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

20,103 篇 会议
103 篇 期刊文献
49 册 图书

馆藏范围

20,255 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

14,206 篇 工学
- 11,477 篇 计算机科学与技术...
- 8,851 篇 软件工程
- 3,234 篇 信息与通信工程
- 2,496 篇 生物工程
- 2,262 篇 控制科学与工程
- 1,800 篇 电气工程
- 1,487 篇 生物医学工程（可授...
- 1,045 篇 机械工程
- 1,028 篇 光学工程
- 1,026 篇 电子科学与技术（可...
- 797 篇 安全科学与工程
- 777 篇 动力工程及工程热...
- 761 篇 交通运输工程
- 681 篇 仪器科学与技术
- 660 篇 化学工程与技术
- 483 篇 材料科学与工程（可...
6,783 篇 理学
- 3,489 篇 数学
- 2,659 篇 生物学
- 1,498 篇 统计学（可授理学、...
- 1,365 篇 物理学
- 844 篇 系统科学
- 738 篇 化学
4,236 篇 管理学
- 2,538 篇 管理科学与工程(可...
- 2,023 篇 图书情报与档案管...
- 1,280 篇 工商管理
1,434 篇 医学
- 1,287 篇 临床医学
- 1,240 篇 基础医学(可授医学...
- 764 篇 药学(可授医学、理...
- 631 篇 公共卫生与预防医...
693 篇 教育学
- 667 篇 教育学
560 篇 法学
487 篇 农学
450 篇 经济学
43 篇 军事学
27 篇 文学
8 篇 艺术学
1 篇 哲学

主题

1,325 篇 deep learning
1,128 篇 machine learning
836 篇 accuracy
561 篇 data mining
541 篇 support vector m...
534 篇 feature extracti...
427 篇 training
413 篇 data models
405 篇 convolutional ne...
397 篇 predictive model...
379 篇 internet of thin...
363 篇 real-time system...
332 篇 computational mo...
322 篇 neural networks
314 篇 big data
233 篇 reinforcement le...
216 篇 forecasting
180 篇 object detection
179 篇 machine learning...
174 篇 optimization

机构

227 篇 chitkara univers...
64 篇 centre of interd...
58 篇 maharishi school...
43 篇 maharishi school...
34 篇 college of techn...
33 篇 school of comput...
31 篇 pune
29 篇 the islamic univ...
28 篇 school of comput...
28 篇 chitkara univers...
26 篇 karnataka bangal...
26 篇 uttaranchal inst...
25 篇 uttaranchal univ...
24 篇 computer science...
24 篇 computer science...
23 篇 department of ar...
22 篇 graphic era deem...
22 篇 school of inform...
22 篇 department of in...
22 篇 national univers...

作者

22 篇 gill kanwarparta...
21 篇 wang lei
21 篇 kukreja vinay
20 篇 shiva mehta
19 篇 liu yang
18 篇 wang jing
15 篇 zhang tao
15 篇 malik bader alaz...
15 篇 joshi kapil
15 篇 singh jagendra
14 篇 yang yang
13 篇 zhang lei
13 篇 li yang
13 篇 chauhan rahul
12 篇 meena belwal
12 篇 novais paulo
12 篇 li li
11 篇 babu tina
11 篇 liu xin
11 篇 rupesh gupta

语言

15,418 篇 英文
4,818 篇 其他
125 篇 中文
3 篇 土耳其文
2 篇 西班牙文
1 篇 俄文

检索条件"任意字段=3rd International Conference on Intelligent Data Engineering and Automated Learning"

共 20255 条记录，以下是4571-4580 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：

MbAbI: A Benchmark dataset for Malayalam Text Understanding and Reasoning 3rd

MbAbI: A Benchmark Dataset for Malayalam Text Understanding ...

引用

3rd international conference on Computing and Communication Networks, ICCCN 2023

作者： Reji Rahmath, K. Reghu Raj, P.C. Rafeeque, P.C. Government Engineering College Palakkad India Government Engineering College Kozhikkode India Government College of Engineering Kannur India APJ Abdul Kalam Technological University Kerala Thiruvananthapuram India

ISBN: (纸本)9789819708918

This paper proposes a Malayalam dataset containing 40000 instances, intended to assist the researchers working on Question Answering systems. This data set is the first of its kind. The Facebook bAbI dataset was translated to create this Malayalam bAbI (or, MbAbI) dataset. It comprises 20 different tasks of varying complexity. The tasks include simple supporting facts to complex path finding tasks. We have machine translated these tasks from English to Malayalam and tested the baseline QA models on these datasets. We have obtained state-of-the-art results with MbAbI dataset using deep learning and transformer models. In order to benefit the low-resource Malayalam research community we have made this dataset publicly available. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Veinseg-Net: A Novel Finger Vein Segmentation Algorithm Based on Deep learning 23

Veinseg-Net: A Novel Finger Vein Segmentation Algorithm Base...

引用

3rd international conference on Bioinformatics and intelligent Computing, BIC 2023

作者： Xu, Hong Wang, Peng Sun, Yewei Ye, Caizeng School of Software Shandong University Jinan250101 China Jinan Engineering Polytechnic Jinan250200 China Hazen and Sawyer 4035 Ridge Top Rd Suite 500 FairfaxVA22030 United States Shandong Institute of Commerce and Technology Jinan250103 China National Agricultural Products Modern Logistics Engineering Technology Research Center Jinan250103 China

ISBN: (纸本)9798400700200

On the basis of the original U-Net and ResNet finger vein segmentation methods, this paper proposes a new finger vein segmentation method based on the combination of the above two methods. This method completes feature extraction by using depth residual network instead of U-Net. Using extended convolution instead of traditional convolution solves the risk of loss of finger vein information extracted by pooling layer, so that the method can extract finger vein veins more accurately without pooling. The algorithm uses the Mish constructor to replace the ReLU constructor to strengthen the anti-compression ability of the model and make vein image more continuous. From the comparison of experimental results, it is not difficult to see that the segmentation accuracy of the newly proposed Veinseg-Net network on multiple finger vein databases are better than those of other depth learning segmentation methods. The good segmentation accuracy of finger vein image can help the finger vein recognition process in the subsequent environment intelligence. © 2023 ACM.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Multi-label code smell Detection Method based on CodeBERT 3

Multi-label code smell Detection Method based on CodeBERT

引用

3rd international conference on Electronics and Information Technology, EIT 2024

作者： Bao, Hongming Wei, Le Chengdu University of Information Technology School of Software Engineering Chengdu China Sichuan Manufacturing Information Industry Collaborative Innovation Center Automatic Software Generation & Intelligence Service Key Laboratory of Sichuan Province Chengdu China

ISBN: (纸本)9798350369151

Code smells usually hint at possible problems or design flaws in the code. Efficient code smell detection methods can significantly improve code quality. However, existing code smell detection methods rely heavily on information such as metrics and indicators, fail to make full use of the syntax and semantics of source code, and have shortcomings in multi-label code smell detection. To this end, this paper proposes a Multi-Label Code Smell Detection Based on CodeBERT (MLCSDCB) based on the pre-trained model CodeBERT. Firstly, the constructed data set is preprocessed and standardized to reduce noise interference, and the multi-label data set is constructed by the label power set method. Then, CodeBERT is used to embed the code and extract its rich syntactic and semantic information. Then, Bi-LSTM was used to fully learn the Code Representation Information [CLS] vector of each layer of CodeBERT to enhance the context understanding ability of the model. Finally, the attention mechanism was used to strengthen the key information according to the importance of each layer [CLS] vector, and the multi-label prediction was performed based on the strengthened feature vector to improve the detection effect of the model. Compared with the existing detection methods based on source code representation, MLCSDCB improves the precision, recall and F1 value by 2.02%, 1.04%and 4.75%respectively. © 2024 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Unlocking IoT Security: Enabling the Future with Lightweight Cryptographic Ciphers 3rd

Unlocking IoT Security: Enabling the Future with Lightweight...

引用

3rd international conference on intelligent Computing Techniques for Smart Energy Systems, ICTSES 2023

作者： Chaturvedi, Srishti Priya Yadav, Ajay Kumar, Ashok Mukherjee, Rahul Bennett University Uttar Pradesh Greater Noida India Government Women Engineering College Rajasthan Ajmer India

ISBN: (纸本)9789819784288

The rapid expansion of the Internet of Things (IoT) has enabled the quick advancement of efficient and adaptable sensors. It is crucial to prioritize the security of data transfer for these devices. The consequences of failures within the realm of IoT can be serious. As a result, the examination and investigation of security concerns related to IoT holds tremendous importance. Lightweight block ciphers have become a significant paradigm in IoT networks. In the domain of cryptography, ongoing efforts revolve around contests and projects that seek to assess the suitability of lightweight ciphers for use in both hardware and software setups. This paper showcases the implementation of various lightweight ciphers such as PRESENT, TWINE, SIMON & SPECK, TEA & XTEA on AVR microcontroller along with AES and DES. This article evaluates the performance of lightweight ciphers on Arduino, which provides a metric for their effectiveness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Internet of Things (IoT) Lightweight cryptography Security

来源：评论

学校读者我要写书评

暂无评论

Memory Optimization and Computing of Emojis-based IoT Smart Pot 3

Memory Optimization and Computing of Emojis-based IoT Smart ...

引用

3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Kalimuthu, M. Narendra Ilaya Pallavan, P. Priya Varshini, G.U. Senthilkumar, S. Pragadeeshwarar, S. Karthick, R. Bannari Amman Institute of Technology Electronics and Instrumentation Engineering Sathyamangalam India

ISBN: (纸本)9798350322842

IoT is everywhere in today's world, from food industry to healthcare. So, we formulated an idea to implement the Internet of Things in a simple and efficient way on plant pots. Currently, indoor plants are sought after, and the quantity of individuals getting them is expanding every day. Gardeners want to grow healthy plants but maintaining plants in pots requires IoT of time and patience. Smart pot helps people to get connected to their plants. Smart pot has a super- intelligent monitoring system that helps to understand plants condition and update the user with emoji. Normal pots have no data monitoring system, tis give smile pot a huge advantage as data about the plant like humidity, moisture level, health of the plant can be monitored often and helps us for future analysis. Even the user can set regular watering session for the plant based on its need. The auto watering system helps to water plants when the moisture level is below par. Overwatering is a major drawback of using pot, smile pot even helps us to track level of water in soil and water plant only when needed. Pretty much anything with roots can grow in smart pot. This method encourages IoT of urban residents to engage with plants and create their own organic food. Thus, smile pot reduces undernourishment and helps to create a better chemical free food supply. © 2023 IEEE.

关键词： Moisture

来源：评论

学校读者我要写书评

暂无评论

Modeling and Simulation of High Frequency and High Precision Multi Axis Cooperative Control Based on Reinforcement learning 3

Modeling and Simulation of High Frequency and High Precision...

引用

3rd international conference on Computer, Control and Robotics, ICCCR 2023

作者： Wang, Haiyu Fu, Zhuang Yan, Jun Hua, Zuohao Guan, Yisheng School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China School of Electromechanical Engineering Guangdong University of Technology Guangzhou China

ISBN: (纸本)9781665492126

Reinforcement learning has attracted much attention in the field of mechanical control, but it has rarely been applied in projects requiring high precision and short control cycle. In order to realize the high frequency and high precision control of multi axis cooperative complex mechanism, this paper decouples and virtualizes the control system of a structure consisting of four valves, infers commands and send control signals at 500Hz, and controls the displacement precisely. The author modified the Proximal Policy Optimization algorithm and made some improvements in the updating rules and training environment, such as batch advantage normalization, attenuation of learning rate, strategy entropy reward, speed control reward, and addition of noise. Finally, the performance of the algorithm exceeded that of PID, ray-PPO in the simulation. © 2023 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Big data Analytics-Based Diabetes Prediction Model for Identifying Internal Factors for Diabetes Mellitus 3

Big Data Analytics-Based Diabetes Prediction Model for Ident...

引用

3rd IEEE Delhi Section Flagship conference, DELCON 2024

作者： Mallika, C. Vanitha, J. Kalaivani, K. Selvamuthukumaran, S. E.G.S. Pillay Engineering College Department of Mca Tamilnadu Nagapattinam India School of Computer Science and Engineering Vit Vellore Vellore India A.V.C. College of Engineering Mannampandal Mayiladuthura India

ISBN: (纸本)9798331518592

Diabetes mellitus (DM) is a serious global health concern. According to the international Diabetes Foundation, 537 million individuals are living with DM worldwide, and this figure is expected to reach 643 million by 2030 and 783 million by 2045. Therefore, there is a pressing need for timely prognosis, identification, and management of DM and its impediments. This research proposes an efficient model to identify DM using an optimized Support Vector Machine (SVM) algorithm. The proposed model implements the Stochastic Gradient Descent (SGD) optimization technique to fine-tune the SVM algorithm by updating hyperparameter. Thus, the cohesive SGD-SVM approach is more appropriate for big databases related to conventional SVM algorithms. The SGD-SVM algorithm can apprise the system progressively as new data arrives, which is beneficial for constantly growing databases. The performance of our OSVM model is meticulously analyzed using the Pima Indian database. To assess the hybrid SGD-SVM model, its classification enactment is compared with existing state-of-the-art machine learning-based diagnosis systems in terms of designated evaluation measures. The extensive results of the experimental analysis demonstrate that SGD-SVM is a more competent model with 95.7% accuracy, 84.2% sensitivity, 86.9% specificity, and 91.7% precision. Further, it realizes a minimal false alarm rate (i.e., 2.0% false positive rate (FPR) and 1.4% false negative rate (FNR)). Therefore, this study can conclude that SGD-SVM is the improved diabetes analytic tool as compared with other existing models found in the literature. © 2024 IEEE.

关键词： Stochastic models

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence in Quality4.0 3

Artificial intelligence in Quality4.0

引用

3rd international conference on Embedded Systems and Artificial Intelligence, ESAI 2024

作者： Lahmine, Souad Bennouna, Fatima ENSA of Fez LISA Department of Industrial Engineering Fez Morocco

ISBN: (纸本)9798331522056

Many studies, mostly based on different sectors applying Industry 4.0, do not highlight the role of artificial intelligence in those sectors and particularly in quality management. Though an appropriate amount of research regarding the implementation of Quality 4.0 has advanced, which is the evolution of quality management systems pertaining to technological alignment with Industry 4.0 technologies, it is mostly within the confined applications of a single sector. It has narrowed the general knowledge of how AI could really improvise processes of quality across different industries. This broad paper takes such a scope in aiming to assess the incorporation of AI in Quality 4.0 from a cross-sectoral view with a perspective to learn how advanced machine learning, predictive analytics, and real-Time data analytics can help polish quality management systems. The emphasis is placed upon the manner in which AI could assist an industry to manage large amounts of data, improve production efficiency, and forestall issue through proactive steps such as anomaly detection and predictive maintenance. With this study, by considering the prospect of AI in varied Eeconomic sectors, new doorways are unlocked for creative quality management practices. Our study attempts to establish that transformative potential of AI for process optimization under Quality 4.0 approaches that make them skillful, effective, and adaptive to rapidly evolving requirements in today's industrial setup. Therefore, it offers an insight into how AI can complement Quality 4.0 toward leading the future of industrial operations with the wider vision of Industry 4.0 while ensuring that the industries are coming up with even better solutions to cope with the complexities of the new production setups. © 2024 IEEE.

关键词： Artificial Intelligence (AI) Industry 4.0 Quality 4.0 quality management

来源：评论

学校读者我要写书评

暂无评论

Research on the development of a digital conservation system for cultural relics based on image recognition technology 23

Research on the development of a digital conservation system...

引用

3rd international conference on Bioinformatics and intelligent Computing, BIC 2023

作者： He, Yicheng Tang, Xinyao Wang, Xupeng School of Art and Design Xi'an University of Technology China School of Mechanical and Precision Instrument Engineering Xi'an University of Technology China

ISBN: (纸本)9798400700200

The system takes excavated cultural relics at archaeological sites during the excavation period as the research object, and composes the current situation of cultural relic protection during the excavation period. It proposes to build a 3D/2D model library of excavated cultural relics based on 3D laser scanning and imaging, data reconstruction, 3D modelling, 3D/2D graphics conversion and database;to realise a series of digital conservation such as accurate collection of archival data of excavated cultural relics and scientific management of cultural relics database, to shorten excavation cycle and improve excavation efficiency, and to provide theoretical basis and practical guidance for digital conservation of excavated cultural relics. © 2023 ACM.

关键词： Excavation

来源：评论

学校读者我要写书评

暂无评论

An intelligent decision making method based on Bayesian policy reuse framework 3

An intelligent decision making method based on Bayesian poli...

引用

3rd international conference on Electronic Communication and Artificial Intelligence, IWECAI 2022

作者： Zhang, Yixin Qi, Han Zhu, Li School of Software Engineering Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9781665479974

Transfer learning plays an important role in multi-agent reinforcement learning. Bayesian policy reuse(BPR) algorithm is an excellent transfer learning algorithm and has been successfully used in repeated stochastic games. BPR can quickly detect the opponents and select the optimal policy. BPR's main limitation is the need of an offline learning phase where the models (priori knowledge) can be obtained. However, BPR may perform poorly when there is a lack of prior knowledge or the prior knowledge is inaccurate. To solve this problem, we propose an algorithm that combine the no-regret with BPR. Our approach can be exploited to improve performance when the priori knowledge is accurate, and to achieve less poor performance when the priori knowledge is inaccurate. Our approach has robust theoretical guarantees and is validated on the repeated stochastic games. © 2022 IEEE.

关键词： Decision making

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 << < 454 455 456 457 458 459 460 461 462 463 > >>

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：