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

551 篇 会议
4 册 图书
4 篇 期刊文献

馆藏范围

559 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

330 篇 工学
- 302 篇 计算机科学与技术...
- 222 篇 软件工程
- 66 篇 信息与通信工程
- 55 篇 控制科学与工程
- 41 篇 生物工程
- 36 篇 生物医学工程（可授...
- 33 篇 电气工程
- 26 篇 电子科学与技术（可...
- 24 篇 动力工程及工程热...
- 21 篇 机械工程
- 20 篇 网络空间安全
- 19 篇 光学工程
- 12 篇 化学工程与技术
- 12 篇 安全科学与工程
- 10 篇 仪器科学与技术
- 8 篇 交通运输工程
115 篇 理学
- 47 篇 数学
- 45 篇 物理学
- 45 篇 生物学
- 25 篇 统计学（可授理学、...
- 12 篇 化学
95 篇 管理学
- 60 篇 管理科学与工程(可...
- 34 篇 图书情报与档案管...
- 19 篇 工商管理
29 篇 医学
- 28 篇 临床医学
- 23 篇 基础医学(可授医学...
- 12 篇 药学(可授医学、理...
- 9 篇 公共卫生与预防医...
16 篇 教育学
- 15 篇 教育学
13 篇 法学
- 12 篇 社会学
6 篇 农学
4 篇 经济学
2 篇 文学

主题

95 篇 machine learning
72 篇 human computer i...
70 篇 accuracy
57 篇 deep learning
35 篇 feature extracti...
31 篇 training
29 篇 convolutional ne...
28 篇 emotion recognit...
27 篇 predictive model...
27 篇 machine learning...
26 篇 computational mo...
21 篇 adversarial mach...
19 篇 real-time system...
18 篇 computer vision
18 篇 data models
17 篇 support vector m...
17 篇 artificial intel...
15 篇 reliability
14 篇 face recognition
14 篇 prediction algor...

机构

4 篇 school of materi...
3 篇 school of comput...
3 篇 school of inform...
3 篇 graphic era deem...
3 篇 new york univers...
2 篇 department of co...
2 篇 saveetha institu...
2 篇 school of comput...
2 篇 school of xiamen...
2 篇 singapore univer...
2 篇 dept. of compute...
2 篇 wuhan digital en...
2 篇 dept. of softwar...
2 篇 dept. of electro...
2 篇 chitkara univers...
2 篇 south china univ...
2 篇 school of comput...
2 篇 school of comput...
2 篇 department of in...
2 篇 dept. of compute...

作者

3 篇 surendran r.
3 篇 ggaliwango marvi...
2 篇 zhou jing
2 篇 r surendran
2 篇 julian anitha
2 篇 wenle bai
2 篇 qingle quan
2 篇 hanqing sun
2 篇 sharma ajay
2 篇 jac fredo agasti...
2 篇 jing zhou
2 篇 kulkarni hrishik...
2 篇 wu kai
2 篇 shahade makarand
2 篇 bharti
2 篇 sharma shamneesh
2 篇 bingyao liu
2 篇 nakayiza hellen
2 篇 vishalakshmi
2 篇 schiller dominik

语言

454 篇 英文
105 篇 其他
8 篇 中文

检索条件"任意字段=5th International Conference on Machine Learning and Human-Computer Interaction, MLHMI 2024"

共 559 条记录，以下是371-380 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：

Innovative Research on Smart Devices Based on the Optimization of Hardware Stacking Structure

Innovative Research on Smart Devices Based on the Optimizati...

引用

Intelligent Design (ICID), international conference on

作者： Xujing Huang Xiaolin Hu Han Liu Guanlu Wang School of Humanities and Design Chengdu Technological University Chengdu China Industrial Design Center Sichuan Engineering Equipment Design and Research Institute Co. Ltd. Chengdu China

ISBN: (数字)9798331541491

ISBN: (纸本)9798331541507

this article aims to explore innovative methods for promoting the improvement of overall performance and usability of smart devices through the optimization of hardware stacking structures. Firstly, without changing the technical principles and hardware selection, it analyzes user behavior, combines the “six characteristics” index and “human-machine engineering design principles” to sort out the mapping relationship between performance requirements, usability, and hardware elements, and summarizes the potential problems that the existing hardware layout may cause. then, the hardware stacking structure is designed and adjusted, and a hardware stacking structure is selected for appearance design in combination with market differentiation. Finally, the key performance and human-computer interaction comfort of the design are verified using SolidWorks engineering simulation software and Jack ergonomic software. In terms of the applicability of this method, it is more suitable for smart device projects with high user engagement, a high degree of modularization in subsystems, and a highly homogenized market for the entire equipment, providing a new perspective for traditional industrial design thinking. However, it is not suitable for purely functional equipment or devices with little human-computer interaction and no spatial constraint conditions.

关键词： Performance evaluation human computer interaction Technological innovation Ergonomics Stacking Hardware Software Smart devices Usability Optimization

来源：评论

学校读者我要写书评

暂无评论

Intelligent Error Correction Method for Electric Power Text Based on ELECTRA

Intelligent Error Correction Method for Electric Power Text ...

引用

Intelligent Computing and human-computer interaction (ICHCI), international conference on

作者： Zhanying Wang Tong Wu Mengzi Zhang Wende Wang State Grid Liaoning Electric Power Co. Ltd Shenyang China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

In the power industry, text information processing is a crucial task. Whether it's a day-to-day official document release, news writing, or an editorial response to a text related to the power system, a large amount of textual information needs to be processed precisely. With the continuous progress of technology and the expansion of application scope, text correction technology will bring more innovation and development opportunities to the power industry, and is of great significance to facilitate the sustainable progress of the power industry. In this paper, the statistical language model and the neural network-based pre-trained model are fused to train and verify the correction of typos in the power text, and finally the model effect is evaluated through the comprehensive index F1. the results show that the F1 values of the single pre-trained model and the single statistical language model are 0.5871 to 0.4738, respectively, which is lower than the F1 of the fusion model for text typo correction of 0.6354. this fusion method has a good effect on text typo correction in the power industry, and makes a positive impact in ensuring the quality of text related to the power system.

关键词： human computer interaction Technological innovation Computational modeling Information processing human factors Writing Power industry Power systems Indexes Few shot learning

来源：评论

学校读者我要写书评

暂无评论

A Deep learning Model for Classification of MDD Patients Studied with EEG Microstate Features

A Deep Learning Model for Classification of MDD Patients Stu...

引用

Intelligent Computing and human-computer interaction (ICHCI), international conference on

作者： Yuchen Jiang Yiyang Li Zhiwu Yang Meng'an Cao Zhaobo Li Fengchun Wu Kai Wu Jing Zhou School of Biomedical Sciences and Engineering South China University of Technology Guangzhou International Campus Guangzhou China Department of Psychiatry The Affiliated Brain Hospital Guangzhou Medical University Guangzhou China School of Material Science and Engineering South China University of Technology Guangzhou China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

the quasi-steady electric fields in electroencephalogram (EEG) are usually called microstates. In the field of neuroscience, methodologies like fMRI, EEG, and MEG have uncovered essential insights into the dynamics of extensive brain networks. Additionally, these techniques have quantified network characteristics using computational neuroscience approaches, which are vital for comprehending both brain information processing and pathological alterations. this study explored the role of abnormal resting-state microstate features in the recognition of MDD patients by deep learning. through factor analysis of microstate parameters, a new feature set that could explain the original microstate features was created and applied to the construction of a convolutional neural network (CNN) classification model. At the same time, a backpropagation learning mechanism was introduced, and the model's performance in distinguishing patients with MDD from healthy individuals was comprehensively evaluated using the k-fold cross-validation approach, alongside metrics such as accuracy, precision, and AUC. this provides strong support for medical research and clinical decision-making. the findings indicate that the accuracy of CNN classification is 97.8%, the precision is 98.2%, and the AUC is 0.980. the performance of the model shows that features of resting-state EEG microstate segmentation can be obtained to effectively assist in the identification of MDD patients.

关键词： Deep learning Measurement human computer interaction Analytical models Accuracy Computational modeling Information processing Brain modeling Electroencephalography Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Rainfall Prediction using Random Forest and XGBoost-A comparative study

Rainfall Prediction using Random Forest and XGBoost-A compar...

引用

Data Intelligence and Cognitive Informatics (ICDICI), international conference on

作者： Deepa Sharma Punam Rattan School of Computer Applications Lovely Professional University Jallandhar India School of Computer Applications Lovely Professional University Jallandhar Punjab India

ISBN: (数字)9798350389609

ISBN: (纸本)9798350389616

there are numerous aspects of human life where knowing how much rain to expect might be beneficial. Heavy rainfall events such as flash floods and landslides, as well as droughts, can be predicted with effective rainfall forecasting. Because of reliable weather forecasts, the infrastructure required to capture rainwater and cultivate crops may be planned ahead of time. With the advent of big data, new possibilities have arisen for weather prediction and research. A variety of machine learning and Deep learning algorithms enable accurate weather forecasting. this study aims to investigate the efficacy of Random Forest in forecasting rainfall in Jammu Region of Union Territory of Jammu and Kashmir and compare its performance with XGBoost using RMSE as performance metric. Hyperparameter Tuning is used to enhance the efficiency of the algorithms. the dataset is collected for a period of 10 years from 2012 to 2022. Random Forest comes out to be slightly better than XGBoost when compared on test data by having less RMSE.

关键词： Measurement Deep learning Rain machine learning algorithms Weather forecasting Prediction algorithms Jamming Forecasting Random forests Tuning

来源：评论

学校读者我要写书评

暂无评论

Understanding Dog Emotions through Deep learning: A CNN-based Classification Framework

Understanding Dog Emotions Through Deep Learning: A CNN-base...

引用

Smart Electronics and Communication (ICOSEC), international conference on

作者： Vishesh Tanwar Chitkara University Institute of Engineering & Technology Chitkara University Punjab India

ISBN: (数字)9798331504403

ISBN: (纸本)9798331504410

Our research article focuses on developing a deep learning-based Convolutional Neural Network (CNN) model for classifying dog emotions into four categories: sadness, happiness, relaxation, and anger. the significance of understanding canine emotions is highlighted, emphasizing the need for an accurate classifier to enhance animal welfare and the human-animal bond and Quality of life. We utilize a dataset collected from Kaggle and implement a CNN architecture, trained using the Stochastic Gradient Descent (SGD) optimizer. the methodology includes detailed descriptions of dataset preprocessing, model creation, and training procedures. Our experimental setup involves evaluation metrics, dataset partitioning, and computational resources. Results demonstrate the CNN model’s superior performance, achieving a validation accuracy of 99.60%, significantly outperforming other baseline models like Support Vector machine (SVM) and K-Nearest Neighbors (KNN), which achieved accuracies of $89 \%$ and $81 \%$, respectively. Practical applications of our model in veterinary care and human-dog interactions are discussed. Future directions suggest avenues for further research, including expanding the dataset and exploring different model architectures. the conclusion summarizes the key findings and emphasizes the implications for enhancing the understanding and interaction between humans and dogs.

关键词： Support vector machines Training Measurement Accuracy Computational modeling Stochastic processes Dogs computer architecture Nearest neighbor methods Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Question Generation using POS Tagging

Question Generation using POS Tagging

引用

Image Processing and Capsule Networks (ICIPCN), international conference on

作者： V Shobha Rani Akhil Reddy Chitiireddy Priyanka Suram G Neelima V Ramu G Sathish Kumar CS&AI SR University Hanamkonda India IIT Khargpur Khargpur India Dept of CS&DS Malla Reddy Engineering College Hyderabad India Dept of Computer Science Chaitanya (Deemed to be University) Hyderabad India

ISBN: (数字)9798350367171

ISBN: (纸本)9798350367188

In education, human-generated questions are commonly utilized to evaluate a student’s comprehension of a text. However, creating a computer program to do this is challenging due to the complexities of human language. Many existing methods rely on expensive tools for accuracy. Considering our research objectives, we suggest a different way of doing things that uses machine learning and pattern matching based on parts of speech to generate knowledge-testing questions from English text without the need for large semantic tools. this paper demonstrates the utilization of the Stanford Question Answering Dataset to improve question-answering performance on textual data extracted from PDF and TXT files. the research findings demonstrate the effective use of question-answering models, trained on SQuAD, to process and extract valuable information from PDF and TXT documents.

关键词： Image processing Semantics Education machine learning Tagging Portable document format Question generation

来源：评论

学校读者我要写书评

暂无评论

Advancing Stress Diagnostics using EEG and Deep learning Methods for Early Stress Identification: A Systematic Literature Survey

Advancing Stress Diagnostics using EEG and Deep Learning Met...

引用

Trends in Material Science and Inventive Materials (ICTMIM), international conference on

作者： Rabiya Nazeer Dhanpratap Singh School of Computer Science and Engineering Lovely Professional University Phagwara Punjab

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Stress is a growing global concern with significant psychological and physiological consequences, necessitating improved diagnostic methods for early detection and intervention. Electroencephalography (EEG) has emerged as a promising noninvasive tool for stress assessment, offering real-time insights into neurological responses. However, traditional methods struggle with the complexity and variability of EEG signals. this review systematically analyzes recent advancements in machine learning (ML) and deep learning (DL) applied to EEG-based stress detection. We assess various models, including Convolutional 1D (CONV1D), Bidirectional Long Short-Term Memory (BiLSTM), and Bidirectional Gated Recurrent Units (BiGRU), and their effectiveness in identifying stress patterns from EEG data. the study also explores the broader implications of EEG in diagnosing Alzheimer's disease and enabling brain-computer interfaces (BCIs), which enhance human-computer interactions, particularly for individuals with mobility impairments. Our findings suggest that integrating ML/DL with EEG can significantly enhance stress detection accuracy, paving the way for automated and scalable mental health diagnostics. By bridging the gap between neuroscience and artificial intelligence, this research contributes to the development of more precise, accessible, and preventive stress-monitoring solutions.

关键词： Deep learning human computer interaction Accuracy Computational modeling Mental health Medical services Brain modeling Electroencephalography Real-time systems Heart rate variability

来源：评论

学校读者我要写书评

暂无评论

CNN-Driven Novel Facial Expression Detection and Analysis

CNN-Driven Novel Facial Expression Detection and Analysis

引用

Smart Electronics and Communication (ICOSEC), international conference on

作者： Supriya Telsang Swaraj Patil Riya Patil Sanjeevani Patil Shraddha Patil Department of Engineering Sciences and Humanities (DESH) Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798331504403

ISBN: (纸本)9798331504410

Emotion is defined as gesture that humans use to express their thoughts and feelings. Different ways of expressing emotions includes facial expressions, body language and voice tone. human facial expressions have similar patterns, its tedious to recognize the facial impressions with naked eye. therefore, Convolutional Neural Network, a Deep learning technique is used in this research. there are 4 impressions of face which are to be identified here and they are laughter, crying, shame, and frustration. the dataset was created which consists total of 1760 images out of which 1600 were for training purposes and 160 images for testing purposes. In this study, CNN method was used to recognize these basic four emotions. After comparing the preprocessing methods in the CNN performance, 96.88% of recognition accuracy was achieved.

关键词： Training human computer interaction Deep learning Emotion recognition Accuracy Face recognition Neural networks Educational technology Convolutional neural networks Testing

来源：评论

学校读者我要写书评

暂无评论

Development of an Intelligent Intrusion Detection Model using an Ensemble of Deep learning Paradigm

Development of an Intelligent Intrusion Detection Model usin...

引用

IEEE international conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： Olamatanmi Josephine Mebawondu Tajudeen Adeleke Badmos Olufunsho D. Alowolodu Jacob Olorunshogo Mebawondu Department of Computing Afe Babalola University Ado-Ekiti Ado-Ekiti Nigeria Department of Computer Science Faculty of Information Technology Federal Polytechnic Nasarawa Nasarawa Nigeria Department of Cyber Security Federal University of Technology Akure Nigeria Department of Computer Science Federal Polytechnic Naasrawa Nasarawa Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

the internet's advent has permeated every aspect of our lives, resulting in an explosion of information generation and management. Deep learning, as an Artificial Intelligence (AI) function, mimics human intelligence in data processing for decision-making. Deep learning (DL) encompasses a variety of machine learning techniques where unsupervised and supervised feature learning can be implemented across multiple layers in hierarchical architectures. Combining deep learning techniques can mitigate the weaknesses of individual methods. this research aims to integrate deep learning techniques to develop an intelligent intrusion detection model. the combined models yield a Network Intrusion Detection System (NIDS) with superior performance compared to individual techniques. the results demonstrate that the ensemble model achieves an accuracy of 79%, surpassing single deep learning models.

关键词： Deep learning Representation learning humanities human intelligence MIMICs Decision making Network intrusion detection Data processing Explosions Ensemble learning

来源：评论

学校读者我要写书评

暂无评论

machine learning Based Object Detection and Voice Guidance Using Yolo Algorithm

Machine Learning Based Object Detection and Voice Guidance U...

引用

international conference on ICT in Business Industry & Government (ICTBIG)

作者： Sanjay S Mintu Kumar thakur Kushal Gowda Y N. Jayapandian Department of CSE Christ University Bangalore India Department of CSE Christ University India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

machine learning is used now a days in multidiscipline. Vision based or image-based application is very popular in healthcare and human interaction. the proposed model of this article is focus on visually challenged individuals to navigating the environment and ensure their safety by detecting nearby objects using the machine learning algorithm like YOLOV5 model. Secondary module is focus on alert intimation through speech notification. Clear vision is one of the God’s gifts, unfortunately so human is having some issue in their vision, this kind of modern technology will help to solve this issue. this model is mainly help to identify the object at the same time spatial location. computer vision algorithms, particularly those that leverage convolutional neural networks, are subsequently employed to identify and categorize objects within the scene. the spatial location of these objects is determined, potentially using depth sensors or stereo cameras to calculate distance and relative position. this integration of technology not only aids in recognizing objects but also enhances spatial awareness, contributing to safer and more confident navigation for visually impaired individuals. the average precision level of proposed model is 91% and average Recall value is providing 0.88.

关键词： YOLO computer vision machine learning algorithms Navigation Computational modeling machine learning Streaming media Sensors Object recognition Smart phones

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56页 << < 34 35 36 37 38 39 40 41 42 43 > >>

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：