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

760 篇 会议
12 册 图书
2 篇 期刊文献

馆藏范围

774 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

382 篇 工学
- 319 篇 计算机科学与技术...
- 235 篇 软件工程
- 97 篇 信息与通信工程
- 87 篇 电气工程
- 64 篇 生物医学工程（可授...
- 41 篇 生物工程
- 39 篇 控制科学与工程
- 20 篇 光学工程
- 14 篇 机械工程
- 14 篇 电子科学与技术（可...
- 13 篇 安全科学与工程
- 12 篇 仪器科学与技术
- 9 篇 化学工程与技术
- 8 篇 交通运输工程
149 篇 理学
- 96 篇 数学
- 49 篇 生物学
- 45 篇 统计学（可授理学、...
- 36 篇 物理学
- 34 篇 系统科学
- 12 篇 化学
81 篇 管理学
- 46 篇 图书情报与档案管...
- 42 篇 管理科学与工程(可...
- 19 篇 工商管理
42 篇 医学
- 38 篇 临床医学
- 34 篇 基础医学(可授医学...
- 21 篇 药学(可授医学、理...
- 9 篇 公共卫生与预防医...
16 篇 法学
- 15 篇 社会学
10 篇 教育学
- 10 篇 教育学
8 篇 经济学
- 8 篇 应用经济学
7 篇 农学
2 篇 军事学

主题

173 篇 machine learning
123 篇 accuracy
83 篇 deep learning
74 篇 signal processin...
74 篇 training
64 篇 machine learning...
63 篇 feature extracti...
58 篇 signal processin...
51 篇 natural language...
46 篇 support vector m...
40 篇 adversarial mach...
38 篇 computational mo...
38 篇 real-time system...
35 篇 predictive model...
30 篇 convolutional ne...
27 篇 image processing
27 篇 data models
23 篇 neural networks
23 篇 visualization
22 篇 optimization

机构

5 篇 bircham internat...
4 篇 department of co...
4 篇 national key lab...
3 篇 department of cs...
3 篇 tarbiat modares ...
3 篇 department of co...
3 篇 university of sc...
3 篇 amity university...
3 篇 department of co...
3 篇 school of mathem...
3 篇 university of so...
3 篇 czestochowa univ...
3 篇 jaypee institute...
3 篇 hospitalier univ...
3 篇 university of te...
2 篇 amity university...
2 篇 všb-tu ostrava 1...
2 篇 swinburne univer...
2 篇 advanced technol...
2 篇 wroclaw universi...

作者

6 篇 boudjella aissa
5 篇 bellebna bachir
4 篇 alavikunhu panth...
4 篇 hongwei liu
4 篇 ajay rana
4 篇 boudjella manal ...
3 篇 shengyang li
3 篇 afef elloumi oue...
3 篇 jack dongarra
3 篇 wathiq mansoor
3 篇 ewa deelman
3 篇 konrad karczewsk...
3 篇 reza ahmed wasif
3 篇 zhang jing
3 篇 yunfei liu
3 篇 roman wyrzykowsk...
2 篇 wang hai-xian
2 篇 junyan zhang
2 篇 shuo ma
2 篇 marius mircea ba...

语言

743 篇 英文
31 篇 其他
1 篇 中文

检索条件"任意字段=7th International Conference on Signal Processing and Machine Learning, SPML 2024"

共 774 条记录，以下是1-10 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：

spml 2024 - 2024 7th international conference on signal processing and machine learning

SPML 2024 - 2024 7th International Conference on Signal Proc...

引用

7th international conference on signal processing and machine learning, spml 2024

ISBN: (纸本)9798400717192

the proceedings contain 49 papers. the topics discussed include: deep K-means clustering based on generative adversarial framework;high similarity attention network with normalized shared convolutions;deep reinforcement learning for carbon emissions detection based on pseudo-count exploration;Fresnel zone theory based non-line-of-sight respiration behavior detection using USRP;TelChatbot: improving telecommunications user satisfaction through enhanced large language models;study on sperm morphology analysis using deep learning;enhancing non-coal object recognition using deep learning on conveyor belts;deep learning based jujube quality assessment: an automated surface defect detection approach;and deep learning-based method for recognizing violation behaviors of underground personnel.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimizing Medical Imaging: High-Performance Hardware for Image processing, machine learning 24

Optimizing Medical Imaging: High-Performance Hardware for Im...

引用

7th international conference on Digital Medicine and Image processing, DMIP 2024

作者： Kalyan Chakravarthy, N.S. Balapanur, Mouli Chandra Pandian, Arun Nambi Pulikanti, Jyothi Prasad, D. Syed Masood, Jafar Ali Ibrahim High-Performance Computing Research Laboratory QIS College of Engineering and Technology Andhra Pradesh Ongole India Department of Internet of Things School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9798400709586

the demand for high-performance hardware solutions for machine learning tasks is growing as medical imaging evolves. In this paper, we will focus on the latest hardware advanced technologies: GPUs, TPUs and FPGAs that can be used for image processing optimization in medical imaging such as brain tumor segmentation or chest X-ray classification. We test these devices on the BraTS and ChestX-ray14 datasets to show how running models quicker increases diagnostic performance. the study offers a comprehensive performance and energy efficiency evaluation of all the considered hardware solutions when training deep learning models for medical imaging, providing clinical guidelines to choose appropriate new-generation accelerators before engaging in expensive leasing contracts. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： GPUS

来源：评论

学校读者我要写书评

暂无评论

7th international conference on Attacks and Defenses for Internet-of-things, ADIoT 2024

7th International Conference on Attacks and Defenses for Int...

引用

7th international conference on Attacks and Defenses for Internet-of-things, ADIoT 2024

ISBN: (纸本)9783031855924

the proceedings contain 10 papers. the special focus in this conference is on Attacks and Defenses for Internet-of-things. the topics include: A Conflict-Aware Active Automata learning Approach for BLE Device Status machine Construction;optimizing Indoor Network Element Layout for Enhanced signal Coverage and Security in Location-Based Services;an Efficient Lattice-Based Authentication Protocol for the Vehicular Ad Hoc Network;a Privacy-Preserving Computer-Aided Diagnosis Framework for Medical Applications Using Federated learning and Homomorphic Encryption;GCFuzz: An Intelligent Method for Generating IoT Protocols Test Cases Using GAN with CVAE;VRMDA: Verifiable and Robust Multi-subset Data Aggregation Scheme in IoT;Assessing the Effectiveness of LLMs in Android Application Vulnerability Analysis;singularization: A New Approach to Designing Block Ciphers for Resource-Constrained Devices.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Assessing the Effect of Data Complexity and Instance Overlap Issues on Imbalanced learning 24

Assessing the Effect of Data Complexity and Instance Overlap...

引用

7th international conference on Big Data and Education, ICBDE 2024

作者： Ali, Muhammad Asim Liu, Jun Moore, Samuel Nibouche, Omar Ulster University Antrium Belfast United Kingdom

ISBN: (纸本)9798400716980

Most machine learning (ML) algorithms work best when the samples in each class are almost equal. However, if a dataset has imbalanced samples then the ML model can achieve a high accuracy by just predicting the majority of classes and achieving a high classifier performance. Different resampling methods are used to handle this imbalance issue by creating synthetic data in the minority class or removing samples from the majority class until the classes are balanced. However, using these resampling methods can harm the dataset performance by creating synthetic data samples in a dataset that already suffers from overlap and other data intrinsic issues. Recently, dataset complexity measures, by observing the characteristics of a dataset, are often used in machine learning tasks as intrinsic descriptors to calculate the difficulty of a classification problem. this study investigates how resampling methods can affect the dataset in terms of complexity, overlapping, and classification accuracy. this is achieved by monitoring 22 different measurements related to data complexity measures obtained from 20 public and pre-processed datasets from the KEEL repository. Our empirical findings demonstrate a strong positive correlation between the resampling methods and the dataset’s complexity and classification accuracy. We also posit that the main reason for poor classification accuracy on an imbalanced dataset is not due to its imbalanced nature but due to the other intrinsic characteristics of the dataset. Finally, we advocate that pre-processing methods and ML algorithms should be based on the dataset’s specific properties, rather than being chosen on an ad hoc basis. © 2024 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Quantitative Analysis of Side Effect Severity using the D-SESS Scale: An Observational Study with Analytical Techniques 24

Quantitative Analysis of Side Effect Severity using the D-SE...

引用

2024 7th international conference on Healthcare Service Management, ICHSM 2024

作者： Gaddam, Vijay Kumar Veldandi, Amulya Godana, Akhila Siri Sripathi, Surya Rao Gudisa, Timothy Department of BioMedical Engineering and Informatics Indiana University IndianapolisIN United States

ISBN: (纸本)9798400710162

the study presented in this paper introduces the Drug Side Effect Severity Scale (D-SESS), a novel quantitative metric designed to assess the severity of drug side effects. By applying natural language processing (NLP) techniques like tokenization for preprocessing and developing clustering and predictive models using machine learning algorithms, this research aims to provide a more nuanced understanding of drug side effects. this categorizes side effects into mild, moderate, and severe based on their impact on patient health. this paper details the methodology behind creating the D-SESS, its initial validation, and the application of clustering models such as K-Means, and Agglomerative Clustering to organize drugs based on their side effect profiles. Predictive modeling further enhances the utility of D-SESS by enabling the assignment of drugs to clusters, facilitating a comprehensive analysis of drug safety. the Drug Side Effect Severity Scale (D-SESS) aims to address this gap by introducing a quantitative metric designed to offer a more nuanced understanding of drug side effects. © 2024 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Research on DOA Estimation Method of Underwater Acoustic signal Based on machine learning 7th

Research on DOA Estimation Method of Underwater Acoustic Sig...

引用

7th international conference on Wireless Communications, Networking and Applications, WCNA 2023

作者： Zhao, Feiyu Beijing Institute of Technology Beijing China

ISBN: (纸本)9789819624089

this project is concerned with the development of a machine learning-based DOA estimation of underwater acoustic signals with the view of improving the efficiency and reliability of the signal processing in complex underwater environments. the feature analysis and classification of the underwater acoustic signals are done with the help of convolutional neural networks (CNNs). through multi-step purification of the signal data and lowering the sampling frequency of the pre-processed signal data, a high-performance arrival angle assessment framework is constructed. the results indicate that the algorithm achieves high accuracy, recall and F1 in different noise intensity levels;particularly, low noise environment with an accuracy of 95%. 2%. the application verification of practical application also confirms that this technology has strong applicability and stability in complex seabed conditions. © the Author(s) 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

7th international Russian Automation conference, RusAutoCon 2024

7th International Russian Automation Conference, RusAutoCon ...

引用

7th international Russian Automation conference, RusAutoCon 2024

ISBN: (纸本)9783031824937

the proceedings contain 37 papers. the special focus in this conference is on Russian Automation. the topics include: Mapping and Path Planning Methods for Highly Automated Vehicles in Agriculture;morphological Analysis and Synthesis Features of Technological Processes;a Modern Method of Wireless Control of Unguarded Railway Crossings;duties and Obligations of the Railway Staff Concerned When the Microprocessorized Contactless Controlling Gauge Device signal Is Triggered;integration of Automated Management Systems for Enterprises’ Transport and Technical Services;development of an Automation Module for Planning Trajectories for Painting Aircraft Fuselage Elements;identification of Metal Sheets in the Flow, Based on the Marking Imprint, Using Neural Networks;study of the Performance of Adaptive Sensor Networks for Collecting and processing thermoelectric Data;development and Research of a Cartographic Model for Municipal Planning as the Basis of an Intelligent Geoinformation System;BIM Visual Programming of Bionic Architecture Construction Using Dynamo and Revit;development of a Model and Algorithms for Trigger Control of Technological Processes of Resource Provision;system for Statistical Assessment of Means of Controlling Engineers’ Qualification for Information Support to Manage the Recruiting Process in Industry;smart Enumeration Technology;comparative Analysis of C-Band Conical Horn Antenna Sparse Structures Characteristics at Different Frequencies;software Implementation of Heuristic Methods of Optimization and Integration into a Cloud Service;computer System for Modeling Fluid Flow Around Bodies and Its Potential in Industry;the Effect of Regular and Irregular Segmentations on Characteristics and Charge Distribution Densities of Microstrip Lines;reinforcement learning with External Teacher for Building Energy Management.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Programmable and Scalable Bit-Sliced VLSI Architecture for Decision Tree-Based machine learning Edge Inference 7th

Programmable and Scalable Bit-Sliced VLSI Architecture for D...

引用

7th IFIP WG 5.5 international Cross-Domain conference on Internet of things

作者： Somesula, Raaga Sai Sivakumar, Sibi Rajagopal Katkoori, Srinivas Univ S Florida Tampa FL 33620 USA

ISBN: (纸本)9783031819025;9783031819001;9783031818998

As the volume and diversity of Internet of things (IoT) data continues to grow, traditional cloud-based processing methods face significant challenges, including latency, bandwidth constraints, and privacy concerns. Our research focuses on employing decision trees (DTs) [1] as an intelligent filtering mechanism on the edge. We propose a novel programmable and scalable custom ASIC architecture designed for decision tree based machine learning (ML) inference. Each bit-slice incorporates two 8-bit SISO input registers connected to an 8-bit comparator for data processing, the output of the comparator drives the select line of Mux, which selects the respective true and false paths. Each bit-slice can be programmed into either a leaf node or a regular node. A leaf node stores classification labels. A regular node compares a feature value with a weight value to decide between true and false paths. Given a DT model, the decision tree can be pre-programmed to store the model weights in respective tree nodes. In the inference phase, feature values are sequentially fed into the DT nodes. After the feature values are loaded the DT tree performs an inference with the classification value generated in the root node. We have implemented and validated the architecture at the layout level using Cadence Virtuoso in 0.5 mu m CMOS technology node. A 5-level DT occupies roughly 90mm(2) area with 22.58 mW of power consumption at a maximum clock speed of 12.8 MHz.

关键词： Decision Tree Edge-AI IoT ASIC VLSI

来源：评论

学校读者我要写书评

暂无评论

Enhancing IoT Security in 6G Networks: AI-Based Intrusion Detection, Penetration Testing, and Blockchain-Based Trust Management (Work-in-Progress Paper) 1st

Enhancing IoT Security in 6G Networks: AI-Based Intrusion D...

引用

1st international Workshop on the Design, Verification, and Validation of IoT Systems, GRAAL4IoT 2024 and 1st international Workshop on IoT Standards, STAND4IoT 2024, held in conjunction with 7th IFIP WG 5.5 international Cross-Domain conference on Internet of things, IFIPIoT 2024

作者： La, Vinh Hoa Mallouli, Wissam Nguyen, Manh Dung de Oca, Edgardo Montes Cavalli, Ana Vörös, Péter Kecskeméti, Károly Alshawki, Mohammed Laki, Sándor Lalas, Antonios Kalafatidis, Sarantis Mpatziakas, Asterios Makris, Nikolaos Drosou, Anastasios Montimage 39 rue Bobillot Paris75013 France Faculty of Informatics ELTE Eötvös Loránd University Budapest1117 Hungary Centre for research and technology Hellas 6th km Charilaou-Thermi Road Thermi Thessaloniki57001 Greece

ISBN: (纸本)9783031820649

the exponential growth of Internet of things (IoT) devices in upcoming 6G networks poses significant security challenges, particularly concerning Distributed Denial of Service (DDoS) attacks, data breaches, and unauthorized access. this paper presents the NATWORK project’s approach to addressing these challenges through three distinct use cases (UC): UC#3.1 focuses on developing AI-driven machine learning techniques for anomaly detection and DDoS mitigation;UC#3.2 introduces advanced AI-powered penetration testing and vulnerability assessment tools;and UC#3.3 explores blockchain-based security mechanisms to enhance trust and secure communications in IoT ecosystems. Collectively, these use cases aim to fortify IoT networks against evolving cyber threats, ensuring data integrity and network resilience. © IFIP international Federation for Information processing 2025.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

Adaptive VR Systems Based on EEG and machine learning Algorithms

Adaptive VR Systems Based on EEG and Machine Learning Algori...

引用

international Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Alexander Yu. Tychkov Robert N. Khizbullin Radik N. Khizbullin Alexander D. Ivanov Alan K. Alimuradov Denis S. Chernyshov Department of Radioengineering and Radioelectronic Systems Penza State University Penza Russia Department of Instrument Engineering and Mechatronics Kazan State Power Engineering University Kazan Russia Department of Electric Power Stations Kazan State Power Engineering University Kazan Russia

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

this paper presents a concept for a system that can adapt virtual reality (VR) scenes in real time based on the user's electroencephalographic (EEG) signals using machine learning algorithms. the proposed approach aims to increase the level of personalization and depth of immersion in the virtual environment by dynamically adjusting scene parameters according to the individual's emotional and cognitive state. the paper considers methods for EEG signal preprocessing, feature extraction, the use of modern neural network architectures for state classification, as well as mechanisms for mapping classification results onto visual and auditory VR elements. Potential applications are discussed, such as adaptive training simulators, therapeutic VR programs, games, and multimedia environments. Issues of scalability, the need for model personalization, minimizing processing delays, and possible solutions are also addressed. this work provides a theoretical foundation for future experimental research and the practical implementation of next-generation adaptive VR systems.

关键词： Training Visualization Solid modeling machine learning algorithms Adaptive systems Sensitivity Virtual environments machine learning Feature extraction Electroencephalography

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78页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：