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91-100 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：

Multi-view Contrastive learning for Next POI Recommendation 24

Multi-view Contrastive Learning for Next POI Recommendation

引用

8th international conference on Computing and data Analysis, ICCDA 2024

作者： Zhang, Jin Zhu, Guixiang Chen, Yihan Lu, Yiheng Wang, Xinyi Feng, Shi Jiangsu Open University Jiang Su Nanjing China Nanjing University of Finance and Economics Jiang Su Nanjing China

ISBN: (纸本)9798400710445

Next POI recommendation aims to forecast their subsequent locations, which base been an important applications for Location-Based Services (LBS). Recently, there has been a growing interest in the investigation of POI recommendation using various deep learning techniques, and achieved great success. However, most of them only model the users preferences from a single view, such as the graph-structured features in the trajectory that indicate the preferences of individuals, or the dynamic change of personal preferences from trajectory sequences. Moreover, they ignore leverage the unique self-supervised signals to guide those two views of user preferences leaning perform better. To fill these critical voids, this paper proposes a Multi-View Contrastive learning for next POI recommendation named MVCL-POI. Specifically, MVCL-POI first exploits dynamic-aware GCN from trajectory graph to automatically extract graph-structured features with considerations of rich node connections. After that, MVCL-POI utilizes a temporal-aware transformer to capture users’ dynamic interest from their historical trajectory sequences. Finally, a multi-view contrastive learning is designed to maximize the agreement between two views of users’ representations. Experiments results on two real-life LBSN datasets show that MVCL-POI yields significant performance advantages over the competitive next POI recommendation methods. © 2024 Copyright held by the owner/author(s).

关键词： Contrastive learning

来源：评论

学校读者我要写书评

暂无评论

8th international Workshop on Chatbots and Human-Centered AI, CONVERSATIONS 2024

8th International Workshop on Chatbots and Human-Centered AI...

引用

8th international Workshop on Chatbots and Human-Centered AI, CONVERSATIONS 2024

ISBN: (纸本)9783031880445

the proceedings contain 15 papers. the special focus in this conference is on Chatbots and Human-Centered AI. the topics include: Exploring the Effects of Consistency-Based Hallucination Detection for LLM-Based QA Chatbots: A Simulation Study;LadderChat An LLM-Based Conversational Agent for Laddering Interviews;can machine learning Models Recognise Emotions, Particularly Neutral, Better than Humans?;An AI-Powered learning Companion for Adaptive and Personalized STEM Education;Development and Evaluation of a University Chatbot Using Deep learning: A RAG-Based Approach;a Voice-Enabled Intelligent Virtual Agent for People with Memory Impairments: thematic Analysis of Focus Group Results;the BookBot Project: Conceptual Design of a Social Robot Facilitating Reading Motivation;Questions People Ask ChatGPT Regarding their Romantic Relationships and What they think About the Provided Answers: An Exploratory Study;AI-Driven Dialogue: Leveraging Generative AI in Conversational Agent Voting Advice applications (CAVAAs);first Aid for Europe – A Study on the Impact of Digital Voting Assistants on Young Adults During the Elections for the European Parliament in 2024;an Analysis of Federal and Municipal Chatbots in Germany;LLM-Powered Conversational AI in Customer Service: Users’ Expectations and Anticipated Use;Feeling Understood by AI: How Empathy Shapes Trust and Influences Patronage Intentions in Conversational AI.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Proposing a machine learning Approach for Cardiovascular Disease Prediction 8th

Proposing a Machine Learning Approach for Cardiovascular Dis...

引用

8th international conference on Microelectronics Electromagnetics and Telecommunications, ICMEET 2023

作者： Singh, Vaibhav Kant Nagwanshi, Kapil Kumar Jaiswal, Manjit Yadav, Nageshwar Dev Department of Computer Science and Engineering Guru Ghasidas Vishwavidyalaya A Central University Chhattisgarh Bilaspur India

ISBN: (纸本)9789819784219

Heart Disease is a very Common Disease in India, the death rate is almost one person per day. the situation seems to be demanding of a system that is going to help in the process of detection so that the problem could be handled in a proper way. We are in search of a system or technique that can reduce the death rate and should be very reliable. In the current time machine learning is the technology for the health sector. We in the current work made an exploration of the machine learning landscape or the support vector machine for handling the problem under consideration. We took experimental analysis data from Kaggle. We performed training using different kernels applicable for support vector machine. In the sections presented in the paper, we will be discussing the Introduction where we will be having a brief overview of the concepts under consideration. then we will look into the problem statement. After which, there is a brief literature review section where we will acknowledge various works done in the field that are helpful in presenting the current work. We will be having a result and implementation section immediately after which we will be having the conclusion section. In the conclusion, we will observe the comparative analysis of the performances of the various kernels for the cardiovascular disease prediction. © 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

Sub-Batch Update Mechanism for Component-Wise Natural Gradient Descent 24

Sub-Batch Update Mechanism for Component-Wise Natural Gradie...

引用

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

作者： Van Tran, Sang Nakata, Toshiyuki Yamaguchi, Rie Shigetomi Mhd, Irvan Yoshimoto, Yoshihide Graduate School of Information Science and Technology The University of Tokyo Bunkyo Tokyo Japan

ISBN: (纸本)9798400718014

Neural networks have become a cornerstone of modern machine learning, powering advances in numerous domains. In distributed computing environments, leveraging large batch sizes is crucial for the efficient training of these networks. However, this approach often leads to reduced data stochasticity when sampling information such as the loss function gradient, adversely affecting the generalization performance of the models. We tackle this issue by introducing the Sub-Batch update mechanism, which divides the large batch into sub-batches and updates the network parameters using each sub-batch. the Sub-Batch update mechanism increases the number of nonlinear operations of calculating the neural network parameter update vector from the sampled network information in Component-Wise Natural Gradient Descent (CW-NGD) neural network training algorithm. this increases the data stochasticity, resulting in accuracy improvement in the trained neural network. Experimental results show that with Sub-Batch update mechanism applied CW-NGD produces trained networks with higher accuracy compared to Adam, SGD, across all six datasets tested, including the ImageNet dastaset. © 2024 Copyright held by the owner/author(s).

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

8th international Symposium on Intelligent Informatics, ISI 2023

8th International Symposium on Intelligent Informatics, ISI ...

引用

8th international Symposium on Intelligent Informatics, ISI 2023

ISBN: (纸本)9789819721467

the proceedings contain 30 papers. the special focus in this conference is on Intelligent Informatics. the topics include: Multi-filter-Based Image Pre-processing on Face Mask Detection Using Custom CNN Architecture;a Handy Simulated Radar Interface for Black Flight Identification System;Spatial Pyramid Image Representation with DCT Features for Offline Signature Verification;Detection of AI Manipulated Videos Using Modern Deep learning Algorithms;comprehensive Exploration of Deepfake Detection Using Deep learning;Options Trading Strategy Based on GRU Forecasting;denoising Historical Text Documents Using Generative Adversarial Networks;comprehensive Survey of Audio-to-Text Conversion;Rainfall Forecasting Using High Spatiotemporal Satellite Imagery and machine learning Techniques: A Case Study Using INSAT 3DR data;the Personalization of Justified Recommendations Using the Users Profile Interest and Reviews;disease Detection in Tomato Plant Leaf Using Deep learning Techniques;boosting Precision Agriculture Using Deep learning Models on Edge Devices;comprehensive Review of Capsule Networks with a Case Study on Potato Leaf Disease Detection Using CapsNet and Attention Mechanism;DenseFed-PSO: Particle Swarm Optimization-Based DenseNet Federated Model in Alzheimer's Detection;a machine learning-Based Marine Vessel/Ship Classification Using Passive Sonar Signals—A Multi-class Problem;a Computer-Aided Diagnosis System for the Detection of Parkinson’s Disease;Impact of the Use of Social Media on the Addiction and Social Isolation Levels of Adolescents After the COVID-19 Pandemic;preliminary Testing of a Color-Based Test Kit Detector for Bioplastics;applications of Artificial Intelligence in Biosensors;Enhancing Bamboo Dryer Using IOT Control;chaotic Resilience: Enhancing IoT Security through Dynamic data Encryption;Enhancement of Malware Detection Systems Using Mal-cGAN;similarity learning and Genetic Algorithm Based Novel S-Box Optimization;A Survey on Deciphering of EEG Wa

关键词：

来源：评论

学校读者我要写书评

暂无评论

Forecasting New Mobile Site Location Suitability Using machine learning

Forecasting New Mobile Site Location Suitability Using Machi...

引用

conference on data science and machine learning applications (cdma)

作者： Zeeshan Rabbani Seyed Ebrahim Hosseini Shahbaz Pervez Chattha Gasim Alandjani Nasser Abosaq Mazlina Abdul Majid School of Information Technology Whitecliffe College Auckland New Zealand School of Information Technology Whitecliffe College Christchurch New Zealand School of Information Technology Whitecliffe College Wellington New Zealand Computer Science and Engineering Yanbu Industrial College Yanbu Saudi Arabia Faculty of Computing Universi Malaysia Pahang Al-Sultan Abdullah Pekan Malaysia

ISBN: (数字)9798331539696

ISBN: (纸本)9798331539702

the increasing density of mobile networks has made the identification of optimal new coverage sites a critical challenge for mobile operators. Traditional methods relying on manual inspections and council plans are labour-intensive and insufficient. this study addresses this issue by leveraging data science and machine learning techniques to predict the suitability of new mobile cell sites. Utilizing data from Radio Spectrum Management New Zealand and Stats New Zealand, the study employs Random Forest as machine learning model. Key factors considered include existing operator information and population density. the methodology integrates data cleaning, feature engineering, and model training, with validation performed using Power BI. Results demonstrate an accuracy of 84.62% for the Random Forest model, highlighting the importance of geographical location and population density in site suitability predictions. this approach will streamline the site selection process and enhance service quality, positioning operators as leaders in underserved areas.

关键词： Training Accuracy Predictive models data science data models Reliability Multiaccess communication Random forests Population density Radio spectrum management

来源：评论

学校读者我要写书评

暂无评论

Enhancing Load Forecasting with VAE-GAN-Based data Cleaning for Electric Vehicle Charging Loads 10th

Enhancing Load Forecasting with VAE-GAN-Based Data Cleaning ...

引用

29th international conference on database Systems for Advanced applications (DASFAA)

作者： Zhang, Wensi Lei, Shuya Jiang, Yuqing Yao, Tiechui Wang, Yishen Sun, Zhiqing State Grid Smart Grid Res Inst Co Ltd Beijing Peoples R China State Grid Hangzhou Power Supply Co Hangzhou Peoples R China

ISBN: (纸本)9789819609130;9789819609147

With the popularization of environmental protection ideas, people are increasingly valuing low-carbon lifestyles and the economy. Electric vehicles play a crucial role in this transformation to reduce carbon emissions. However, integrating electric vehicles into the power grid poses challenges, especially the possibility of destructive load peaks, which may endanger the stability and safety of the power grid. Accurately predicting the load of electric vehicles and managing grid scheduling are crucial for solving this problem. the current solutions are mainly divided into two categories: statistics-based methods and machine learning-based methods. Statistical methods require a large amount of long-term data modeling, making data collection a significant challenge. Similarly, machine learning-based methods have good long-term prediction performance on high-quality data, but they do not perform well in terms of short-term prediction accuracy. To overcome these obstacles, a comprehensive electric vehicle charging load prediction framework is proposed, which utilizes an innovative variational autoencoder to generate adversarial networks (VAE-GAN) for data processing, Principal Component Analysis (PCA) for feature extraction, and an improved CNN-GRU model for prediction. the experimental results show that the accuracy of short-term power load prediction is significantly improved, which verifies the effectiveness of the framework in processing small sample load data and provides advanced tools for intelligent management of electric vehicle charging stations.

关键词： load forecasting electric vehicles data cleaning variational autoencoder generate adversarial networks gated recurrent network

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of Transfer learning Models to Detect the Rice Plant Leaf Diseases from Real-Time data of Chhattisgarh State of India 8th

Performance Analysis of Transfer Learning Models to Detect t...

引用

8th international conference on Intelligent Technologies, ICIT 2023

作者： Rathore, Yogesh Kumar Janghel, Rekh Ram Pradhan, Monoj Department of Information Technology National Institute of Technology Raipur India Department of Computer Science and Engineering Shri Shankaracharya Institute of Professional Management andTechnology Raipur India Indira Gandhi Agricultural University Raipur India

ISBN: (纸本)9789819738588

the economic condition and living of many countries depend on agriculture which depends on the production and protection of crops from diseases. Many computerized techniques help to improve the plant disease detection capability accurately at an early stage. this study evaluates the performance of different classifiers on public and private datasets using various neural network architectures, including Alex-Net, Google-Net, Efficient-Net, VGG-16, Vgg-19, ResNet-50, ResNet-101, Shuffle-Net, and Xception-Net. the results show that the neural network architectures perform better than traditional machine learning classifiers, with most achieving perfect accuracy scores of 99.9%. the Q SVM (Quadratic SVM) classifier is the best-performing machine learning classifier, achieving near-perfect accuracy scores across all architectures. However, some architectures, such as ResNet-50 and ResNet-101, perform consistently well across many classifiers, while others, such as Efficient-Net, are not as consistent among the top-performing architectures. Overall, the study suggests that using neural network architectures can lead to excellent classification accuracy for this particular data, but traditional machine learning classifiers quadratic SVM can also perform well, with the decision tree classifier being the weakest performer among the classifiers tested. © 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

8th international conference on Intelligent Technologies, ICIT 2023

8th International Conference on Intelligent Technologies, IC...

引用

8th international conference on Intelligent Technologies, ICIT 2023

ISBN: (纸本)9789819738588

the proceedings contain 44 papers. the special focus in this conference is on Intelligent Technologies. the topics include: the Percentage Depth Dose Analysis of an Electron Beam for Various Energies Using Monte Carlo Simulation;Determination of Diagnostic Reference Levels for General Radiography in thorax, Abdomen, and Lumbar Spine Examinations at XYZ Hospital Using Tube Output Measurment;Hybrid IT Project Management Methodology Based on Best Practices of Project Management and Critical Success Factors Influencing IT Project Management;a Comprehensive Investigative Analysis of Emotional Intelligence: theoretical Frameworks, Measurement Methodologies, and Multifaceted applications;Enhanced Bidirectional GRUs with Self-attention for Medical Image Report Generation: A Deep learning Approach;Surrogate Model Assisted Multi-objective Optimization Using Morphing Techniques for FEM Simulations;intelligent Facial Recognition System for Vehicles;transfer learning with Mobile Net for Brain Tumor Detection in Neuroimaging;performance Analysis of Transfer learning Models to Detect the Rice Plant Leaf Diseases from Real-Time data of Chhattisgarh State of India;translator Chatbot in Cloud Environment Using Amazon Translate and Amazon Lex;leveraging Computational Techniques for Accurate Diagnosis of Early-Onset Alzheimer’s Disease;Impact Analysis and Parametric Evaluation of Open-Source Heterogenous DICOM Viewers: A Comprehensive Resource for Researchers and Practitioners;real-Time Myanmar Hand Gestures Recognition Using Deep learning Models;stock Trading Recommendation System with Fuzzy Logic;artificial Intelligence for Predicting Climate and Natural Disasters in Peru;Stock Price Prediction Using Fuzzy-RNN and Portfolio Management with Genetic Algorithm;machine learning Implementation with K-Nearest Neighbor (KNN) Algorithm to Predict Rainfall in Tangerang Regency;analysis of Tomato Leaf Diseases Detection Models;swarm Based Adaptive Control of Wearable Rehabilitation Robot.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Mezzo TLS 1.3 Protocol, Suitable for Transmitting Already-Encrypted data: – Short Paper – 8th

Mezzo TLS 1.3 Protocol, Suitable for Transmitting Already-E...

引用

8th international Symposium on Cyber Security, Cryptology, and machine learning, CSCML 2024

作者： Drucker, Nir Gueron, Shay IBM Research Haifa Israel University of Haifa Haifa Israel Meta Seattle United States

ISBN: (纸本)9783031769337

Secure communication protocols such as TLS 1.3 are used almost everywhere to protect the confidentiality and integrity of data in transit. the encryption part in these protocols does not come for free: it adds latency and consumes processing cycles. Although nowadays, modern computing platforms encrypt data very efficiently, the encryption overheads can be spared when they are not required. For example, if an application stores the data in an encrypted form, transferring it under TLS 1.3 involves double encryption (and decryption) of the data without adding privacy. Specifically, consider homomorphic encryption based applications or encrypted databases. this paper introduces "Mezzo-TLS 1.3", which is a version of TLS 1.3 that is suitable for already-encrypted inputs. We show that when the threat model allows for using Mezzo-TLS 1.3, this protocol can speed up data transfer by up to 2.58×. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Authentication Protocol

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 << < 6 7 8 9 10 11 12 13 14 15 > >>

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：