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

4,140 篇 会议
38 册 图书
6 篇 期刊文献

馆藏范围

4,184 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
- 2,466 篇 计算机科学与技术...
- 2,041 篇 软件工程
- 615 篇 生物工程
- 587 篇 信息与通信工程
- 364 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...
1,367 篇 理学
- 673 篇 数学
- 645 篇 生物学
- 331 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
342 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

528 篇 machine learning
245 篇 deep learning
117 篇 support vector m...
99 篇 adversarial mach...
93 篇 accuracy
93 篇 machine learning...
83 篇 forecasting
76 篇 convolutional ne...
70 篇 predictive model...
70 篇 feature extracti...
59 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
16 篇 mehta shiva
10 篇 william p.
8 篇 sharma vikrant
7 篇 mahamudul hasan
7 篇 shiva mehta
7 篇 hasan mahamudul
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.

语言

2,638 篇 英文
1,545 篇 其他
112 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 4184 条记录，以下是1521-1530 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：

Research on Detection Method of Large-Scale Network Internal Attack Based on machine learning 1

引用

4th international conference on machine learning for Cyber Security, ML4CS 2022

作者： Liu, Chang Long, Chaozhong Yu, Yuchuan Lin, Ziqi Jiangsu Fengren Information Technology Co. Ltd. Nanjing241000 China Kunshan Open University Kunshan215316 China Information Center of Public Security Bureau of Rongshui Miao Autonomous County Liuzhou545399 China Shandong Information Vocational and Technical College Weifang261044 China

ISBN: (数字)9783031200991

ISBN: (纸本)9783031200984

Aiming at the problem of inaccurate analysis of forged address attack behavior in current detection methods, this paper proposes a large-scale network attack detection method based on machine learning. A large-scale network internal attack detection model is constructed to analyze the degree of network internal attack. the model is trained by machine learning method to improve the convergence speed of model detection. After determining the attack target, analyzing the network vulnerability attribute, tracing the network internal attack source. Computes the hash of a function to ensure that the data set is complete and not tampered with. Alarm windows automatically check the point, set different alarm levels. the Euclidean distance is used as the distance measure of clustering process to distinguish the attack behavior. the detection formula of large-scale network internal attack is constructed, and the calculation result is divided into the level of large-scale network internal attack. Experimental results show that the method is consistent with the actual path, and the highest recall is 93%, the highest precision is 0.98, with good detection results. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

A Model-Based machine learning Approach for Assessing the Performance of Blockchain applications 7

A Model-Based Machine Learning Approach for Assessing the Pe...

引用

7th IEEE international conference on Smart Internet of things, SmartIoT 2023

作者： Albshri, Adel Alzubaidi, Ali Solaiman, Ellis Newcastle University School of Computing United Kingdom University of Jeddah College of Computer Science and Engineering Saudi Arabia Umm Al-Qura University College of Computing Saudi Arabia

ISBN: (纸本)9798350316575

the recent advancement of Blockchain technology consolidates its status as a viable alternative for various domains. However, evaluating the performance of blockchain applications can be challenging due to the underlying infrastructure's complexity and distributed nature. therefore, a reliable modelling approach is needed to boost Blockchain-based applications' development and evaluation. While simulation-based solutions have been researched, machine learning (ML) model-based techniques are rarely discussed in conjunction with evaluating blockchain application performance. Our novel research makes use of two ML model-based methods. Firstly, we train a k nearest neighbour (k\text{NN}) and support vector machine (SVM) to predict blockchain performance using predetermined configuration parameters. Secondly, we employ the salp swarm optimization (SO) ML model which enables the investigation of optimal blockchain configurations for achieving the required performance level. We use rough set theory to enhance SO, hereafter called ISO, which we demonstrate to prove achieving an accurate recommendation of optimal parameter configurations;despite uncertainty. Finally, statistical comparisons indicate that our models have a competitive edge. the k\text{NN} model outperforms SVM by 5% and the ISO also demonstrates a reduction of 4% inaccuracy deviation compared to regular SO. © 2023 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

CT Image Classification of Pulmonary Nodules Based on Deep Transfer learning and Inception-Res-V2 4

CT Image Classification of Pulmonary Nodules Based on Deep T...

引用

4th international conference on Advances in Electrical Engineering and computer applications, AEECA 2023

作者： Wang, Ran Harbin University of Commerce School of Computer and Information Engineering Harbin China

ISBN: (纸本)9798350308082

the CT image classification method of pulmonary nodules based on deep convolutional neural network has a great advantage in performance compared with the traditional method. However, deep convolutional neural networks require a large number of labeled images for training. In practical applications, the number of labeled lung nodules CT images is often difficult to meet the requirements of network training. In this paper, an inception-res-v2 deep convolutional neural network model based on transfer learning is proposed to classify CT images of pulmonary nodules. First, the deep convolutional neural network model is pre-trained on the large scale dataset ImageNet, then the transfer learning method is used to fine tune the network with few pulmonary nodule CT images to solve the problem of insufficient training data. In this paper, the classify accuracy of CT images of pulmonary nodules of two deep neural networks: googlenet and inception-res-v2 were compared under the condition of transfer learning. In addition, the effects of different optimization algorithms on the classification results of transfer learning are also studied. Experiments show that the main factor affecting the final classification accuracy of CT images of pulmonary nodules is the network structure. Regardless of the optimization algorithm used, the inceptionres-v2 network has higher classification accuracy. the inception-res-v2 deep convolutional neural network model based on transfer learning proposed in this paper can be applied to other image classification and target detection tasks, and has important application value. © 2023 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Effectiveness of Deep learning Technologies to Assist Educational Inclusion for Children with Down Syndrome 5

Effectiveness of Deep Learning Technologies to Assist Educat...

引用

5th international conference on Advancements in Computing, ICAC 2023

作者： Silva, Shehan Jayasinghe, Anjula Dilshan, Rishitha Dissanayake, Chandur Vidhanaarachchi, Samitha De Silva, Dilshan Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

Down Syndrome (DS) is a genetic disorder causing intellectual disability and developmental delays. Despite instances of discrimination, several individuals with DS have achieved success through proper education and community support. this research addresses the challenges faced by children with DS in terms of motor skill development, cognitive impairments, and speech difficulties with the use of Deep learning Technologies such as LSTM, CNN machine learning models. To bridge the educational gap and improve speech intelligibility, this study focuses on oral motor exercises that enhance articulation skills. Cognitive development in individuals with DS is also a concern, prompting the proposal of a self-learning system to foster cognitive growth. Fine motor skills improvement is explored through yoga exercises, and interventions like interactive technologies are considered to enhance learning experiences. this paper discusses the development of a user-friendly mobile application for early intervention in DS, integrating interactive activities using advanced technologies and a parent therapy dashboard. the system's potential for improving developmental skills and future expansion is emphasized. © 2023 IEEE.

关键词： Speech intelligibility

来源：评论

学校读者我要写书评

暂无评论

machine learning (ML) assisted Edge security framework on FPGAs 9

Machine Learning (ML) assisted Edge security framework on FP...

引用

9th international conference on computer and Communication Engineering, ICCCE 2023

作者： Sheikh, Abdul Manan Islam, Md. Rafiqul Habaebi, Mohamed Hadi Zabidi, Suriza Ahmad Najeeb, Athaur Rahman Bin Basahel, Ahmed International Islamic University Malaysia Department of Electrical and Computer Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9798350325218

Edge computing (EC) is an act of bringing computational and storage capability near data sources. It helps to reduce response times and bandwidth requirements. However, the rapid proliferation of edge devices has expanded the attack surface and opportunity for adversaries to penetrate corporate networks. the limited computational abilities of edge devices and the heterogeneous nature of communication protocols further increase the security challenges of EC. Also, the trustworthiness of hardware devices is challenged due to security and privacy threats like trojan insertion, IP cloning, and hardware counterfeits. the application of machine Language (ML) models in the edge computing paradigm creates a distributed intelligence architecture. Also, Field Programmable Gate Arrays (FPGAs) can exploit Physical Unclonable Functions (PUFs) characteristics to generate and store authentication keys. the PUF structure deployed with ML models in the edge layer can learn its complex input-output mapping from the Challenge and Response pairs (CRPs) to identify the suspicious and unknown responses. this article discusses the security and privacy issues in various layers of the EC architecture and proposes intrusion detection systems through the integration of FPGA-based edge sever and ML models. A PUF-assisted ML framework of the intrusion detection system is proposed to authenticate and detect potential attacks on the network. © 2023 IEEE.

关键词： Hardware security

来源：评论

学校读者我要写书评

暂无评论

Dual Autoencoder-based Framework for Image Compression and Decompression 15

Dual Autoencoder-based Framework for Image Compression and D...

引用

15th international conference on machine Vision (ICMV)

作者： Patel, Bhargav Ahmedabad Univ Ahmadabad Gujarat India

ISBN: (纸本)9781510666184;9781510666191

Recent development in deep learning has shown great possibilities in many computer vision tasks. Image compression is a crown field of computer vision, and deep learning is gradually being used for image compression & decompression tasks. the compression rate of the lossy compression algorithm is higher than lossless compression but the main disadvantage of lossy compression is the loss of data while compressing it. It is observed that a higher compression rate causes higher data loss. Recent advancements in deep learning technique for computer vision like image noise reduction and image super-resolution has shown great possibilities in the area of image enhancement. If these techniques can be utilized to mitigate the impact of a higher compression rate on the output of lossy compression, then the nearly same image quality can be achieved. In this paper, an image compression & decompression framework are proposed. this framework is based on two convolutional neural networks (CNN) based autoencoders. Images and videos are the main sources of unstructured data. Storing and transmitting these unstructured data in the cloud server can be costly and resource-consuming. If a lossy compression can compress the image to store in the cloud server then it can reduce the storage cost and space. We have achieved a 4x compression ratio which means an image will occupy only 25% space compared to the original image. the original image will be retrieved using a joint operation of deconvolution and image enhancement algorithms. the proposed framework receives state-of-the-art performance in terms of Peak Signal-to-Noise ratio (PSNR) and Structure Similarity Index Measure (SSIM) with 4x compression.

关键词： Auto-Encoder Convolutional neural network (CNN) Image compression & decompression Deep learning

来源：评论

学校读者我要写书评

暂无评论

7th EAI international conference on machine learning and Intelligent Communication, MLICOM 2022

7th EAI International Conference on Machine Learning and Int...

引用

7th EAI international conference on machine learning and Intelligent Communication, MLICOM 2022

ISBN: (纸本)9783031302367

the proceedings contain 16 papers. the special focus in this conference is on machine learning and Intelligent Communication. the topics include: A RF Fingerprint Clustering Method Based on Automatic Feature Extractor;across Online Social Network User Identification Based on Usernames;a Weakly Supervised Text Classification Method Based on Vocabulary Construction;research on the Construction and application of Knowledge Graph in the Field of Open Data Policy;comparative Study on the Methods of Atmospheric Early Warning Based on machine learning;image Segmentation Based on Fuzzy Method;Design and Analysis on U-VLC-CC-CDMA Systems;an Improved Dynamic Spectrum Access Algorithm Based on Reinforcement learning;Inception Resnet V2-ECANet Based on Gramian Angular Field Image for Specific Emitter Identification;automated Metal Surface Defect Detection;design and Implementation of Intelligent Truck Based on Azure Kinect;a Comparison of Discrete Event Simulator and Real-Time Emulator for Mobile Ad Hoc Network;a Data-Driven Algorithm for Large-Scale Multi-camera Calibration;efficient Transmission Protocols for the Satellite-Terrestrial Integrated Networks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

machine learning Solutions to Polycystic Ovary Syndrome: A Review 6

Machine Learning Solutions to Polycystic Ovary Syndrome: A R...

引用

6th international conference on Contemporary Computing and Informatics, IC3I 2023

作者： Gupta, Kajal Prasad, Rajesh Ajay Kumar Garg Engineering College Computer Science Engineering Department Ghaziabad India

ISBN: (纸本)9798350304480

Polycystic Ovary Syndrome (PCOS) is one of the most popular endocrine disorders. It is a kind of disorder which generally occurs in women when they are in their reproductive age. Women who suffer from PCOS can experience totally absence of menses, unstable menstrual cycles and as well as the rise in androgens or sex hormones. the ovaries will have many follicles at a time and they fail to ovulate an egg every month and may also lead to infertility. the major causes which lead to the syndrome are unclear till date. On the other hand, if the syndrome is not diagnosed early, it can lead to more serious diseases which include diabetes-2 and diseases related to the heart. the major objective of this paper is to review on the application of all the emerging technologies such as machine learning (ML), Artificial Intelligence (AI) in the detection of the PCOS. It will enable researcher to help in knowing what changes can be made in the technologies or what new technologies can be adopted to detect the PCOS. this research paper discussed the advantages, disadvantages and future direction of emerging technologies application in PCOS detection and prediction. © 2023 IEEE.

关键词： AI androgen follicle ML PCOS

来源：评论

学校读者我要写书评

暂无评论

Object Recognition based on Deep learning Algorithms using Embedded IoT with Interactive Interface 7

Object Recognition based on Deep Learning Algorithms using E...

引用

7th international conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Borde, Swapna Patil, Chandan Sonawane, Chinmay Singh, Mankrit Vidyavardhini's College of Engineering and Technology Vasai India B.E. Computer Engineering Vidyavardhini's College of Engineering and Technology Vasai India

ISBN: (纸本)9798350397253

Object detection is one of the most popular applications of machine learning in the modern era. With the growth of IOT in recent times, dedicated devices offering real-time object detection have seen overwhelming demand and applications in many sectors e.g. security, healthcare, workplace etc. Different algorithms and approaches have been implemented and studied in terms of object detection. To refer to a few the YOLO family, RCNN family, SSD etc. this research study compares the performance of YOLO and Faster RCNN based on a custom dataset containing different objects and items. the IOU of each data point (image) is calculated and compared. YOLO performs better for a small margin. In this research study, a language learning interactive model is demonstrated based on object detection(YOLO), NLP, python, flask and IoT (Raspberry Pi.) the web application is running on is divided into two parts, learning and practice. the learning part has a raspberry pi device which has a camera module that captures real-time footage, recognizes the object and reads out its name in the language the user is learning. the practice has the same setup, with the application asking the user to show a particular object. Points are awarded for correct guesses, making the learning process more interactive and involving. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Design of a machine learning based Data Analytics Engine to Improve Decision Making Processes 5

Design of a Machine Learning based Data Analytics Engine to ...

引用

5th international conference on Smart Systems and Inventive Technology, ICSSIT 2023

作者： Pethe, Yoginee Surendra Dandekar, Pranali Rahul Shri Ramdeobaba College of Engineering and Management Department of Computer Application Nagpur India Shri Ramdeobaba College of Engineering and Management Department of Computer Science and Engineering Nagpur India

ISBN: (纸本)9781665474672

Analytical Hierarchy Processing (AHP) assists in estimation of input-specific weights for improving system-level decision making operations. the process initially decides a goal, and then uses different criterion & alternatives to achieve it. But original AHP model is not efficient for large-scale systems, which limits its capability under real-time use cases. To overcome this issue, various machine learning based techniques are proposed, and each of them has their own set of limitations. Techniques with higher efficiency also showcase high complexity, while simplistic optimization techniques have limited performance levels. To overcome these limitations, this text proposes design of an efficient AHP model with low complexity via integration of (GWO), and iterative learning (IL) operations. the proposed model initially performs context-based correlation between input parameter sets. these correlation values are used to modify the AHP decisions, which are tuned by GWO process. Results of Grey Wolf optimization this GWO process are optimized via IL based tuning, which incrementally modifies the correlation values for optimum efficiency levels. Due to which the proposed model showcases low complexity, while maintaining higher efficiency when compared with the original AHP process. the proposed model was evaluated on multiple datasets including housing, image processing, and employment scenarios. Based on this evaluation it was observed that the proposed model showcased 8.5% higher accuracy, 6.4% higher precision, with 4.5% 1ower delay when compared with original AHP and standard AHP-optimization techniques. Due to this improvement, the proposed model is capable of deployment for a wide variety of real-time scenarios. © 2023 IEEE.

关键词： 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419页 << < 149 150 151 152 153 154 155 156 157 158 > >>

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：