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

34,825 篇 会议
5,749 篇 期刊文献
296 册 图书

馆藏范围

40,870 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

25,549 篇 工学
- 17,910 篇 计算机科学与技术...
- 15,005 篇 软件工程
- 6,564 篇 信息与通信工程
- 4,222 篇 控制科学与工程
- 3,253 篇 电子科学与技术（可...
- 3,205 篇 电气工程
- 2,620 篇 生物工程
- 2,155 篇 生物医学工程（可授...
- 1,793 篇 光学工程
- 1,689 篇 机械工程
- 1,448 篇 动力工程及工程热...
- 1,421 篇 仪器科学与技术
- 1,253 篇 化学工程与技术
- 954 篇 安全科学与工程
- 850 篇 交通运输工程
- 781 篇 建筑学
13,171 篇 理学
- 7,160 篇 数学
- 3,666 篇 物理学
- 2,884 篇 生物学
- 2,315 篇 统计学（可授理学、...
- 1,598 篇 系统科学
- 1,294 篇 化学
6,464 篇 管理学
- 3,838 篇 管理科学与工程(可...
- 2,940 篇 图书情报与档案管...
- 2,180 篇 工商管理
1,792 篇 医学
- 1,541 篇 临床医学
- 1,438 篇 基础医学(可授医学...
- 942 篇 药学(可授医学、理...
1,175 篇 法学
- 965 篇 社会学
778 篇 经济学
- 777 篇 应用经济学
556 篇 农学
547 篇 教育学
169 篇 文学
93 篇 军事学
46 篇 艺术学
3 篇 哲学
2 篇 历史学

主题

1,173 篇 accuracy
917 篇 computational mo...
886 篇 feature extracti...
745 篇 training
735 篇 deep learning
734 篇 computer science
579 篇 machine learning
549 篇 real-time system...
534 篇 support vector m...
516 篇 predictive model...
441 篇 internet of thin...
413 篇 data models
379 篇 convolutional ne...
371 篇 optimization
354 篇 reliability
353 篇 computer archite...
316 篇 data mining
315 篇 artificial intel...
299 篇 routing
296 篇 visualization

机构

83 篇 institut univers...
82 篇 north-west unive...
81 篇 national centre ...
79 篇 infn sezione di ...
76 篇 infn sezione di ...
76 篇 institute of inf...
67 篇 tno technical sc...
66 篇 università di ca...
59 篇 université de st...
58 篇 dept. of informa...
56 篇 dept. of compute...
53 篇 leiden universit...
52 篇 school of automa...
46 篇 dept. of compute...
44 篇 dept. of compute...
44 篇 dept. of electri...
44 篇 nikhef national ...
44 篇 dept. of compute...
42 篇 infn lnf via enr...
42 篇 in2p3 lpc campus...

作者

85 篇 ferrara g.
85 篇 ardid m.
85 篇 gal t.
85 篇 bozza c.
84 篇 calvo d.
81 篇 chen a.
78 篇 kalekin o.
78 篇 díaz a.f.
75 篇 boumaaza j.
72 篇 coleiro a.
67 篇 huang f.
64 篇 gozzini s.r.
52 篇 kulikovskiy v.
50 篇 dallier r.
42 篇 anguita m.
41 篇 benoit d.m.
41 篇 eddymaoui a.
41 篇 del burgo r.
40 篇 gagliardini s.
40 篇 labalme m.

语言

38,671 篇 英文
1,663 篇 其他
370 篇 中文
116 篇 日文
47 篇 朝鲜文
5 篇 德文
3 篇 法文
2 篇 斯洛文尼亚文
1 篇 葡萄牙文
1 篇 俄文
1 篇 土耳其文

检索条件"机构=Dept. of Computer Engineering and Systems Science"

共 40870 条记录，以下是721-730 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：

Architectural Design for AdhaarAssist - A Forward-Looking Lock-Free STM Solution for Adhaar

Architectural Design for AdhaarAssist - A Forward-Looking Lo...

引用

2024 IEEE International Conference on Signal Processing and Advance Research in Computing, SPARC 2024

作者： Jafar, Sana Pranveer Singh Institute of Technology Dept. of Computer Science and Engineering Kanpur India

ISBN: (纸本)9798350385199

Any parallel program is judged based on its efficiency in doing multiple tasks at the same time without getting stuck due to an underlying problem. The main purpose of a parallel program is to effectively and quickly solve a large and complicated problem at hand. This is why;parallel programs form the basis of many powerful supercomputers where parallel computing is supported through special hardware which is complemented with parallel software achieving hundreds of petaflop/s of performance. The biggest challenge for a parallel programmer is to build a program that has a minimum tradeoff for increased parallelism and good concurrency control among the parallel tasks. One of the biggest applications of parallelism is the huge, ever-increasing database of Adhaar biometric. Its crucial to have a robust, fast and efficient way of accessing and manipulating this data so that along with faster results, consistency of the database is also maintained. This paper proposes a schema AdhaarAssist which is a lock-free STM based algorithm that will work on a shared in-memory data structure. Some of its features are increased concurrency by lazy conflict detection, partial aborts that optimize the algorithm for maximum throughput when complex and lengthy transactions are employed, memory barriers and timestamping. The algorithm proposed in this paper will open the way for leveraging it for distributed-shared in-memory databases like the one used by Adhaar. © 2024 IEEE.

关键词： Concurrency control

来源：评论

学校读者我要写书评

暂无评论

Enhanced Machine Learning Approach for Detecting Spammers in Industrial Mobile Cloud Computing Environment 5

Enhanced Machine Learning Approach for Detecting Spammers in...

引用

5th International Conference on IoT Based Control Networks and Intelligent systems, ICICNIS 2024

作者： Bhavana, K. Sai Abhinandu, B. Sriyesh, P. Sai Rama, K. Satheesh Kumar, S. Institute of Aeronautical Engineering Dept. Computer Science & Information Technology Hyderabad India

ISBN: (纸本)9798331518097

This research study proposes an innovative machine learning algorithm, Spammer Identification Novel K-Means Extension (SINKEX), to fortify IoT mobile networks against commands and potential disruptions in industrial production. Utilizing an industrial mobile cloud dataset, the algorithm employs basic, content, and network features, including follower count, post frequency, message content, and hyperlink usage, for spam detection. After employing Pearson Correlation and Euclidean Distance to eliminate dissimilar records, Principal Component Analysis (PCA) is applied to remove irrelevant features. The SINKEX algorithm then labels unclassified records, designating an account as a SPAMMER or NON-SPAMMER based on features like follower count and post frequency. Comparisons with a hybrid fuzzy c-means clustering algorithm demonstrate SINKEX's superior performance, achieving higher accuracy, precision, and recall. The results are presented through an intuitive graphical user interface, showcasing the algorithm's effectiveness in securing industrial IoT networks against malicious activities. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Classification of Epileptic Seizure Using 2L- LSTM Architecture

Classification of Epileptic Seizure Using 2L- LSTM Architect...

引用

2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Dhondiyal, Shiv Ashish Dimri, Sushil Chandra Malik, Preeti Graphic Era Deemed to Be University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350373783

Epilepsy is a long-term neurological problem that makes it hard for people to function their daily lives normally because their seizures can happen at any time. People who have epileptic seizures often hurt their brains, which can lead to memory loss, mental decline, and other problems. Because of this, it is important to find epileptic seizures quickly and get medical help for them. This paper presents the optimized two-layer long short-term memory model (2L-LSTM), and it can automatically expand retrospectively and for each patient. The program automatically creates distinctive characteristics that help identify seizure patients as either epileptic or not epileptic in real time. The proposed two layer Long Short-Term Memory (2L-LSTM) classifier classifies Epileptic or non-Epileptic signals with up to 98% accuracy. It also gives the sensitivity, specificity and F1-score of 95%, 94% and 96% respectively. The Simulation results shows that proposed 2L-LSTM model perform far better as compared to 1L-LSTM. © 2024 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Eva: Python-based Desktop Virtual Assistant for Visually Impaired 7

Eva: Python-based Desktop Virtual Assistant for Visually Imp...

引用

7th International Conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Abraham, Anishamol Mathew, Benita Susan Mathew, Dona Lisa Mohammad, Fiaz S Krishnan, Gokul Amal Jyothi College of Engineering Dept. of Computer Science Kottayam686518 India

ISBN: (纸本)9798350372816

Virtual assistants have become essential resources in the digital age, providing users with a wide range of functionalities to expedite work and increase productivity. In this research, we provide a complete examination of Eva, a virtual assistant created using Python, and compare it to other virtual assistants such as Cortana and Copilot. Through a meticulous examination of Eva's features, we demonstrate its superiority in versatility and effectiveness. By embracing Eva's strengths and capitalizing on its competitive advantages, we push for a future in which digital experiences are inclusive and empowering for all users. © 2024 IEEE.

关键词： Python

来源：评论

学校读者我要写书评

暂无评论

Lip Reading Into Text Using Deep Learning 14

Lip Reading Into Text Using Deep Learning

引用

14th International Conference on Cloud Computing, Data science and engineering, Confluence 2024

作者： Manglani, Krishna Bahuguna, Utkarsh Gupta, Subhash Chand Amity School of Engineering and Technology Dept. of Computer Science Uttar Pradesh India

ISBN: (纸本)9798350344837

An essential part of computer vision, lip reading, has grown significantly and is now used in autonomous driving, public safety, and hearing-impaired communication. This work provides an in-dept. analysis of both conventional and deep learning-based lip reading systems, examining their development over time, difficulties encountered, and critical role in human communication. The suggested LipNet model, which leverages the complementary abilities of Long Short-Term Memory networks (LSTMs) for temporal modelling and Convolutional Neural Networks (CNNs) for spatial feature extraction, is a central focus of this research. When LipNet is tested using the GRID Corpus dataset, it outperforms baseline models in terms of performance. Saliency maps and viseme analysis highlight LipNet's ability to capture phonologically relevant areas in lip motions, providing insight into the network's attention processes. Apart from examining the importance of datasets such as OuluVs2and GRID Corpus, this study presents GhostNet, a lightweight model that tackles the requirement for effective network designs. The testing results highlight LipNet's competitive Character Error Rate (CER) and Word Error Rate (WER) in comparison to baseline models, proving that it is the best method for real-world use. The research ends with a summary of potential future developments in lip reading technology, such as modal integration, realtime applications, personalisation, ethical issues, and the goal of creating a communication environment that is more inclusive. This study highlights the effectiveness of LipNet and paves the way for future developments in the ever-evolving area of lip reading by examining a variety of methodologies. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

An Innovative Ensemble Approach to Detecting Distributed Denial of Service Attacks Using Machine Learning

An Innovative Ensemble Approach to Detecting Distributed Den...

引用

2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Applications, ICAIQSA 2024

作者： Rajput, Deepak Singh Upadhyay, Arvind Kumar Amity University Dept. of Computer Science and Engineering Madhya Pradesh Gwalior India

ISBN: (纸本)9798331517953

In the present era marked by rapid Internet development, there is a growing emphasis on information security. Distributed Denial of Service (DDoS) attacks poses significant threats to servers globally. Various methods and services have emerged to prevent and mitigate damage caused by these attacks. The challenge in implementing defence lies in timely attack detection, requiring a highly accurate mechanism. DDoS attack methods are diverse and evolving, rendering traditional prevention methods less effective. This research explores the application of machine learning, utilizing the CICDDoS2019 dataset to train hybrid models. The proposed ensemble model combines unsupervised K-Means for dataset labelling and supervised classifiers (Random Forest, XGBoost, AdaBoost, SVM) with Artificial Neural Network (ANN). Achieving an overall accuracy of 99.46%, this study underscores the effectiveness of deep learning in DDoS attack detection. © 2024 IEEE.

关键词： Random forests

来源：评论

学校读者我要写书评

暂无评论

Survey on Online Learning Applications in Multi-UAV Networks 15

Survey on Online Learning Applications in Multi-UAV Networks

引用

15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Kim, Jaemin Kim, Hyosu Paek, Jeongyeup Son, Yongseok Lee, Hyung Tae Cho, Sungrae Chung-Ang University Dept. of Computer Science and Engineering Seoul Korea Republic of

ISBN: (纸本)9798350364637

This paper provides a comprehensive review of the application of online learning techniques in multi-UAV systems, highlighting their role in enhancing autonomy and efficiency in dynamic environments. Key areas of focus include adaptive path planning, collision avoidance, and swarm behavior control, along with the associated technical challenges and future research directions. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Hybrid Residual Blocks - Transformers Improving Cardiac MRI Segmentation in Deep Learning

Hybrid Residual Blocks - Transformers Improving Cardiac MRI ...

引用

2023 IEEE International Conference on Communications, Information, Electronic and Energy systems, CIEES 2023

作者： Naser, Maysaa Abd Ulkareem Al-Asadi, Abbas H. Hassin University of Basrah Dept. of Computer Information Systems Basrah Iraq Kufa University Dept. of Computer Science Kufa Iraq

ISBN: (纸本)9798350336917

Cardiovascular disease is one of the primary causes of mortality and disability. By assisting in early diagnosis, segmentation techniques based on deep learning might help to lessen their severity, although extremely high levels of accuracy are required. Introduce a novel and flexible architecture that raises the bar for semantic segmentation accuracy in this study. Our contributions focus on the merging of strong self-attention mechanisms obtained from Transformer with traditional convolutional neural network (CNN) architecture. This hybrid model demonstrates improved feature representation, contextual understanding, and pixel-wise predictions, setting new standards in semantic segmentation tasks. the average dice coefficients for ACDC dataset by our model, AVG DICE 92.52%, RV 90.77%, MYO 90.00%, LV 96.2S% © 2023 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Transformer-based Self-Supervised Imputation and Attention GANs Oversampling for Medical Data Processing 31

Transformer-based Self-Supervised Imputation and Attention G...

引用

31st Annual IEEE International Conference on High Performance Computing, Data, and Analytics, HiPC 2024

作者： Singh, Aryan Kumar Saikia, Arpit Baro, Pranita Borah, Malaya Dutta Dept. of Computer Science and Engineering National Institute of Technology Silchar Silchar India

ISBN: (纸本)9798331509095

Dealing with missing data and class imbalance is a necessity for the development of a solid predictive model in medical research. This work presents a novel hybrid dynamic method devoted to addressing these dual challenges, specifically focusing on medical datasets. In this work, we investigate the incompleteness and imbalance of the dataset using two sophisticated measures: the Incompleteness Factor and the Imbalance Ratio. These metrics are used to guide customized approaches. A transformer-based imputation method is employed to learn complex data dependencies to impute missing data. Second, the oversampling method of Self-Attention Enhanced Conditional Generative Adversarial Network is implemented. This technique generates better model training results by accommodating self-attention mechanisms that create fake samples that follow the actual data distributions as well as class distributions. This paper introduces one potential solution to obtain model-level accuracy increase for tasks like disease prediction, patient prognosis, etc., over medical datasets. The proposed method aims to remove the measurement biases caused by incompleteness and class imbalance and preprocess the data to enhance the credibility and clinical relevance of the experimental results. © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-based Decision Making for Charging/Discharging Cost Optimization of PREV in Smart City 1

Machine Learning-based Decision Making for Charging/Discharg...

引用

1st International Symposium on Parallel Computing and Distributed systems, PCDS 2024

作者： Neelakantam, Gone Ecole Centrale School of Engineering Mahindra University Dept. Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350349658

Smart cities, equipped with smart grid infrastructure, establish advanced communication networks that facilitate interactions among multiple entities. It is well-known that smart grid technology ensures the reliable transmission of electricity. Additionally, Plug-in Hybrid Electric Vehicles (PHEVs) significantly contribute to the efficient utilization of energy in mobility-aware environments. The Intelligent Transportation System (ITS) enables Vehicle-to-Infrastructure (V2I) communication, which is crucial for providing transportation services and managing PHEV recharging at user-preferred locations. This capability is a key element of smart city infrastructure. To optimize the use of PHEV services in a smart city, addressing the cost minimization of charging and discharging is essential. Therefore, this paper proposes a decision tree machine learning-based algorithm within a fog computing platform aimed at minimizing charging and discharging costs. Performance evaluation demonstrates that the model outperforms existing algorithms in terms of accuracy. These results indicate that our model can accurately predict the costs associated with charging and discharging PHEVs in smart city environments. © 2024 IEEE.

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500页 << < 69 70 71 72 73 74 75 76 77 78 > >>

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：