes an ensemble approach where feature extractions are integrated and optimized using a random forest to determine the most effective weightings for final predictions. this method not only harnesses the power of deep learning to enhance feature detection across diverse conditions but also implements transfer learning (i.e. ImageNet weights) to address challenges posed by small or non-varied datasets, significantly advancing the abilities of facial expression recognition systems.

关键词： Training Attention mechanisms Accuracy Social networking (online) Face recognition Computational modeling Transfer learning Robustness Ensemble learning Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

5th international conference on Smart Computing and Informatics, SCI 2021

5th International Conference on Smart Computing and Informat...

引用

5th international conference on Smart Computing and Informatics, SCI 2021

ISBN: (纸本)9789811696688

the proceedings contain 58 papers. the special focus in this conference is on Smart Computing and Informatics. the topics include: QCA-Based Error Detection Circuit for Nanocommunication Network;evaluating Performance on Covid-19 Tweet Sentiment Analysis Outbreak Using Support Vector machine;minimum Simplex Nonlinear Nonnegative Matrix Factorization for Hyperspectral Unmixing;prediction and Analysis of Vitamin D Deficiency Using machine learning Algorithms;student Performance Prediction Using Classification Models;estimating Driver Attentiveness through Head Pose Using Hybrid Geometric-Based Method;IIWSCOA-Based DCNN: Improved Invasive Weed Sine Cosine Optimization Algorithm for Early Detection of Myocardial Infarction Using Deep Convolution Neural Network;intrusion Detection Using Support Vector machine and Artificial Neural Network;student’s Academic Performance Prediction Using Ensemble Methods through Educational data mining;A Flexible Accession on Brain Tumour Detection and Classification Using VGG16 Model;check Certificate—A Certificate Verification Platform for Students and Organizations;secure Cluster-Based Routing Using Modified Spider Monkey Optimization for Wireless Sensor Networks;ChefAI Text to Instructional Visualization Using Amazon Web Services;Identification of Predominant Genes that Causes Autism Using MLP;Detecting Impersonators in Examination Halls Using AI;telugu Text Classification Using Supervised machine learning Algorithm;Application of Hybrid MLP-GWO for Monthly Rainfall Forecasting in Cachar, Assam: A Case Study;Temperature Prediction Using Hybrid MLP-GOA Algorithm in Keonjhar, Odisha: A Case Study;development of Different Word Vectors and Testing Using Text Classification Algorithms for Telugu;addressing Longtail Problem using Adaptive Clustering for Music Recommendation System;A Proficient GK-KMA Based Segmentation and Lung Nodule Detection in CT Images Using PTRNN;framework for Diabetic Retinopathy Classification.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Analysing Depression in Social Media data Using machine learning Techniques

Analysing Depression in Social Media Data Using Machine Lear...

引用

Electronics and Sustainable Communication Systems (ICESC), 2020 international conference on

作者： B Jayapradha T. Velmurugan PG and Research Department of Computer Science Dr. Ambedkar Government Arts and Science College Chennai India PG and Research Department of Computer Science Dwaraka Doss Govardhan Doss Vaishnav College Chennai India

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

In the present digital era, a significant volume of text data has started to emerge post-COVID with the increase in the number of people who have started using social media. the text thus generated encapsules a hidden layer of emotion with in it. this emotion hidden in the textual data conveys a lot of understanding of the people who are responsible for the creation of the text and helps to know the person better. However, extracting the emotions from the text data is quiet a challenging task as it involves a series of pre-processing pipelines and also the application of machine learning techniques to the text involved in the research for the purpose of extracting the emotion from it. the primary objective of this research work focusses on extracting depression based emotional text using some of the machine learning techniques. It also gives a comparative analysis between the machine learning techniques in terms of accuracy. this work has utilized machine learning techniques such as Naïve Bayes and Random Forest to find the emotion particularly depressions in the Kaggle data set, particularly, text-based information taken into account for the analysis. Finally, this work concludes that the performance of machine learning algorithms based on its efficiency. this information can then enable appropriate counselling interventions, preventing the person under depression from escalating into suicidal thoughts or to other mental health issues.

关键词： Text mining Accuracy Social networking (online) Pipelines Forestry Mental health Depression Prediction algorithms Naive Bayes methods Random forests

来源：评论

学校读者我要写书评

暂无评论

Computer Software Application in Blockchain and Big data Technology

Computer Software Application in Blockchain and Big Data Tec...

引用

Information Science and Education (ICISE-IE), international conference on

作者： Yuxiu Chen Zhenhua Wen Guangzhou Vocational University of Science and Technology Guangzhou China

ISBN: (数字)9798331506766

ISBN: (纸本)9798331506773

this paper studies the integrated application of blockchain and big data technology in computer software. the article outlines the decentralized data storage mechanism of blockchain and the data processing capabilities of big data technology, analyzing the role of both in enhancing data processing efficiency and security. In the financial sector, blockchain simplifies cross-border transaction processes and enhances the transparency and security of asset management. In logistics management, blockchain enables transparent tracking of the supply chain, improving data reliability. At the same time, big data technology supports business analytics, scientific research, and public services, providing decision-making support through data mining and machine learning.

关键词： Technological innovation Merging Education Decision making Supply chains Big data data processing Software Blockchains Security

来源：评论

学校读者我要写书评

暂无评论

Modeling and Analyzing the Manifolds of Cortical-Muscle During Card-Grabbing by Preferential Subspace Identification

Modeling and Analyzing the Manifolds of Cortical-Muscle Duri...

引用

pattern recognition and machine learning (PRML), IEEE international conference on

作者： Jiyu Tan Yurong Li Jixiang Li Nan Zheng College of Electrical Engineering and Automation Fuzhou University Fuzhou China Fujian Key Laboratory of Medical Instrumentation and Pharmaceutical Technology Fuzhou University Fuzhou China

ISBN: (数字)9798350355925

ISBN: (纸本)9798350355932

the primary aim of this study is to construct a state-space model that reduces the complexity of the human sensorimotor control system and explore motion control theory based on manifolds. Low-dimensional neural and muscle manifolds, representing the population activity of the brain and muscles, quantify the sensorimotor function of the human cortex, revealing hidden information about how the brain controls movement. this study used EEG and EMG signals from 25 participants during a card grabbing task. Preferential subspace recognition (PSID) algorithm was used to construct a state space model of subjects to study the neural computational strategies for sensorimotor control in the preparation and execution phases of motion, as well as the differences between brain and muscle population activity. the results show that from the preparation stage to the execution stage, the population activity of cortical muscles follows the orthogonal neural computation strategy in the subspace. the degree of trajectory entanglement between neural manifolds and muscle manifolds is greater than that during exercise preparation. Moreover, neural manifolds are less entangled than muscle manifolds and show a more stable state in structure. these results show that the adopted approach effectively reveals the orthogonal neural mechanisms of brain control during movement, highlighting the differences in control output and feedback input in sensorimotor control. this offers a new perspective on how the brain controls complex movements.

关键词： Manifolds Computational modeling Muscles Aerospace electronics Control systems Brain modeling State-space methods Complexity theory Trajectory pattern recognition

来源：评论

学校读者我要写书评

暂无评论

5th international conference on machine learning, Image Processing, Network Security, and data Sciences, MIND 2023

5th International Conference on Machine Learning, Image Proc...

引用

5th international conference on machine learning, Image Processing, Network Security, and data Sciences, MIND 2023

ISBN: (纸本)9783031622168

the proceedings contain 29 papers. the special focus in this conference is on machine learning, Image Processing, Network Security and data Sciences. the topics include: the Potential of 1D-CNN for EEG Mental Attention State Detection;marker-Based Augmented Reality Application in Education Domain;detection and Classification of Waste Materials Using Deep learning Techniques;Deep learning Based EV’s Charging Network Management;internet of Medical things: Empowering Mobility and Health Monitoring with a Smart Walking Stick;SynText - data Augmentation Algorithm in NLP to Improve Performance of Emotion Classifiers;preface;Phishing Detection Using 1D-CNN and FF-CNN Models Based on URL of the Website;A Comparative Analysis of ML Based Approaches for Identifying AQI Level;a Review of Authentication Schemes in Internet of things;advancements in Facial Expression recognition: A Comprehensive Analysis of Techniques;a Deep learning Method for Obfuscated Android Malware Detection;COVID-19 Detection from Chest X-Ray Images Using GBM with Comparative Analysis;hate Speech Detection Using machine learning and Deep learning Techniques;effectiveness of Influencer Marketing on Gen Z Consumers;compressors Using Modified Sorting and Parallel Counting;violence Detection in Indoor Domestic Environment Using Multimodal Information;Code-Mixed Language Understanding Using BiLSTM-BERT Multi-attention Fusion Mechanism;diabetes Prediction Using machine learning Classifiers;crop Yield Prediction Using machine learning Approaches;Comparative Analysis of Economy-Based Multivariate Oil Price Prediction Using LSTM;MRI Based Spatio-Temporal Model for Alzheimer’s Disease Prediction;bridging the Gap: Condensing Knowledge Graphs for Metaphor Processing by Visualizing Relationships in Figurative and Literal Expressions;a Novel Unsupervised learning Approach for False data Injection Attack Detection in Smart Grid;a Multi-stage Encryption Technique Using Asymmetric and Various Symmetric Ciphers;speed-Invar

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research and Application of Intermediate Experiment Digitization Basic Platform

Research and Application of Intermediate Experiment Digitiza...

引用

Consumer Electronics and Computer Engineering (ICCECE), 2021 IEEE international conference on

作者： Jian Cao Feng Zhao Ziming Liu Deshui Tong Yuanfang Wang Shu Wang Oil production technology research institute PetroChina Liaohe Oilfield Liaoning China

ISBN: (数字)9798331533113

ISBN: (纸本)9798331533120

this paper focuses on the development and application of an intelligent basic platform for intermediate experiments, serving the oil production process. through a series of methods such as hardware intelligent upgrading and transformation, establishing connections between programmable logic controllers and hardware devices based on Modbus protocol, designing configuration software to read and control display data in real time, the intelligent basic platform for intermediate experiments has been successfully developed. the research and development achievements include the design and completion of three sets of configuration systems, intelligent control of hardware working status, and real-time data reading and graphical display, providing efficient and intelligent platform support for experimental research in the industry.

关键词： Industries Protocols machine learning algorithms Oils Hardware Software Real-time systems data mining Intelligent control Testing

来源：评论

学校读者我要写书评

暂无评论

Research on intelligent elderly care service information system based on machine learning 23

Research on intelligent elderly care service information sys...

引用

Proceedings of the 2023 5th international conference on Internet of things, Automation and Artificial Intelligence

作者： Qi Chen Nan Sheng Guangzhou Academy of Fine Arts China

ISBN: (纸本)9798400716485

the aging of the population is becoming more and more serious, and intelligent pension is becoming more and more important. Today, machine learning and artificial intelligence are widely used in all walks of life, and facial recognition based on machine learning is applied to the pension service system, which will make the pension system intelligent. the elderly identity verification through face recognition has the characteristics of direct and convenient, not easy to lose. In recent years, with the research and application of machine learning in the field of artificial intelligence such as computer vision, face recognition as an important part of computer vision technology has also been greatly developed, all kinds of face recognition algorithms based on machine learning emerge endlessly, and the effect is far higher than the traditional method. this paper designs and implements an artificial intelligence elderly care service information system based on machine learning, and studies the face recognition technology of intelligent elderly care system. the paper carried out feasibility analysis and demand analysis of the system research, discussed the functions to be designed and implemented in the research, analyzed the work flow of the research, and according to the work flow, the research was divided into five functional modules: image acquisition, face detection, feature extraction, identity recognition and result output. the machine learning model YOLO is used for face detection, ERT algorithm is used for face alignment, and 128-dimensional feature vector is extracted by residual neural network to realize face recognition. the input and output of real-time images are realized by OpenCV. the function of the algorithm is tested on the flw data set, and the accuracy of the algorithm can reach more than 98%. It realizes the research of face recognition system in artificial intelligence elderly care service information system based on machine learning, which can achi

关键词：

来源：评论

学校读者我要写书评

暂无评论

machine learning Model to Selection of Job Applicant Documents to Increase the Human Resources Department Performance

Machine Learning Model to Selection of Job Applicant Documen...

引用

international conference on Cybernetics and Intelligent System (ICORIS)

作者： Inayatulloh Rajiv Dharma Mangruwa Prasetya Cahya S Nuril Kusumawardani Soeprapto Putri Information Systems Department School of Information System Bina Nusantara University Jakarta Indonesia Communication and Business-Telkom University Bandung Indonesia Azman Hashim International Business School University of Technology Malaysia Malaysia

the planning of the company's existing and future human resource needs is included in the process of human resource recruitment. the availability of human resources, in terms of both quality and quantity, will be significantly impacted by the recruitment process, if it is both efficient and successful. the initial stages of the employee recruitment process involve selecting applicant documents according to company needs. Currently, the document selection process is done manually by studying the applicant documents one by one and then grouping them into several categories. this mechanism is inefficient and risks producing the wrong choices. On the other hand, machine learning has text recognition and image processing capabilities to increase the effectiveness and efficiency of the process. So, the purpose of this research is to help companies, especially the human resources division, improve the effectiveness and efficiency of new employee selection, especially the selection and classification of job applicant documents. the research method uses a qualitative approach with a literature review to identify new employee recruitment problems was continued by designing data sets, training data, and testing with machine learning using the LVQ method. the result of this research is that a machine learning model builds a model for selecting job applicant documents using machine learning with the learning Vector Quantization (LVQ) method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A STYLE TRANSFER MAPPING AND FINE-TUNING SUBJECT TRANSFER FRAMEWORK USING CONVOLUTIONAL NEURAL NETWORKS FOR SURFACE ELECTROMYOGRAM pattern recognition 47

A STYLE TRANSFER MAPPING AND FINE-TUNING SUBJECT TRANSFER FR...

引用

47th IEEE international conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Kanoga, Suguru Hoshino, Takayuki Tada, Mitsunori Natl Inst Adv Ind Sci & Technol Tokyo Japan Keio Univ Yokohama Kanagawa Japan

ISBN: (纸本)9781665405409

Reducing inter-subject variability between new users and the measured source subjects, and effectively using the information of classification models trained by source subject data, is very important for human-machine interfaces. In this study, we propose a style transfer mapping (STM) and fine-tuning (FT) subject transfer framework using convolutional neural networks (CNNs). To evaluate the performance, we used two types of public surface electromyogram datasets named Myo-datasets and NinaPro database 5. Our proposed framework, STM-FT-CNN, showed the best performances in all cases compared with conventional subject transfer frameworks. In the future, we will build an online processing system that includes this subject transfer framework and verify its performance in online experiments.

关键词： Transfer learning style transfer mapping fine-tuning convolutional neural network surface electromyogram

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318页 << < 90 91 92 93 94 95 96 97 98 99 > >>

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：