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

668 篇 会议
24 册 图书
1 篇 期刊文献

馆藏范围

693 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

484 篇 工学
- 454 篇 计算机科学与技术...
- 315 篇 软件工程
- 74 篇 生物医学工程（可授...
- 72 篇 信息与通信工程
- 37 篇 控制科学与工程
- 33 篇 生物工程
- 24 篇 电气工程
- 20 篇 光学工程
- 20 篇 化学工程与技术
- 17 篇 机械工程
- 14 篇 安全科学与工程
- 11 篇 动力工程及工程热...
- 11 篇 交通运输工程
- 10 篇 仪器科学与技术
162 篇 理学
- 88 篇 数学
- 48 篇 统计学（可授理学、...
- 44 篇 生物学
- 34 篇 系统科学
- 24 篇 物理学
- 13 篇 化学
98 篇 管理学
- 67 篇 图书情报与档案管...
- 41 篇 管理科学与工程(可...
- 32 篇 工商管理
50 篇 医学
- 45 篇 临床医学
- 41 篇 基础医学(可授医学...
- 23 篇 公共卫生与预防医...
- 17 篇 药学(可授医学、理...
17 篇 法学
- 15 篇 社会学
13 篇 经济学
- 13 篇 应用经济学
13 篇 农学
- 13 篇 作物学
4 篇 教育学
4 篇 文学
2 篇 军事学

主题

142 篇 machine learning
50 篇 deep learning
47 篇 adversarial mach...
41 篇 accuracy
31 篇 machine learning...
31 篇 data models
29 篇 support vector m...
23 篇 data mining
21 篇 artificial intel...
21 篇 training
19 篇 feature extracti...
18 篇 predictive model...
18 篇 federated learni...
17 篇 multiaccess comm...
17 篇 convolutional ne...
15 篇 sentiment analys...
14 篇 neural networks
14 篇 data science
13 篇 real-time system...
12 篇 random forests

机构

6 篇 department of co...
6 篇 department of el...
4 篇 college of compu...
4 篇 department of ar...
4 篇 riphah college o...
4 篇 international in...
3 篇 department of co...
3 篇 department of co...
3 篇 college of compu...
3 篇 department of co...
3 篇 national superco...
3 篇 university of fl...
3 篇 school of comput...
3 篇 college of engin...
2 篇 school of crypto...
2 篇 college of compu...
2 篇 university of sc...
2 篇 kulliyah of info...
2 篇 school of comput...
2 篇 school of inform...

作者

6 篇 surendran r
5 篇 qureshi basit
5 篇 kodipalli ashwin...
4 篇 k s. balamurugan
4 篇 dewan md. farid
4 篇 rao trupthi
4 篇 saba tanzila
3 篇 de-shuang huang
3 篇 aljedaani wajdi
3 篇 nurtas marat
3 篇 kamal shoaib
3 篇 altaibek aizhan
3 篇 eljasik-swoboda ...
3 篇 sathish kumar p....
2 篇 panos m. pardalo...
2 篇 ludi stephanie
2 篇 chen yuedan
2 篇 giuseppe nicosia
2 篇 hemmje matthias
2 篇 jin guang

语言

571 篇 英文
117 篇 其他
35 篇 中文
1 篇 俄文

检索条件"任意字段=8th International Conference on Data Science and Machine Learning Applications, CDMA 2025"

共 693 条记录，以下是71-80 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：

Clustering based Medical Image Segmentation: A Study on MRI Scans of Brain Tumors 24

Clustering based Medical Image Segmentation: A Study on MRI ...

引用

8th international conference on Advances in Artificial Intelligence, ICAAI 2024

作者： Mimenbayeva, Aigul B. Aruova, Aliya A. Bekmagambetova, Gulmira K. Niyazova, Rozamgul S. Turebayeva, Rakhila D. Naizagarayeva, Akgul A. Tursumbayeva, Ainur F. Departament of Computational and Data Science Astana IT University Astana Kazakhstan Department of Computer Science Agrotechnical Research University Named after S. Seifullin Astana Kazakhstan L.N. Gumilyov Eurasian National University Department of Artificial Intelligence Technologies Astana Kazakhstan Department of Information Systems Kazakh Agrotechnical Research University Named after S. Seifullin Astana Kazakhstan

ISBN: (纸本)9798400718014

this study investigates the application of Hierarchical clustering for image segmentation, with a focus on its efficacy in analyzing medical images, particularly MRI scans of brain tumors. Image segmentation plays a pivotal role in computer vision, facilitating various applications across industries. Leveraging a systematic approach, we conduct a comprehensive review of recent literature on machine learning algorithms for image segmentation. Subsequently, utilizing a dataset comprising MRI images with and without tumors, we preprocess and analyze the data using the Histogram of Oriented Gradients (HOG) technique to extract pertinent features. these features serve as input for the Hierarchical clustering algorithm to partition the images into distinct regions of interest. For each row of vectors, the Jensen-Shenton distance was calculated. the resulting symmetric matrices are distances among the corresponding vectors, quantifying dissimilarity in cluster analysis. Our findings underscore the effectiveness of Hierarchical clustering in clustering medical images, with potential implications for advancing computational analysis in healthcare and related domains. © 2024 Copyright held by the owner/author(s).

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Snow Forecasting with machine learning to Unravel Meteorological Patterns for Precision Weather Prediction

Snow Forecasting with Machine Learning to Unravel Meteorolog...

引用

conference on data science and machine learning applications (cdma)

作者： Abdulaziz AlSowail Mohammed Almashal Musaed Bin Saeed Nidal Nasser Sara Benoumhani College of Engineering Alfaisal University Riyadh Saudi Arabia

ISBN: (数字)9798331539696

ISBN: (纸本)9798331539702

this paper delves into the dynamic realm of weather prediction, specifically focusing on the binary classification task of forecasting snowfall. Employing machine learning models, including Logistic Regression, Support Vector machine (SVM), and Decision Tree, we seek to unravel the intricate patterns and relationships within meteorological data. the dataset, centered around London's weather, captures diverse parameters such as cloud cover, sunshine, temperature, and precipitation, with the target variable indicating the presence or absence of snow. the methodology encompasses meticulous data cleaning, feature engineering, and model evaluation, shedding light on the models' efficacy in predicting snow events. Precision, recall, accuracy, and F1 score serve as key metrics, unraveling the nuances of model performance. the results, elucidated through confusion matrices and feature importance analyses, offer insights into the strengths and weaknesses of each model.

关键词： Support vector machines Logistic regression Accuracy Snow Clouds Weather forecasting machine learning Predictive models data models Forecasting

来源：评论

学校读者我要写书评

暂无评论

A Mobile Application for learning Baybayin Alphabet with Character Recognition 24

A Mobile Application for Learning Baybayin Alphabet with Cha...

引用

8th international conference on E-Society, E-Education and E-Technology, ESET 2024

作者： Lacorte, Alice Maldonado Gutierrez Calvez, Jeanne Pauline Atanacio, Marvin Menisis, Archie Natividad, Arniel Esguerra, Dave School of Architecture Computing and Engineering National University Philippines Batangas Lipa City Philippines Ninjavan Company Laguna Cabuyao Philippines Laguna Cabuyao Philippines

ISBN: (纸本)9798400707094

this paper introduces a mobile application designed to facilitate the learning and practice of the Baybayin script-an ancient writing system indigenous to the Philippines into a more interactive and engaging way. the scope delineates in the need for more comprehensive Baybayin learning resources, emphasizing the need for an interactive mobile application that will engage students or users to learn the said ancient writings. the methodology highlights the use of spiral model for software development and descriptive type of research for data gathering. Based on the results of the study, the application’s features include interactive lessons, quizzes, a progress tracker, and practice writing, with a distinctive character recognition system allowing users to receive real-time feedback on their writing skills. the overarching goals are to promote cultural awareness, improve Baybayin writing skills, deepen historical appreciation, and provide an engaging learning experience. the character recognition accuracy, employing machine learning algorithms, enhances the learning experience. It presented a detailed discussion of the results, encompassing cultural awareness, interactive way of familiarizing the writing system, improved writing skills, engaging learning experiences, and accessibility, positioning the app as a dynamic and valuable tool for Baybayin enthusiasts and learners to value its historical significance. © 2024 Copyright held by the owner/author(s).

关键词： Mobile applications

来源：评论

学校读者我要写书评

暂无评论

10th international Workshop on Big data Management and Service, BDMS 2024, 9th international Workshop on Big data Quality Management, BDQM 2024, DASFAA 2024 Workshop on Emerging Results in data science and Engineering, ERDSE 2024 and 8th international Workshop on Graph data Management and Analysis, GDMA 2024 held in conjunction with 29th international conference on database Systems for Advanced applications, DASFAA 2024

10th International Workshop on Big Data Management and Servi...

引用

10th international Workshop on Big data Management and Service, BDMS 2024, 9th international Workshop on Big data Quality Management, BDQM 2024, DASFAA 2024 Workshop on Emerging Results in data science and Engineering, ERDSE 2024 and 8th international Workshop on Graph data Management and Analysis, GDMA 2024 held in conjunction with 29th international conference on database Systems for Advanced applications, DASFAA 2024

ISBN: (纸本)9789819609130

the proceedings contain 26 papers. the special focus in this conference is on Big data Management and Service. the topics include: FAIth: A Fast, Accurate, and Lightweight database-Agnostic Learned Cost Model;fast Approximate Temporal Butterfly Counting on Bipartite Graphs via Edge Sampling;Financial-ICS: Identifying Peer Firms via LongBERT from 10K Reports;establishing a Decentralized Diamond Quality Management System: Advancing Towards Global Standardization;co-estimation of data Types and their Positional Distribution;Enhancing Load Forecasting with VAE-GAN-Based data Cleaning for Electric Vehicle Charging Loads;audio-Guided Visual Knowledge Representation;boundary Point Detection Combining Gravity and Outlier Detection Methods;A Meta-learning Approach for Category-Aware Sequential Recommendation on POIs;automatic Post-editing of Speech Recognition System Output Using Large Language Models;comparative Analysis with Multiple Large-Scale Language Models for Automatic Generation of Funny Dialogues;effectiveness of the Programmed Visual Contents Comparison Method for Two Phase Collaborative learning in Computer Programming Education: A Case Study;generating Achievement Relationship Graph Between Actions for Alternative Solution Recommendation;generating News Headline Containing Specific Person Name;Investigating Evidence in Sentence Similarity Using MASK in BERT;acceleration of Synopsis Construction for Bounded Approximate Query Processing;Query Expansion in Food Review Search with Synonymous Phrase Generation by LLM;Question Answer Summary Generation from Unstructured Texts by Using LLMs;Real Estate Information Exploration in VR with LoD Control by Physical Distance;voices of Asynchronous learning Students: Revealing learning Characteristics through Vocabulary Analysis of Notes Tagged in Videos;review Search Interface Based on Search Result Summarization Using Large Language Model;yes-No Flowchart Generation for Interactive Exploration of Personalized Health Improve

关键词：

来源：评论

学校读者我要写书评

暂无评论

PBHS: A Prediction-Based Scheduler for Hyperparameter Tuning 25

PBHS: A Prediction-Based Scheduler for Hyperparameter Tuning

引用

8th international conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2025

作者： Yu, Hong-Feng Chang, Cheng-Hsun Chou, Jerry National Tsing Hua University Hsinchu Taiwan

ISBN: (纸本)9798400713354

this paper presents PBHS, a prediction-based hyperparameter tuning scheduler. Recent years have seen the Cambrian explosion of deep learning technology powered by the rapid increment in both data availability and computational ability. Meanwhile, several experiments have shown that model architecture as well as its hyperparameters are the critical factors that affect the final performance, such that random network configuration can lead to catastrophic performance. As deep learning technology continuing to take places in everyday applications, it becomes crucial to develop a tool with well-designed algorithm that is able to develop the model by tuning hyperparameters automatically and find the best performance with corresponding hyperparameter configuration under time and resources limitations. Existing solutions only kill the candidate configurations base on their current performance, which may falsely kill some candidates that are actually very promising. thus, we design an auto-tuning scheduler combining with mathematical method to predict the trend of learning curve, so that the scheduler can look forward. We test our scheduler with various neural networks and data set, and prove its effective. © 2025 Copyright held by the owner/author(s).

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Setting Up a Georeferenced Road Accident database in Senegal: Automatic data Extraction and GIS Integration

Setting Up a Georeferenced Road Accident Database in Senegal...

引用

conference on data science and machine learning applications (cdma)

作者： Yoro DIA Mouhamadou Djimba thIAM Oumy NIASS Ousmane SALL Tony TONA LANDU Abdramane SOW Université Numérique Cheikh Hamidou KANE (Ex. UVS) Dakar SENEGAL Université Iba Der THIAM de Thiès Thiès SENEGAL Université Alioune DIOP de Bambey Bambey SENEGAL

ISBN: (数字)9798331539696

ISBN: (纸本)9798331539702

Road accidents are a major public health issue, leading to numerous deaths and injuries each year. the lack of data on these accidents in this country hinders prevention efforts. this paper presents a study aimed at filling this gap by creating a database of road accidents from Senegalese websites using web scraping and Natural Language Processing (NLP) techniques. the collected data is then integrated into a Geographic Information System (GIS) to visualize high-risk areas and facilitate the analysis of accident trends. the goal is to provide accurate and actionable information for road accident prevention.

关键词： Road accidents Accuracy databases Social networking (online) Prevention and mitigation Soft sensors machine learning Natural language processing Safety Geographic information systems

来源：评论

学校读者我要写书评

暂无评论

Image Generation from Arabic Text: Comparative Study of Proposed Architectures 8th

Image Generation from Arabic Text: Comparative Study of Prop...

引用

8th international conference on Arabic Language Processing

作者： Bahani, Mourad El Ouaazizi, Aziza Maalmi, Khalil Essahlaoui, Abdelouahed Sidi Mohamed Ben Abdellah Univ Natl Sch Appl Sci Artificial Intelligence Data Sci & Emerging Syst Fes Morocco Sidi Mohamed Ben Abdellah Univ Lab Engn Sci FPT Taza Morocco

ISBN: (纸本)9783031804373;9783031804380

Text-to-image generation is a cutting-edge technology that enables computers to generate images from textual descriptions. While this technology has been extensively researched and applied to English language text, applying it to Arabic language text is still in its early stages. Additionally, the Arabic language is challenging due to its right-to-left writing system and extensive vocabulary of 1.3 million words. In this paper, we explore text-to-image generation for generating images from Arabic language text descriptions. Firstly, we fine-tune a transformer-based model pre-trained on the Arabic text to transform the text information into affine transformation within the DF-GAN generator. Secondly, we present a text transformer that combines LSTM layers to address the limitation of unrecognized words. thirdly, a mask predictor is trained into the generator using a weakly supervised method and incorporated into the affine transformation for a more effective integration of image and text features. In addition, we add the DAMSM loss function as a regularization to the loss function to achieve convergences and stability in the training phase. the experiment on two challenging datasets CUB and Oxford-flower shows that our architectures can accurately generate high-quality images faithfully representing the Arabic textual descriptions. We believe the scaling of this task could have critical applications in fields such as Arabic visual learning, e-commerce, advertising, and entertainment.

关键词： machine learning Deep learning Computer Vision Generative Adversarial Networks Text-to-Image Generation Arabic Text Processing

来源：评论

学校读者我要写书评

暂无评论

8th international conference on Intelligent Transport Systems, INTSYS 2024

8th International Conference on Intelligent Transport System...

引用

8th international conference on Intelligent Transport Systems, INTSYS 2024

ISBN: (纸本)9783031863691

the proceedings contain 25 papers. the special focus in this conference is on Intelligent Transport Systems. the topics include: Interoperable Traceability in Supply Chains: A Use Case in Agritech;treemob: Expressive Mobility data Representation through Tree-Based Structures;From GPS Traces to Individual Emission Exposure: A data-Driven Four-Step Process;capacity Vehicle Routing Problem with Time Windows: Simulation Tool for Footprint Network Design;chain of Portable Health Folders: A Systematic Literature Review;integrating Metro Infrastructure in Circular Food Supply Chains: A Model for Decentralized Quito’s Food Bank Network Redesign;An AutoML Approach for Bike Demand Forecasting and Redistribution;adaptive Stop-Skipping Scheduling Approach Using Reinforcement learning;machine learning Approach for Labeling Undetected Planned Trips in Public Transport Operators;reinforcement learning Algorithms with Graph Convolution Networks for Traffic Signal Control;optimizing Intelligent Transportation Systems with Multi-agent Reinforcement learning: A Socio-economic Impact Assessment;a Mobile Application to Secure Pedestrians Interacting with Automated Vehicles;A Simulation-Based Security Benchmarking Approach for Assessing Cooperative Driving Automation (CDA) applications;wireless Interference and Regulatory Frameworks for Frequency Allocation in V2X Communication Systems;runtime Norms Regulation Framework for Drones’ Smart Cities applications;a data-Driven Integrated Framework for Virtual Testing of Autonomous Vehicles in Mixed Traffic Scenarios;federated learning for Lane-Change Prediction;Evaluating Traffic Control Strategies for Autonomous Shuttle in Different AV Penetration, Using SUMO Traffic Simulation;Adaptive Video Bitrate Allocation for Remotely Operated Vehicles (ROV);experimental Evaluation of Road-Crossing Decisions by Autonomous Wheelchairs Against Environmental Factors;impact of Network Delays on Edge-Assisted Platooning Systems in 5G Networks: Addressing Lat

关键词：

来源：评论

学校读者我要写书评

暂无评论

Speech Recording Analysis for Parkinson’s Detection Using machine learning Approach 8th

Speech Recording Analysis for Parkinson’s Detection Using M...

引用

8th IFIP TC 12 international conference on Computer, Communication and Signal Processing, ICCCSP 2024

作者： Deepika, G. Vinothiyalakshmi, P. Department of Computer Science and Engineering Sri Venkateswara College of Engineering Chennai India

ISBN: (纸本)9783031736162

Parkinson’s Disease (PD) is a neuro-degenerative disorder that affects the motor skills of a person when the production of dopamine is reduced and eventually motor dysfunction. Dopamine is a chemical produced by brain cells, which is responsible for controlling movements. thus, if Parkinson’s disease is detected earlier, then the progression and the effects of its symptoms can be controlled. the proposed Parkinson’s Disease Detection (PDD) model used for the detection of Parkinson’s Disease using various machine learning (ML) algorithms such as K-Nearest Neighbor (KNN), Support Vector machine (SVM), Logistic Regression (LR), Voting Classifier, and Random Forest (RF). the algorithms are applied on balanced data scales and on features selected using LDA and PCA from the speech recording dataset. On experimental analysis, the SVM algorithm is found to be more efficient on the balanced dataset and PCA extracted features, giving an accuracy of 96.73% and 95.42% respectively as compared to the other classification algorithms. While the Random Forest algorithm gives the best results on LDA applied dataset giving an accuracy of 95.85%. © IFIP international Federation for Information Processing 2025.

关键词： Random forests

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Review of Capsule Networks with a Case Study on Potato Leaf Disease Detection Using CapsNet and Attention Mechanism 8th

Comprehensive Review of Capsule Networks with a Case Stud...

引用

8th international Symposium on Intelligent Informatics, ISI 2023

作者： Shenbaga Moorthy, Rajalakshmi Arikumar, K.S. Prathiba, Sahaya Beni Pabitha, P. Sri Ramachandra Faculty of Engineering and Technology Sri Ramachandra Institute of Higher Education and Research Chennai600 116 India Department of Data Science and Business Systems SRM Institute of Science and Technology Kattankulathur Chennai603 203 India Centre for Cyber Physical Systems School of Computer Science and Engineering Vellore Institute of Technology Chennai600127 India Department of Computer Technology Anna University Madras Institute of Technology Campus Chennai600044 India

ISBN: (纸本)9789819721467

Accurate solutions are needed for a variety of computer vision applications, including medical imaging, object detection, and recognition. Such complicated challenges are beyond the capabilities of artificial intelligence and machine learning, which mainly rely on data and algorithms to learn. the path to Deep learning (DL) is thus paved. Even though deep learning is incredibly effective at solving complex problems, it is invariant, meaning that it ignores the spatial relationship between the features and instead searches for features only. this can cause the model’s performance to suffer. Additionally, because the model is invariant, gathering a large volume of training data is a difficult undertaking. To address this, the Capsule Network (CapsNet), whose performance outperforms Deep learning techniques, was introduced. Despite its success, applications of CapsNet and working remain a mystery. thus, the performance of CapsNet across many applications and obstacles is examined in this study together with the predecessors of CapsNet. Additionally, this paper explores the use of Capsule Networks with an attention mechanism (CapsNet-ATM) for predicting potato leaf diseases. the performance of CapsNet-ATM in this crucial agricultural application is thoroughly assessed and contrasted with the well-known models VGG-16 and VGG-19, providing insight into the system’s efficacy and promise as a reliable tool for the detection and prediction of potato leaf disease. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial 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70页 << < 4 5 6 7 8 9 10 11 12 13 > >>

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：