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

4,137 篇 会议
38 册 图书
6 篇 期刊文献

馆藏范围

4,181 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,738 篇 工学
- 2,465 篇 计算机科学与技术...
- 2,042 篇 软件工程
- 616 篇 生物工程
- 587 篇 信息与通信工程
- 362 篇 生物医学工程（可授...
- 266 篇 控制科学与工程
- 216 篇 电气工程
- 211 篇 光学工程
- 148 篇 安全科学与工程
- 136 篇 机械工程
- 124 篇 电子科学与技术（可...
- 118 篇 化学工程与技术
- 107 篇 交通运输工程
- 91 篇 动力工程及工程热...
1,369 篇 理学
- 675 篇 数学
- 646 篇 生物学
- 332 篇 统计学（可授理学、...
- 307 篇 物理学
- 197 篇 系统科学
- 127 篇 化学
720 篇 管理学
- 393 篇 管理科学与工程(可...
- 388 篇 图书情报与档案管...
- 237 篇 工商管理
340 篇 医学
- 315 篇 临床医学
- 308 篇 基础医学(可授医学...
- 221 篇 药学(可授医学、理...
- 125 篇 公共卫生与预防医...
159 篇 法学
- 138 篇 社会学
157 篇 教育学
- 155 篇 教育学
141 篇 农学
- 140 篇 作物学
89 篇 经济学
9 篇 军事学
5 篇 文学

主题

526 篇 machine learning
243 篇 deep learning
117 篇 support vector m...
99 篇 adversarial mach...
92 篇 accuracy
92 篇 machine learning...
83 篇 forecasting
75 篇 convolutional ne...
70 篇 predictive model...
69 篇 feature extracti...
58 篇 artificial intel...
53 篇 students
51 篇 learning systems
48 篇 decision trees
48 篇 training
47 篇 reinforcement le...
47 篇 computational mo...
47 篇 computer vision
46 篇 internet of thin...
41 篇 neural networks

机构

46 篇 chitkara univers...
15 篇 graphic era hill...
10 篇 college of manag...
9 篇 graphic era deem...
8 篇 computer science...
8 篇 beijing universi...
7 篇 school of comput...
7 篇 school of comput...
7 篇 school of comput...
7 篇 department of in...
6 篇 università di ca...
6 篇 infn sezione di ...
6 篇 north-west unive...
6 篇 computer science...
6 篇 lovely professio...
6 篇 in2p3 lpc campus...
6 篇 kkr and ksr inst...
6 篇 institut univers...
6 篇 national centre ...
6 篇 greater bay area...

作者

18 篇 kukreja vinay
15 篇 mehta shiva
10 篇 william p.
8 篇 sharma vikrant
7 篇 mahamudul hasan
7 篇 shiva mehta
6 篇 chen a.
6 篇 benoit d.m.
6 篇 ferrara g.
6 篇 ardid m.
6 篇 calvo d.
6 篇 gagliardini s.
6 篇 eddymaoui a.
6 篇 kulikovskiy v.
6 篇 labalme m.
6 篇 gal t.
6 篇 bozza c.
6 篇 khatun a.
6 篇 kalekin o.
6 篇 huang f.

语言

3,930 篇 英文
250 篇 其他
34 篇 中文

检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

共 4181 条记录，以下是1501-1510 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：

5th international conference on Real Time Intelligent Systems, RTIS 2023

5th International Conference on Real Time Intelligent System...

引用

5th international conference on Real Time Intelligent Systems, RTIS 2023

ISBN: (纸本)9783031558474

the proceedings contain 41 papers. the special focus in this conference is on Real Time Intelligent Systems. the topics include: the application of Artificial Intelligence Technology in Dance Teaching;design of a Cabin English Automatic Broadcasting Detection System Based on Deep learning;application of Improved Clustering Algorithms in Modern Education Technology’s Blended learning;an IoT Blockchain to Improve the Traceability on Agri-Food applications;process Analysis of Depression Expression and Action Changes and their Psychological Integration Based on Deep learning Algorithms;moderating the Role of Real-Time Intelligence Systems in the Relationship Between Emotional Intelligence and Employee Performance;optimization of Logistics Distribution Route Based on Improved Genetic Algorithm;carrier Adjustment Algorithm for Mobile Communication Network Based on Deep Reinforcement learning;diabetic Retinopathy Detection Using Amalgamated Deep learning Algorithm;evaluation Method of College Students’ Education Based on Artificial Neural Networks;research on Intelligent Algorithm-Based Swimming Athlete Pose Recognition and Correction Method;study on a Web-Based Remote Classroom English Writing Practice System Using Intelligent Model;coordination Training and Testing of Upper and Lower Limbs in Aerobics Under Neural Networks;vocal Melody Extraction Based on Sparse Autoencoding Neural Networks;Football Players’ Physical Parameter Simulation Training Based on AI Intelligent Simulation;Total Cost of Ownership Optimization for ERP System Implementation Project Using Advanced Technologies;design of Neural Network-Based Intelligent Robot-Assisted English Translation System;english Language Translation machine System Based on Human-computer Interaction;early Warning of Subjective Perception of Students Based on Big Data Analysis Techniques in Growth Environment;towards an Autonomous Response System. Case: Denial of Service Attacks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

machine learning application for News Text Classification 13

Machine Learning Application for News Text Classification

引用

13th international conference on Cloud Computing, Data Science and Engineering, Confluence 2023

作者： Agarwal, Jyoti Christa, Sharon Pai, H. Aditya Kumar, M. Anand Prasad, M.S. Guru Graphic Era Deemed to Be University Dept of Cse Dehradun India Graphic Era Deemed to Be University Dept of Computer Applications Dehradun India

ISBN: (纸本)9781665462631

News article are the source of historic information that can be accessed whenever required. Today in modern world, Internet is also doing the same task and full of online news on multiple topics which also contains some irrelevant or unhelpful information. People are living a very busy and hectic life and they does not have enough time to read the complete news article. they want to read information as per their area of interest. therefore, it becomes important to process online news content and classify them into various categories like sports, entertainment, Business, Finance etc. so that it become easily and quicky accessible to the user. this paper is an attempt in the direction of classifying the news text into different sections using machine learning algorithms. Experiment is performed on an online dataset taken from Kaggle. this dataset was having around 210K news headlines from 2012 to 2022. Four different classification algorithms (Random Forest, Decision Tree, K-Neighbor Classifier and Gaussian NB) are applied on the dataset to find the results. © 2023 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Elevating Aloe Vera Leaf Disease Detection through Federated learning CNNs 4

Elevating Aloe Vera Leaf Disease Detection through Federated...

引用

4th IEEE international conference on Smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2023

作者： Sharma, Vikrant Kukreja, Vinay Mehta, Shiva Garg, Navin Graphic Era Hill University Computer Science And Engineering Uttarakhand Dehradun India Chitkara University Institute Of Engineering And Technology Chitkara University Punjab India Graphic Era Deemed To Be University Computer Science And Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350384628

this study explores the novel use of federated learning in conjunction with CNN for illness classification in Aloe vera leaves. Five separate client-contributed classes of Aloe Vera leaf diseases form the basis of the dataset used in the research. the technique is centered on using federated learning to create a decentralized data analysis system that protects privacy. Each client's local datasets are used to create a model that is optimized worldwide. the examination of the results included a thorough evaluation of the model's performance across all five customers (nh-1 to nh-5) using a variety of statistical metrics. To provide a complete picture of the model's performance, compute the macro, micro, and weighted averages. Results showed that nh-1, nh-2, nh-3, nh-4, and nh-5 all had macro standards of 88.61%, 84.07%, 80.08%, 90.02%, and 94.16%, respectively, indicating that the model performed evenly across all classes. Using weighted averages, which take into account the class imbalance, further analysis revealed that nh-5 was in the lead at 94.25%, followed by nh-4 at 90.04%, nh-1 at 88.97%, nh-2 at 84.45%, and nh-3 at 80.13%. Micro averages, which take into account all classes' contributions, con firmed similar findings: NH 5 achieved 94.25%, NH 4 gained 90.04%, NH 1 reached 88.94%, NH 2 achieved 84.49%, and NH 3 achieved 80.15%. In particular, for agricultural disease identification, the study's major contribution is the way it shows how federated learning may be used to merge local data into a strong global model. © 2023 IEEE.

关键词： Data privacy

来源：评论

学校读者我要写书评

暂无评论

Developing an Effective Model for Skin Disease Detection: Techniques and Approaches 4

Developing an Effective Model for Skin Disease Detection: Te...

引用

4th international conference on Advancement in Electronics and Communication Engineering, AECE 2024

作者： Yadav, Nikhil Kumar Tiwari, Amit Gaurav Verma, Harsh Kumar Saxena, Arpna Ajay Kumar Garg Engineering College Varanasi India Ajay Kumar Garg Engineering College Muzaffarpur India Ajay Kumar Garg Engineering College Meerut India Ajay Kumar Garg Engineering College Ghaziabad India Ajay Kumar Garg Engineering College Master of Computer Application Ghaziabad India

ISBN: (纸本)9798350364729

this research highlights the critical role of the skin as the body's primary defense against damage and infection. Despite its importance, the skin can be vulnerable to serious infections caused by fungi, viruses, or even dust, leading to conditions ranging from acne to eczema. Some skin diseases are highly contagious and can be spread by simple contact, underscoring the need for proper diagnosis and treatment to alleviate suffering and prevent transmission. the study focuses on developing a prototype for identifying skin diseases using convolutional neural networks (CNNs), a choice based on their effectiveness in image processing tasks. this research uses CNNs to classify specific skin conditions, including hand dermatitis, hand eczema, subacute eczema, lichen simplex, stasis dermatitis, and ulcers are all different skin conditions.. the methodology integrates image processing techniques with machine learning and uses the processed images to train a CNN model. the training data consists of five classes of skin conditions from the Dermnet dataset, which includes 19600 images. the prototype achieved an accuracy of 92%, highlighting the system's potential. Research suggests that with further improvements and a larger data set, the system could significantly improve early detection and treatment of skin ailments representing a substantial advance in dermatology care. © 2024 IEEE.

关键词： Dermatitis

来源：评论

学校读者我要写书评

暂无评论

A Hybrid machine learning Model for House Price Prediction 4th

A Hybrid Machine Learning Model for House Price Prediction

引用

4th international conference on Innovative Product Design and Intelligent Manufacturing System, IPDIMS 2022

作者： Subbulakshmi, B. Nirmala Devi, M. Sriram Srimadhi Arvindhan, M. Thiagarajar College of Engineering Thiruparankundram Madurai625015 India Galgotias University UP Greater Noida226001 India

ISBN: (纸本)9789819916641

A house price prediction model will be an effective application to predict and evaluate the cost of a certain property using the attributes. the main focus here is determining the prices of houses with higher accuracy by taking the important factors that may affect the price. It now plays an important role as the first step in many websites that are available online that are used to predict the price of the houses. Most of the websites lack accuracy as they show different prices for similar kinds of houses. By using some of the machine learning and deep learning algorithms, a prediction model can be developed that gives the price of the property with higher accuracy. the models that are used in this work are selected by utilizing many machine learning and deep learning models. the final model is the one that gives the highest accuracy among all the models that are taken into account. the result gives us minimum error and maximum accuracy. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Improving Primate Sounds Classification Using Binary Presorting for Deep learning 1

引用

4th international conference on Deep learning theory and applications (DeLTA)

作者： Koelle, Michael Illium, Steffen Zorn, Maximilian Nusslein, Jonas Suchostawski, Patrick Linnhoff-Popien, Claudia Ludwig Maximilians Univ Munchen Inst Informat Oettingenstr 67 Munich Germany

ISBN: (数字)9783031390593

ISBN: (纸本)9783031390586;9783031390593

In the field of wildlife observation and conservation, approaches involving machine learning on audio recordings are becoming increasingly popular. Unfortunately, available datasets from this field of research are often not optimal learning material;Samples can be weakly labeled, of different lengths or come with a poor signal-to-noise ratio. In this work, we introduce a generalized approach that first relabels subsegments of MEL spectrogram representations, to achieve higher performances on the actual multi-class classification tasks. For both the binary pre-sorting and the classification, we make use of convolutional neural networks (CNN) and various data-augmentation techniques. We showcase the results of this approach on the challenging ComparE 2021 dataset, with the task of classifying between different primate species sounds, and report significantly higher Accuracy and UAR scores in contrast to comparatively equipped model baselines.

关键词： Audio classification Binary presorting Relabelling Background noise CNN

来源：评论

学校读者我要写书评

暂无评论

Android Malware Detection Using Deep learning Techniques 4

Android Malware Detection Using Deep Learning Techniques

引用

4th international conference on Multimedia Processing, Communication and Information Technology, MPCIT 2024

作者： Janardhana, D.R. Nithin, H.V. Sandhya, B.R. Bhatia, Aakash D. Nitte Meenakshi Institute of Technology Department of CSE Bengaluru India PES Institute of Technology & Management Department of Data Science Shivamogga India

ISBN: (纸本)9798350375466

With the rapid increase in Android devices and applications, securing these platforms has become critical. Android malware presents serious risks to user privacy, data integrity, and device functionality. Traditional malware detection methods are often insufficient due to the evolving sophistication of modern malware. this study investigates the use of deep learning, specifically Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for enhancing Android malware detection accuracy and robustness. In this work, there is a comprehensive framework that utilizes both static and dynamic analysis to extract extensive features from Android applications. Static analysis examines the application's code, permissions, and metadata without executing the app, while dynamic analysis observes the app's behavior during runtime. these features are fed into CNN and RNN models, which are adept at handling spatial and sequential data, respectively, capturing complex patterns and temporal dependencies in malware behavior. Extensive experiments on a benchmark dataset of benign and malicious Android applications show that machine learning models, particularly CNNs and RNNs, significantly outperform traditional signature-based detection techniques. In this work, the best-performing model achieved a detection accuracy of over 95% with a low false-positive rate, demonstrating the potential of CNNs and RNNs to provide robust and scalable solutions for Android malware detection. this research highlights the importance of continuous feature engineering and model updating to adapt to evolving malware tactics and suggests that hybrid approaches combining static and dynamic analysis can offer more comprehensive defense mechanisms against sophisticated threats. Future work will focus on real-time detection capabilities and integrating these models into practical security solutions for end-users. © 2024 IEEE.

关键词： Android malware

来源：评论

学校读者我要写书评

暂无评论

Optimizing Energy Management and Load Balancing through AI-Driven Quantum Approximate Optimization 4

Optimizing Energy Management and Load Balancing Through AI-D...

引用

4th IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Manjunath Kamath, K. Manasa, M. Anitha, B.S. Mahadevi Tlajiya, Falguni Chavan, Sangramjit Department of Cyber Security Karkala India Brindavan College of Engineering Department of Artificial Intelligence and Machine Learning Bengaluru India Sarada Vilas College Department of Computer Science Mysuru India Parul institute of Engineering and Technology Parul University Department of Electrical Engineering Gujarat India Pune India

ISBN: (纸本)9798350352931

the integration of Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing (QA) offers a promising approach to addressing energy management and load balancing challenges in modern power systems. this study explores the application of these quantum computing techniques, coupled with Artificial Intelligence (AI), to optimize energy distribution across smart grids. the proposed hybrid model leverages the problem-solving capabilities of QAOA for discrete optimization and the real-time adaptability of QA for minimizing energy consumption and operational costs. AI techniques are employed to predict energy demand, balance loads, and ensure efficient resource allocation. Simulations were conducted on a smart grid scenario involving renewable energy sources, varying demand, and distributed energy generation. the results demonstrate that the hybrid model achieved a 25% improvement in load balancing efficiency and a 30% reduction in energy wastage compared to traditional optimization methods. Additionally, the model reduced peak energy demand by 20%, contributing to overall grid stability. the quantum-enhanced approach also decreased computational complexity by 40%, enabling faster decision-making in dynamic environments. these findings highlight the potential of combining quantum algorithms with AI for sustainable and efficient energy management. © 2024 IEEE.

关键词： Quantum computers

来源：评论

学校读者我要写书评

暂无评论

PartSeg v2: Bioimage Segmentation Using Advanced Deep learning Techniques 4th

PartSeg v2: Bioimage Segmentation Using Advanced Deep Learni...

引用

4th international conference on Frontiers in Computing and Systems, COMSYS 2023

作者： Bokota, Grzegorz Basu, Subhadip Sroka, Jacek Insititute of Informatics University of Warsaw Warsaw Poland Department of Computer Science and Engineering Jadavpur University Kolkata India

ISBN: (纸本)9789819726134

In this paper, we present a new version of our bioimaging tool PartSeg. It allows integration of deep learning models from the Bioimage Model Zoo, which is a community-driven AI model repository. We also show how PartSeg’s power users can train such models, for example, to increase automatization of their data processing workflows. then, we present further new features of PartSeg that make it easier to publish datasets in a durable and referencable way with version tracking. We also describe good practices related to data publishing and how adding metadata can allow for easier data discovery. Availability of such published datasets enables development of even better machine learning models. Publishing of the data is also a requirement for verifiable and repeatable science, leads to greater visibility of the results and enables cooperation and cross-domain exchange of ideas. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Bioimaging

来源：评论

学校读者我要写书评

暂无评论

A knowledge graph representation learning based approach to qualitative case discipline 4

A knowledge graph representation learning based approach to ...

引用

4th international conference on computer Science and Communication Technology, ICCSCT 2023

作者： Zhang, Tiange Liu, Yuefeng Zhang, Hanyu School of Information Engineering Inner Mongolia University of Science & Technology Inner Mongolia Baotou014017 China

ISBN: (纸本)9781510671232

To solve the problem of irregular and inefficient case characterization and discipline in the field of discipline inspection and supervision, a method of case characterization and discipline measurement based on knowledge map representation learning is proposed. the method uses the knowledge map of discipline inspection cases as auxiliary information, and the knowledge representation learning model is used to characterize the entities and relationships in the knowledge graph, and the results of the characterized representation are subsequently processed by similar case calculation, and then uses the results of the representation to calculate similar cases to further realize the qualitative discipline of cases. the negative sampling method of the knowledge representation learning model is investigated to improve the knowledge graph vectorization accuracy and facilitate the manipulation of the knowledge graph in the case of qualitative quantitative discipline task. the knowledge graph inference-based approach to case characterization and discipline improves accuracy and computational efficiency. By improving the existing model, the improved model can reduce the impact of noisy data to a certain extent. © 2023 SPIE.

关键词： Inspection

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419页 << < 147 148 149 150 151 152 153 154 155 156 > >>

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：