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

40,424 篇 会议
105 篇 期刊文献
97 册 图书

馆藏范围

40,626 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

23,007 篇 工学
- 19,828 篇 计算机科学与技术...
- 17,960 篇 软件工程
- 7,848 篇 信息与通信工程
- 7,818 篇 生物工程
- 4,814 篇 控制科学与工程
- 3,902 篇 生物医学工程（可授...
- 2,970 篇 电气工程
- 2,738 篇 光学工程
- 1,917 篇 网络空间安全
- 1,854 篇 电子科学与技术（可...
- 1,631 篇 安全科学与工程
- 1,434 篇 机械工程
- 1,424 篇 交通运输工程
- 1,343 篇 动力工程及工程热...
- 1,251 篇 化学工程与技术
14,245 篇 理学
- 8,024 篇 生物学
- 6,069 篇 数学
- 3,062 篇 物理学
- 2,808 篇 统计学（可授理学、...
- 1,467 篇 系统科学
- 1,462 篇 化学
7,484 篇 管理学
- 4,222 篇 图书情报与档案管...
- 3,679 篇 管理科学与工程(可...
- 2,014 篇 工商管理
3,602 篇 医学
- 3,120 篇 临床医学
- 3,076 篇 基础医学(可授医学...
- 2,390 篇 药学(可授医学、理...
- 1,390 篇 公共卫生与预防医...
1,563 篇 法学
- 1,390 篇 社会学
1,286 篇 教育学
- 1,282 篇 教育学
1,126 篇 农学
804 篇 经济学
283 篇 文学
53 篇 军事学
2 篇 艺术学
1 篇 哲学
1 篇 历史学

主题

2,369 篇 deep learning
1,938 篇 machine learning
822 篇 support vector m...
639 篇 convolutional ne...
566 篇 training
544 篇 feature extracti...
533 篇 forecasting
480 篇 computational mo...
466 篇 reinforcement le...
460 篇 machine learning...
456 篇 object detection
422 篇 computer vision
413 篇 neural networks
409 篇 internet of thin...
392 篇 predictive model...
355 篇 covid-19
332 篇 long short-term ...
309 篇 transfer learnin...
259 篇 convolution
254 篇 image segmentati...

机构

472 篇 chitkara univers...
135 篇 computer science...
126 篇 school of comput...
88 篇 karnataka bangal...
85 篇 college of compu...
83 篇 centre of interd...
67 篇 school of comput...
61 篇 school of comput...
58 篇 school of comput...
58 篇 graphic era deem...
53 篇 department of co...
50 篇 medical technica...
49 篇 computer science...
49 篇 school of comput...
47 篇 maharishi school...
46 篇 department of co...
43 篇 computer science...
43 篇 the islamic univ...
42 篇 department of co...
41 篇 school of comput...

作者

61 篇 shiva mehta
49 篇 sharma vikrant
40 篇 anjali t.
37 篇 vinay kukreja
34 篇 rakesh kumar
30 篇 deepak gerard
29 篇 sharma neha
27 篇 gill kanwarparta...
25 篇 vishal jain
25 篇 sheshang degadwa...
25 篇 li li
25 篇 nagaraj p.
24 篇 rishabh sharma
24 篇 kukreja vinay
22 篇 pareek piyush ku...
22 篇 shanmugasundaram...
21 篇 yu wang
21 篇 dhairya vyas
20 篇 kumar manish
20 篇 p nagaraj

语言

39,647 篇 英文
965 篇 其他
274 篇 中文
4 篇 葡萄牙文
3 篇 西班牙文
1 篇 德文
1 篇 土耳其文

检索条件"任意字段=2023 International Conference on Computer Engineering and Distance Learning, CEDL 2023"

共 40626 条记录，以下是4871-4880 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：

Automated diabetes diagnosis and risk assessment using machine learning 2nd

Automated diabetes diagnosis and risk assessment using machi...

引用

2nd international conference on Next-Generation Computing and Information Systems, ICNGCIS 2023

作者： Mathukiya, Deep Kumar, Yogesh Koul, Apeksha Department of Computer Science and Engineering School of Technology Pandit Deendayal Energy University Gandhinagar India Punjabi University Punjab Patiala India

ISBN: (纸本)9781032738659

Currently, Diabetes is a prevalent issue worldwide, affecting millions of people. The detection machinery for this disease is only available at healthcare centers, so individuals with diabetes are only aware of their condition when they visit and undergo a checkup. Prolonged diabetes can lead to various complications like heart disorders, kidney disease, nerve damage, and diabetic retinopathy. However, the risk can be reduced if the disease at its early stage is predicted. By utilizing a deep learning approach, this model can easily determine if an individual is diabetic or not. The aim of the research is to develop machine learning model that can identify diabetic people on the basis of their clinical data. The machine learning algorithms utilized in this study include Naive Bayes (NB), k-nearest neighbor (KNN), Stochastic Gradient Descent (SGD), Decision tree (DT), Support Vector Machine (SVM), Random Forest (RF), and Logistic Regression (LR). We have implemented efficient pre-processing techniques to detect as well as handle missing/ NAN and duplicate values and later trained our models with the cleaned dataset. During execution, we found that Random Forest as well as Decision Tree performed well for both diabetic and non-diabetic class by computing 100% and 99% accuracy respectively. © 2025 The Author(s).

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

TLRNet: Tibetan Lip Reading Based on ResNet and BiGRU 2

TLRNet: Tibetan Lip Reading Based on ResNet and BiGRU

引用

2nd Asia conference on Electrical, Power and computer engineering, EPCE 2023

作者： Gan, Zhenye Ding, Xu Yu, Xinke Kong, Zhenxing Northwest Normal University Engineering Research Center of Gansu Province for Intelligent Information Technology and Application College of Physics and Electronic Engineering Lanzhou China

ISBN: (纸本)9798350310818

Lip reading, also known as visual speech recognition, is a way of human-computer interaction based on visual information. At present, the research on lip reading mainly focuses on English and Mandarin Chinese, and there are relatively few studies on Tibetan, a low-resource minority language. Therefore, the present study proposes a specific deep learning model named the TLRNet for word-level visual speech recognition for Tibetan. The model comprises the ResNet-18 architecture, which is a residual neural network, and the BiGRU layer, a bi-directional gated recurrent unit. We train and evaluate it on the TLRW-50 dataset, which consists of fifty common Tibetan words. Our proposed model achieves Top-1 and Top-5 classification accuracies of 41.82% and 59.37%, respectively, demonstrating its potential effectiveness in recognizing Tibetan spoken words based on visual cues. © 2023 IEEE.

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

Dynamics of the learning Process of a Multilayer Neural Network when using the AdaDelta Optimization Method 24

Dynamics of the Learning Process of a Multilayer Neural Netw...

引用

24th international conference on Computational Problems of Electrical engineering, CPEE 2023

作者： Sveleba, S. Katerynchuk, I. Kunyo, I. Brygilevych, V. Kotsun, V. Sidelnyk, Yu. National University of Lviv Department of Optoelectronics and Information Technologies Ivan Franko Lviv Ukraine The State Higher School of Technologyand Economics in Jaroslaw Jaroslaw Poland Lviv Branch of Private Higher Education Establishment 'European University' Lviv Ukraine Faculty of Electronics and Computer Technologies

ISBN: (纸本)9798350330342

The AdaDelta learning process optimization method has been tested for a multilayer neural network with two hidden layers with 28 neurons each, when recognizing printed numbers. Testing the learning error of this neural network was carried out using the mapping function and Fourier spectra of the error function. The mapping function describes the process of doubling the number of local minima. It is found that the application of the AdaDelta optimization method leads to a radically different picture of the behavior of the branching diagram than when applying the learning optimization methods Adam, AdamMax, and AMSGrad. Namely, with an increase in the number of iterations, the process is 'extinguished' by retraining, by correcting the learning step of each neuron. It is shown that the hyperparameter ρ, which describes the contribution of the gradient square of the error function, significantly influences on the learning process of the neural network That is, increasing the optimization parameter ρ to (0.9 div 0.999) causes a decrease in the region of change of the magnitude of the learning step. The step is selected automatically during training, for each neuron according to the AdaDelta optimization algorithm. It is shown that the optimal value of the optimization parameter ρ is 0.9. © 2023 IEEE.

关键词： Python

来源：评论

学校读者我要写书评

暂无评论

A Deep learning Approach for Non-Invasive Hypertension Classification from PPG Signal

A Deep Learning Approach for Non-Invasive Hypertension Class...

引用

2023 international conference on Next-Generation Computing, IoT and Machine learning, NCIM 2023

作者： Promi, Rifah Tasnim Haque Nazri, Rezwana Akter Salim, Md. Shahidul Raju, S. M. Taslim Uddin Department of Computer Science and Engineering Khulna9203 Bangladesh

ISBN: (纸本)9798350316001

Hypertension or high blood pressure is the leading risk factor with the largest contribution to the burden of disease and mortality. Therefore, regular blood pressure (BP) checks are necessary to track hypertension and reduce risk. In light of this, we have proposed a noninvasive method for hypertension detection based on photoplethysmography (PPG) signals using deep learning techniques. A hybrid deep learning model consisting of a Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) is introduced. First, PPG signals were acquired from 219 subjects, which underwent pre-processing steps. Then, hypertension was detected with satisfactory results by using our proposed model. Here, CNN is used to extract features in order to work better in classification tasks. Our proposed model constructed with CNN and GRU achieved an Accuracy of 85.00 %, Recall of 84.44 %, Precision of 87.77% and F1-score of 86.08%. Our goal is to improve the medical industry by precisely detecting hypertension. © 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

Auto-grading C programming assignments with CodeBERT and Random Forest Regressor 14

Auto-grading C programming assignments with CodeBERT and Ran...

引用

14th international conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Muddaluru, Roshan Vasu Thoguluva, Sharvaani Ravikumar Prabha, Shruti Pati, Peeta Basa Balakrishnan, Roshni M Amrita Vishwa Vidyapeetham Dept of Computer Science Engineering Bengaluru India

ISBN: (纸本)9798350335095

Grading coding assignments manually is challenging due to complexity and subjectivity. However, auto-grading with deep learning simplifies the task. It objectively assesses code quality, detects errors, and assigns marks accurately, reducing the burden on instructors while ensuring efficient and fair assessment. This study provides an analysis of auto-grading of the C programming assignments using machine learning and deep learning approaches like regression, convolutional neural networks (CNN) and long short-term memory (LSTM). Using a code-based transformer word embedding model called CodeBERT, the textual code inputs were transformed into vectors, and the vectors were then fed into several models. The testing findings demonstrated the efficacy of the suggested strategy with a root mean squared error (RMSE) of 1.89. The contrast between statistical methods and deep learning techniques is discussed in the study. © 2023 IEEE.

关键词： Grading

来源：评论

学校读者我要写书评

暂无评论

Machine learning-Aided Optimization Approach for Sustainable Energy Systems 1

Machine Learning-Aided Optimization Approach for Sustainable...

引用

1st IEEE international conference on Emerging Research in Computational Science, ICERCS 2023

作者： Hussian, Ahmed Ali Ettyem, Sajjad Ali Zearah, Sajad Ahmed, Ibrahem Ismail, Laith S. Ibrahem, Marwa Al-Kunooze University College Technical Computer Engineering Department Basrah Iraq National University of Science and Technology Dhi Qar Department of Medical Devices Engineering Technologies Nasiriyah Iraq Al-Ayen University Thi-Qar Scientific Research Center Iraq Al-Farahidi University Medical Instruments Engineering Techniques Baghdad Iraq Al-Turath University College Computer Technologies Engineering Baghdad Iraq Al-Maamoun University College Computer Technology Engineering Baghdad Iraq

ISBN: (纸本)9798350359756

Energy derived from renewable sources is expanding quickly. Renewable energy systems meet off-grid and on-grid load requirements, often connected to conventional sources. Geothermal, solar, wind, and other renewable energy sources can be harnessed economically at the current rate of technological development. Renewable-based electricity production is an alternative form of green power generation that reduces issues with energy consumption. Though this raises numerous uncertainties and difficulties, it may jeopardize potential economic, technological, and environmental gains. Consequently, a Machine learning aided Optimization Approach (MLOA) for sustainable energy systems has been suggested in this study. The Enhanced Long Short-Term Memory (E-LSTM) model of recurrent neural networks trained by Adam optimizer is employed in MLOA due to its ability to predict solar and wind generation to provide optimal energy consumption control. The numerical outcomes demonstrate that the suggested MLOA method improves prediction and accuracy rates by 98.22% compared to other current approaches. © 2023 IEEE.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Utilization of Processing of Images in Bio-Acoustics

Utilization of Processing of Images in Bio-Acoustics

引用

2023 international conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Raja Praveen, K.N. Shrimal, Gajendra Shukla, Meenu Computer Science Department Bangalore India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350357769

The present research examines how the Felsenstein approach might be improved in light of huge data and evolutionary inference. The Felsenstein approach, phylogeny starting points, huge data, statistical techniques, and testing hypotheses are among the important ideas and terms covered in the overview. It emphasizes the importance of repeatability in evolutionary inferences as well as the difficulties brought on by rogue genera and bootstrapping proportions. The article suggests a brand-new strategy to increase the accuracy of phylogenetic investigations that makes use of transfer separation and bipartition distance. The abstract's conclusion emphasizes the need of better methods for managing huge datasets and for recognizing instability taxonomic. This study dives into the refining of the Felsenstein technique within the setting of vast data and evolution prediction. Essential ideas comprise the Felsenstein method, evolutionary points of departure, problems associated with huge datasets, methods in statistics, and testing hypotheses. Noteworthy focus is made on the relevance of reproducibility in phylogenetic conclusions, along with the complexity provided by rogue families and ramping percentages. The article provides a unique technique targeted at boosting the accuracy of phylogenetic studies, utilising transfer isolation and bipartition distances. The summary continues by highlighting the essential need for sophisticated approaches capable of successfully handling big datasets and spotting taxonomic fragility. © 2023 IEEE.

关键词： ABC Big data Bipartition distance Bootstrap Confidence intervals Felsenstein method Homogenization Hypothesis testing Phylogenetic estimation Phylogenetic starting Reboot method Rogue taxa Statistical approach Taxonomic units Transfer distance

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Transportation Using Deep Reinforcement learning: A Comprehensive Review 15

Revolutionizing Transportation Using Deep Reinforcement Lear...

引用

15th IEEE international conference on Computational Intelligence and Communication Networks, CICN 2023

作者： Rai, Salabh Dixit, Aryan Yadav, Ashutosh Bhushan, Bharat Computer Science and Engineering Sharda University Greater Noida India

ISBN: (纸本)9798350324433

Deep Reinforcement learning (DRL) is revolutionizing the way many challenging transportation decision-making problems are approached. This potent learning-based technology is used more frequently to tackle difficult challenges in the domain of transportation. Any control-based system, including those in electricity, robotics, transportation, and the Internet of Things, can benefit from new data-driven research methodologies. This paper provides a summary of the mathematical foundation of DRL, as well as several very successful DRL extensions and well-liked and prospective DRL algorithms. On the basis of above analysis the paper further explore the suitability, advantages, disadvantages, and general and particular application-related problems of DRL approaches for their use in transportation. Finally, this paper outlines the future research paths and resources that might be used to put DRL into practice. © 2023 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

A Server Anomaly Detection Method Based on EWC and LSTM-GAN 9

A Server Anomaly Detection Method Based on EWC and LSTM-GAN

引用

9th international conference on computer and Communications, ICCC 2023

作者： Yu, Lei Le, Wei Chengdu University of Information Technology School of Software Engineering Chengdu China Chengdu University of Information Technology Sichuan Manufacturing Information Industry Collaborative Innovation Center School of Software Engineering Chengdu China

ISBN: (纸本)9798350317251

In the realm of server operations and maintenance, anomaly data is often characterized by its rarity, evolving over time with the influx of new data. Models require continuous parameter updates to adapt to these shifting data distributions. To address these challenges, this paper introduces a method for detecting anomalous server data based on Adversarial learning and Elastic Weight Consolidation (EWCAD-GAN). Firstly, this method employs stacked Long Short-Term Memory networks (LSTM) as both the generator and discriminator, using adversarial training principles to obtain an initial model. Secondly, the Elastic Weight Consolidation (EWC) algorithm is applied to fine-tune the model obtained after adversarial training, bolstering the model's ability to remember temporal patterns within time- series data. This approach alleviates the difficulties associated with training models on rare anomalous data and facilitates online learning through the use of the EWC algorithm. Experimental evaluations of this method were conducted on two publicly available datasets for intelligent operations and maintenance anomaly detection. The results clearly demonstrate that EWCAD- GAN outperforms other similar methods, achieving significantly higher anomaly detection accuracy while simultaneously addressing the challenges associated with model training and online learning. © 2023 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

An Improved Deep Reinforcement learning for Robot Navigation 3

An Improved Deep Reinforcement Learning for Robot Navigation

引用

3rd international conference on Machine learning and computer Application, ICMLCA 2022

作者： Zheng, Qifeng Huang, Xiaogang Dong, Chen Liu, Yuting Cheng, Dong College of Computer and Data Science Fuzhou University Fuzhou China

ISBN: (纸本)9781510664814

Collision-free navigation is an important research direction for multi-robot systems, in which the two core problems are navigating to the target point and avoiding other robots. Many researchers use deep reinforcement learning as navigation strategy to realize multi-robot collision avoidance navigation. However, most of them use raw sensor information or global state information of the agent as the neural network input, which is not conducive to extending the navigation strategy to a larger space. This paper proposes an improved deep reinforcement learning navigation strategy, which enables robots to learn navigation and collision avoidance strategies more accurately. This strategy converts the interactive environment state from the global coordinate representation to the relative vector representation, and attenuates the influence of the rear irrelevant agents on the collision avoidance strategy. Experimental results show that the proposed method outperforms existing learning-based methods in three indicators: success rate, additional time to reach the target, and model convergence speed. © 2023 SPIE.

关键词： Multipurpose robots

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 << < 484 485 486 487 488 489 490 491 492 493 > >>

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：