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

1,721 篇 会议
45 册 图书
12 篇 期刊文献

馆藏范围

1,777 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

1,224 篇 工学
- 1,093 篇 计算机科学与技术...
- 629 篇 软件工程
- 253 篇 信息与通信工程
- 200 篇 电气工程
- 177 篇 生物工程
- 99 篇 控制科学与工程
- 98 篇 生物医学工程（可授...
- 60 篇 光学工程
- 46 篇 化学工程与技术
- 45 篇 电子科学与技术（可...
- 41 篇 机械工程
- 41 篇 仪器科学与技术
- 40 篇 安全科学与工程
- 30 篇 交通运输工程
- 28 篇 动力工程及工程热...
- 27 篇 材料科学与工程（可...
456 篇 理学
- 199 篇 数学
- 197 篇 生物学
- 144 篇 物理学
- 83 篇 统计学（可授理学、...
- 51 篇 系统科学
- 46 篇 化学
233 篇 管理学
- 167 篇 图书情报与档案管...
- 86 篇 管理科学与工程(可...
- 43 篇 工商管理
182 篇 医学
- 160 篇 临床医学
- 72 篇 基础医学(可授医学...
- 39 篇 药学(可授医学、理...
- 32 篇 公共卫生与预防医...
34 篇 法学
- 30 篇 社会学
17 篇 经济学
14 篇 教育学
11 篇 农学
2 篇 艺术学
1 篇 军事学

主题

237 篇 machine learning
182 篇 deep learning
137 篇 pattern recognit...
107 篇 feature extracti...
89 篇 support vector m...
88 篇 data mining
74 篇 accuracy
72 篇 training
57 篇 convolutional ne...
50 篇 machine learning...
46 篇 artificial intel...
45 篇 data models
40 篇 neural networks
39 篇 face recognition
38 篇 computational mo...
36 篇 learning systems
36 篇 adversarial mach...
33 篇 predictive model...
32 篇 classification
32 篇 image recognitio...

机构

6 篇 college of compu...
5 篇 xi'an university...
4 篇 badji mokhtar un...
4 篇 shanghai jiao to...
4 篇 institute of big...
4 篇 chitkara centre ...
4 篇 chitkara univers...
4 篇 library shanghai...
3 篇 school of comput...
3 篇 univ chittagong ...
3 篇 chongqing univer...
3 篇 centre of resear...
3 篇 school of comput...
3 篇 school of comput...
3 篇 school of design...
3 篇 korea univ dept ...
3 篇 school of automa...
3 篇 university of mi...
3 篇 shenyang jianzhu...
3 篇 xi'an university...

作者

5 篇 venkatesh svetha
4 篇 ashwini kodipall...
4 篇 zhang yan
4 篇 srinivasa gowri
4 篇 kamel mohamed s.
4 篇 lall brejesh
4 篇 trupthi rao
3 篇 andersson karl
3 篇 peng yang
3 篇 malerba donato
3 篇 karl andersson
3 篇 chaudhury santan...
3 篇 de-shuang huang
3 篇 sekhar c. chandr...
3 篇 wang shuo
3 篇 kamata sei-ichir...
3 篇 mohammad shahada...
3 篇 azizi nabiha
3 篇 phung dinh
3 篇 krasotkina olga

语言

1,695 篇 英文
74 篇 其他
22 篇 中文

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

共 1778 条记录，以下是391-400 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：

Akshi: An Assistance system for visually challenged using machine learning 4

Akshi: An Assistance system for visually challenged using Ma...

引用

4th international conference on Artificial Intelligence and Speech Technology, AIST 2022

作者： Jain, Aakash Verma, Ritik Khokhar, Gurtej Singh Bhadauria, Madhulika Amity University Department of Computer Science and Engineering Uttar Pradesh Noida India

ISBN: (纸本)9781665499026

this work focuses on is emotion recognition. Emotion shows crucial data about human communication. It's general to utilize face expressions to convey feelings throughout a discussion, and personal communication is only possible through facial expressions. the goal of this study is for offering a machine learning-based emotion recognition structure for people who are impaired visually. We present a CNN-based solution approach to manage this challenge, for training and testing we used FER2013 database which consisted of 7 facial expression and a total of 35,685 images out of which we selected 3 facial expression happy, sad, and neutral comprising of 21264 images and achieved an accuracy of 81%.It has some limitations that it needs a person to operate and sometimes mix up of expressions so gives wrong results. Likewise, CNN we also implemented Transfer learning model i.e., Mobile Net for facial expression detection with similar dataset and achieved an accuracy of around 80%. To improvise our overall accuracy firstly we and modified the CNN design and achieved an overall accuracy of 91.65% which was superior to previous two implementations. the primary utility of the model is to help visually impaired people for better communication. © 2022 IEEE.

关键词： Emotion recognition

来源：评论

学校读者我要写书评

暂无评论

Non-invasive Technique for Detecting Glycosuria through Image Processing and Deep learning Approaches 5th

Non-invasive Technique for Detecting Glycosuria Through Imag...

引用

5th EAI international conference on Cognitive Computing and Cyber Physical Systems, IC4S 2024

作者： Teja, Chitturi Siva Nitheesha, Gokaraju Kumar, Boyidi Ravi Krishna, Bandaru Radha Naik, Desavath Madhu Pareek, Prakash Singh, Lokendra Department of ECE Vishnu Institute of Technology Bhimavaram534202 India Dehradun248002 India

ISBN: (纸本)9783031770746

Glycosuria level monitoring is a fundamental aspect of diabetes management, enabling proactive and personalized care to prevent complications, improve overall health, and enhance the quality of life for individuals with diabetes. Conventional glycosuria monitoring methods often involve invasive procedures, potentially risking the immune system, especially with repeated injections. the research focuses on a non-invasive method utilizing urine samples for glycosuria testing to address these concerns. the proposed method integrates image processing techniques, such as Gaussian filtering and image resizing, to optimize input data with machine learning approaches. Deep learning, especially convolutional neural networks is employed for their ability in feature extraction and pattern recognition. the system aims to achieve high accuracy in categorizing glycosuria levels into groups such as diabetes, prediabetes, and normal, providing a reliable and non-invasive alternative to traditional glycosuria monitoring techniques. this approach shows promise in enhancing patient compliance and overall health monitoring for individuals requiring regular glucose assessment. the accuracy of the proposed method based on CNN achieves 98.54% where the existing method based on support vector machine (SVM) achieves only 88.46%. it is evident from simulation results, the proposed method attained 11.39% improved accuracy when compared to existing SVM. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Accuracy Classification Convolutional Neural Network Deep learning gaussian filter Glycosuria

来源：评论

学校读者我要写书评

暂无评论

QNet: A Quantum-Native Sequence Encoder Architecture 4

QNet: A Quantum-Native Sequence Encoder Architecture

引用

4th IEEE international conference on Quantum Computing and Engineering, QCE 2023

作者： Day, Wei Chen, Hao-Sheng Sun, Min-Te National Central University Department of Computer Science Taoyuan City Taiwan

ISBN: (纸本)9798350343236

this work proposes QNet, a novel sequence encoder model that entirely inferences on the quantum computer using a minimum number of qubits. Let n and d represent the length of the sequence and the embedding size, respectively. the dot-product attention mechanism requires a time complexity of O(n2 ·d), while QNet has merely O(n+d) quantum circuit depth. In addition, we introduce ResQNet, a quantum-classical hybrid model composed of several QNet blocks linked by residual connections, as an isomorph Transformer Encoder. We evaluated our work on various natural language processing tasks, including text classification, rating score prediction, and named entity recognition. Our models exhibit compelling performance over classical state-of-the-art models with a thousand times fewer parameters. In summary, this work investigates the advantage of machine learning on near-term quantum computers in sequential data by experimenting with natural language processing tasks. © 2023 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Secure Sleep Apnea Detection with FHE and Deep learning on ECG Signals 27th

Secure Sleep Apnea Detection with FHE and Deep Learning on E...

引用

27th international conference on pattern recognition, ICPR 2024

作者： Yalavarthi, Bharat Kaushik, Arjun Ramesh Sharma, Tilak Jutla, Charanjit Ratha, Nalini University at Buffalo BuffaloNY United States IBM Research Yorktown HeightsNY United States

ISBN: (纸本)9783031783531

Sleep apnea, a prevalent sleep disorder affecting individuals of all demographics, poses a threat of significant disruption to daily life. the analysis of Electrocardiogram (ECG) data facilitates the accurate diagnosis of sleep apnea. With the advent of machine learning and its accessibility through cloud services, doctors have been compelled to enhance their diagnostic capabilities by integrating deep learning into their analytical tools. However, challenges such as data privacy, security, and confidentiality regulations are hindering the adoption of deep learning in the healthcare domain. In this research, we address these challenges by proposing an end-to-end encrypted framework to analyze encrypted ECG signals and diagnose sleep apnea. Leveraging Fully Homomorphic Encryption (FHE) on deep learning models ensures privacy and security by design while enabling computations on encrypted data. To overcome the unique challenges posed by handling encrypted data in deep learning models, we introduce novel and efficient techniques for adapting several key components such as the convolutional layer, max pooling, ReLU activation, and fully connected layer to the FHE domain. Our approach includes adapting the convolutional layer in the spectral domain, implementing fully connected layers as generalized matrix multiplication, and employing approximation methods for ReLU activation and max pooling. the experimental results on real encrypted ECG data demonstrate the feasibility and efficacy of our proposed framework, achieving a remarkable accuracy of 99.56% in detecting sleep apnea. Our proposed encrypted network does not lose any predictive performance compared to its plaintext counterpart. this research underscores the potential of encrypted data processing in significantly enhancing the security and privacy of healthcare services, particularly in the domain of sleep apnea diagnosis. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Sleep research

来源：评论

学校读者我要写书评

暂无评论

A Novel Efficient Approach for Feature Selection for Enhanced Performance in Breast Cancer Prediction 4th

A Novel Efficient Approach for Feature Selection for Enhance...

引用

4th international conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Bansal, Arin Lohan, Vishal Kumar Khanna, Munish Agnihotri, Shantanu UPES Dehra Dun Uttarakhand India Galgotias Univ Dankaur India

ISBN: (纸本)9783031837920;9783031837937

Modern research relies on computer-aided diagnostic (CAD) tools for efficient utilisation of time and resources. these technologies help medical practitioners make decisions by swiftly identifying anomalies and providing reliable information. the effective selection of features (characteristics) is crucial for these systems to appropriately categorise high-dimensional biological data. these traits may help diagnose linked medical issues. Biomedical data has many unnecessary or redundant information, making pattern identification difficult. therefore, a feature selection (FS) technique should be implemented and used to remove these characteristics from the training data. Eliminating irrelevant or uninformative characteristics is the main objective of FS techniques to enhance classification accuracy along with reduction of training and testing time of machine learning (ML) classifiers. In ML-driven CAD systems, the FS phase is crucial to success. Adding efficient features during training may boost ML model performance. this empirical research proposes an FS-based biological data categorisation approach based on integration of Water Wave Optimization (WWO) soft-computing algorithm with efficient ML classifiers. Using the publicly accessible Wisconsin Diagnostic Breast Cancer (WDBC) standard dataset, this study classifies benign and malignant tumours. the 70:30 train-test split approach is implemented and the suggested strategy's competency is assessed using accuracy, sensitivity (Recall), specificity, precision, F1-Score, Kappa Score, Matthews Correlation Coefficient (MCC), and ROC AUC Score. Best accuracy calculated using the proposed method is 97.96%. the suggested clinical decision support system has a good classification performance, making it a useful secondary opinion tool and lowering the workload of experienced medical physicians.

关键词： Feature Selection Soft-computing algorithms Medical data machine learning Optimization

来源：评论

学校读者我要写书评

暂无评论

Face and Iris based Human Authentication using Deep learning 4

Face and Iris based Human Authentication using Deep Learning

引用

4th international conference on Electronics and Sustainable Communication Systems, ICESC 2023

作者： Muthukumaran, B. Harshavarthanan, L. Dhyaneshwar, S. Sharief, Muhammed Zaid Srm Institute of Science and Technology Kattankulathur Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350300093

Unique data protection is must in the modern world. Security for information technology and access to restricted areas, such as airports, governments, healthcare facilities, and military bases, are two areas where biometric systems using a person's unique physiological or behavioral features have grown increasingly popular. In order to make a biometric system function reliably over a wide range of uses and settings, it is best to employ a multimodal biometric system that identifies individuals using a combination of factors. To further enhance the security, a multi-modal biometric authentication system could be employed to circumvent the constraints of a single-modal biometric authentication system. the suggested work describes a multimodal biometrics method that uses a Face and Iris (FI) based model. At first, multi-feature based programmed FI recognition in dim lighting is provided. the FI image is used as the input for the work proposed here. Methods based on normalization or lighting has been presented to obtain good performance under illumination variations. After FI images are preprocessed, the Gabor features, Local Binary pattern (LBP) features, and phase congruency features are retrieved. Z score level fusion is used to combine the extracted features and generate a key. Deep Neural Network (DNN) classifiers are used to identify FI images based on the fused keys. the experimental outcomes prove the proposed system outperforms the current system. However, when applied to color FI images, it does not yield accurate recognition results. © 2023 IEEE.

关键词： Biometrics

来源：评论

学校读者我要写书评

暂无评论

Enhancing Student Performance Prediction using E-learning through Multimodal data Integration and machine learning Techniques

Enhancing Student Performance Prediction using E-Learning th...

引用

Sentiment Analysis and Deep learning (ICSADL), international conference on

作者： NS Koti Mani Kumar Tirumanadham thaiyalnayaki S Ganesan V Department of CSE Bharath Institute of Higher Education and Research Chennai India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

Advanced machine learning techniques have shown significant promise in predicting student performance in E-Iearning systems, but challenges such as handling imbalanced datasets, integrating multimodal behavioral data, and managing the complexities of feature selection persist. Recent techniques, such as SMOTE for class balancing and BorutaNetCV for feature selection, have made strides in improving prediction accuracy; however, they often fail to address real-time cognitive state integration and the influence of diverse engagement patterns. To overcome these limitations, this study employs a comprehensive methodology that combines robust preprocessing methods, advanced feature selection, and ensemble machine learning models such as Random Forest, AdaBoost, and XGBoost. the findings demonstrate that predictive accuracy can be significantly enhanced through these techniques, and the proposed framework enables the development of personalized interventions that can foster improved student engagement and success in dynamic E-learning environments.

关键词： Sentiment analysis Accuracy Electronic learning Computational modeling Education Predictive models Feature extraction Real-time systems pattern recognition Random forests

来源：评论

学校读者我要写书评

暂无评论

Early Detection and Classification of Plant Diseases/Abiotic Disorders using Deep learning-A Review 4

Early Detection and Classification of Plant Diseases/Abiotic...

引用

4th international conference on Inventive Research in Computing Applications, ICIRCA 2022

作者： Suganya, J. Jebadurai, Jebaveerasingh Jebadurai, Immanuel Johnraja Paulraj, Getzi Jeba Leelipushpam Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Plant diseases and abiotic disorders are crucial elements in affecting the yield and quality of plants. thus, an early detection is obligatory to increase the productiveness. Diagnosing a plant disease is very pivotal at the fundamental stage. But in recent years, it can be carried out by Artificial Intelligence based machine learning and deep learning algorithms. Comparatively deep learning has obtained good accuracy in the field of image processing than other traditional methods. this review explores the research progress in plant diseases recognition using deep learning in recent years. this paper presents the summary of the layout of plant diseases and its causes, traditional classification methods/DL models used in plant diseases, information and statistical data of the existing models. the paper also discusses some important techniques used in DL models, datasets and performance measures. It is hoped that this paper will be an assistive asset to those who wish to explore the plant disease recognition using deep learning. © 2022 IEEE.

关键词： learning algorithms

来源：评论

学校读者我要写书评

暂无评论

2022 IEEE 4th international conference on BioInspired Processing, BIP 2022

2022 IEEE 4th International Conference on BioInspired Proces...

引用

4th IEEE international conference on BioInspired Processing, BIP 2022

ISBN: (纸本)9781665470483

the proceedings contain 16 papers. the topics discussed include: towards text simplification in Spanish: a brief overview of deep learning approaches for text simplification;improving semi-supervised deep learning by using automatic thresholding to deal with out of distribution data for Covid-19 detection using chest X-ray images;analysis software for the principal physical properties in food matrices;recognition of grammatical classes of overt speech using electrophysiological signals and machine learning;comparison of Nextera XT and Collibri Es library preparation kits: from wet lab to bioinformatics analysis;data quality metrics for unlabeled datasets;towards an understanding of the lipophilicity of non-coded amino acids: computational simulations of proline analogs;gene expression analyses of gingival tissue of patients with periodontitis using public transcriptomic data;and miRNA networks regulating gene expression in response to tension or compression forces in the cells of the periodontal ligament.

关键词：

来源：评论

学校读者我要写书评

暂无评论

the Method of Restoration and Identification of Information Flows in the Information Space 4

The Method of Restoration and Identification of Information ...

引用

4th IEEE international conference on Advanced Trends in Information theory, ATIT 2022

作者： Zamrii, Iryna Shkapa, Viktoriya Vlasyk, Hanna State University of Telecommunications Kyiv Ukraine

ISBN: (纸本)9798350332629

the use of integrated data management information systems not only ensures the smooth operation of each system throughout the enterprise, but also encourages the maximum removal of manual production management by integrating computerized systems of all departments to create a single information space management of the entire enterprise. this requires the improvement and development of new methods, such as recognition, identification, verification, etc., to establish all the elements of the information space and the relationships between *** paper describes in detail the block diagram of the algorithm for identifying the input atomic elements of the information space in the information space, which is the union of all information spaces of the enterprise. that allows you to constantly update, add and accumulate new information in databases and information space. the effectiveness of this method of identification was tested with the help of machine learning methods. the method of restoring the parameters of atomic elements of the information space is also considered in detail. © 2022 IEEE.

关键词： 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178页 << < 36 37 38 39 40 41 42 43 44 45 > >>

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：