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

1,313 篇 会议
11 篇 期刊文献
9 册 图书

馆藏范围

1,333 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

901 篇 工学
- 745 篇 计算机科学与技术...
- 487 篇 软件工程
- 302 篇 信息与通信工程
- 204 篇 电气工程
- 175 篇 生物工程
- 126 篇 生物医学工程（可授...
- 105 篇 光学工程
- 89 篇 控制科学与工程
- 80 篇 电子科学与技术（可...
- 58 篇 仪器科学与技术
- 46 篇 机械工程
- 35 篇 化学工程与技术
- 27 篇 安全科学与工程
- 26 篇 交通运输工程
- 17 篇 动力工程及工程热...
423 篇 理学
- 189 篇 生物学
- 186 篇 数学
- 149 篇 物理学
- 76 篇 统计学（可授理学、...
- 54 篇 系统科学
- 40 篇 化学
165 篇 管理学
- 104 篇 图书情报与档案管...
- 69 篇 管理科学与工程(可...
- 37 篇 工商管理
145 篇 医学
- 129 篇 临床医学
- 87 篇 基础医学(可授医学...
- 65 篇 药学(可授医学、理...
- 23 篇 公共卫生与预防医...
28 篇 教育学
- 28 篇 教育学
27 篇 法学
- 21 篇 社会学
16 篇 经济学
16 篇 农学
5 篇 军事学
1 篇 文学
1 篇 历史学

主题

211 篇 machine learning
132 篇 deep learning
78 篇 signal processin...
72 篇 accuracy
71 篇 feature extracti...
68 篇 signal processin...
61 篇 support vector m...
57 篇 machine learning...
46 篇 predictive model...
33 篇 neural networks
32 篇 convolutional ne...
30 篇 random forests
29 篇 computational mo...
29 篇 training
26 篇 natural language...
26 篇 prediction algor...
21 篇 technological in...
20 篇 real-time system...
19 篇 adversarial mach...
18 篇 image processing

机构

16 篇 chitkara centre ...
14 篇 centre of resear...
12 篇 shenyang ligong ...
6 篇 ai & ds vishwaka...
6 篇 school of inform...
5 篇 department of me...
5 篇 khulna universit...
5 篇 department of co...
4 篇 delhi technologi...
4 篇 heilongjiang uni...
4 篇 department of s&...
4 篇 beijing univ pos...
4 篇 it vishwakarma i...
4 篇 department of co...
4 篇 sri lanka instit...
4 篇 advanced telecom...
4 篇 shenyang ligong ...
4 篇 graduate school ...
3 篇 chitkara univers...
3 篇 karunya institut...

作者

6 篇 mehta shiva
5 篇 rasmita panigrah...
4 篇 neelamadhab padh...
4 篇 wang xin
3 篇 m. vigenesh
3 篇 baydeti nagaraju
3 篇 sinambela marzuk...
3 篇 santosh kumar sh...
3 篇 ganapati panda
3 篇 debendra muduli
3 篇 abujar sheikh
3 篇 a. sivanantham
3 篇 li yajie
3 篇 li aihua
3 篇 zhou feng
3 篇 islam md. sanzid...
2 篇 aira kharvel par...
2 篇 nokshangthemba
2 篇 maheswara rao v ...
2 篇 lee tzong-ru

语言

1,292 篇 英文
32 篇 其他
11 篇 中文

检索条件"任意字段=Proceedings of the 2019 2nd International Conference on Signal Processing and Machine Learning"

共 1333 条记录，以下是181-190 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：

Commercial Clustering of Indian Bamboo Species Using machine learning Techniques 2

Commercial Clustering of Indian Bamboo Species Using Machine...

引用

2nd international conference on Paradigm Shifts in Communications Embedded Systems, machine learning and signal processing, PCEMS 2023

作者： Sawarkar, Ankush D. Shrimankar, Deepti D. Sahu, Santosh Kumar Singh, Lal Bokde, Neeraj Dhanraj Kumar, Manish Department of Computer Science and Engineering Maharashtra Nagpur440 010 India Shri Ramdeobaba College of Engineering and Management Department of Computer Science and Engineering Maharashtra Nagpur440 013 India National Environmental and Engineering Research Institute Environmental Biotechnology and Genomics Division Maharashtra Nagpur440 020 India Aarhus University Center for Quantitative Genetics and Genomics Aarhus Denmark Palermo University Engineering Department Viale delle Scienze Ed.8 Palermo90128 Italy

ISBN: (纸本)9798350310719

Bamboo is a grass that grows quickly (lm/days) and is very important to India's social, economic, and environmental growth. India has a big market for bamboo because of the gap between its imports (3,306 thousand $) and exports (607 thousand $) of its products. Clustering bamboo for business will be important in the near future since it can be used in over 1,000 ways and is worth USD 2.969 billion in trade. machine learning (ML) clustering models play a vital role in achieving this task for the commercial clustering of bamboo. In this research, we have presented details of twenty commercial species of bamboo in India has been identified, and data on the 2000 bamboo species have been collected. Although many algorithms have been introduced for clustering in recent years, not on bamboo, especially on morphological data. The target of this paper is to cluster these different bamboo species based on its commercial value using various ML algorithms such as K-means, Gaussian Mixture Models (GMM), and Balance Iterative Reducing and Clustering using Hierarchies (BIRCH). Clustering comes under unsupervised learning;there is no direct accuracy count. To evaluate the performance of clustering and determine which algorithm is best for clustering, we have used other indirect performance measures such as Silhouette Score, Calinski-Harabasz Index (CHI), and the Davies-Bouldin Index (DBI). K-mean shows the highest performance measures among all the other clustering ML models, with achieve a silhouette score of 0.5126, CHI of 17315 and DBI of 0.6633. © 2023 IEEE.

关键词： Bamboo

来源：评论

学校读者我要写书评

暂无评论

Advancements in fECG: Employing Adaptive Noise Cancellation Algorithms for signal Enhancement 2

Advancements in fECG: Employing Adaptive Noise Cancellation ...

引用

2nd international conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： Kiran, Ananya Sreevidya, M.S. Suprith Kumar, K.S. B.M.S College of Engineering Department of ECE Bangalore India

ISBN: (纸本)9798350367461

Monitoring the fetus during pregnancy is crucial for identifying factors that could adversely affect fetal health, preventing intrauterine deaths or causing permanent harm to the fetus. Diverse approaches including fetal electrocardiography (fECG), fetal phonocardiography (fPCG), fetal echocardiography (fECHO), fetal magnetocardiography (fMCG) and cardiotocography (CTG) utilizing Doppler ultrasound are utilized in the surveillance of fetal well-being. The fECG method has been employed for extracting fetal signals. However, proper signal processing is imperative during pregnancy due to contamination by maternal components and disturbances encompassing biological elements such as maternal and fetal movements, breathing, muscle activity, uterine contractions, and technical interferences like electrostatic potentials and network disruptions contribute to the overall noise. This study focuses on the technique of extracting fetal electrocardiogram (fECG) using Active Noise Cancellation (ANC). The application of destructive interference principles is used to isolate the fetal heart signal from surrounding maternal and environmental noise. An adaptive filter is designed using three prominent algorithms: the Gradient Descent method, the Least Mean Square (LMS) Algorithm, and the Normalized Least Mean Square (NLMS) algorithm. A MATLAB Graphical User Interface (GUI) is developed to implement these algorithms, allowing the variation of parameters such as filter length and learning rate for each algorithm. The GUI provides graphical visualization of the results, facilitating a comprehensive comparison of all three algorithms. The presented research contributes to enhancing the accuracy of fetal monitoring and signal extraction during pregnancy. © 2024 IEEE.

关键词： Graphical user interfaces

来源：评论

学校读者我要写书评

暂无评论

A Romanization Method for the Bengali Language with Efficient Encoding Scheme 2nd

A Romanization Method for the Bengali Language with Efficien...

引用

2nd international conference on Big Data, IoT and machine learning, BIM 2023

作者： Tipu, Amrita Das Fahad, Md. Mandal, Ashis Kumar Department of Computer Science and Engineering Hajee Mohammad Danesh Science and Technology University Dinajpur5200 Bangladesh

ISBN: (纸本)9789819989362

Transliteration is crucial in natural language processing as it enables the conversion between two languages while retaining their phonetic representation. The ability to transliterate the Bengali language is essential for cross-lingual communication. Most Bengali machine transliteration techniques rely on one-hot coding to numerically represent features, which is computationally intensive, requires significant memory, and results in lower accuracy in some cases. Addressing these limitations, we present an efficient feature representation method utilizing binary coding and compare it against the one-hot coding approach using two machine learning models: SVM and random forest. The proposed method is evaluated on the Dakshina dataset and the NEWS 2018 dataset for Bengali to English transliteration. The experimental results indicate that our approach outperforms the traditional methods while requiring significantly less memory and training time. Overall, the proposed method enables a better romanization of frequently used words. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： signal encoding

来源：评论

学校读者我要写书评

暂无评论

Research on Algorithms of Computer Image Intelligent Recognition and Deep learning 2

Research on Algorithms of Computer Image Intelligent Recogni...

引用

2nd international conference on signal Image processing and Communication, ICSIPC 2022

作者： Shao, Zheneenji Zhou, Jingxuan Sichuan University Chengdu China Dalian University of Technology Dalian China

ISBN: (纸本)9781510657694

In recent years, with the rapid development of science and technology in my country, people's requirements for computer information technology have become higher and higher. In order to better explore new things, engineers and technicians need to continuously optimize computer information processing systems to help people better solve practical problems. The article mainly analyzes the development process of computer intelligent image recognition algorithms, expounds the computer intelligent image recognition algorithm, and finally puts forward the technical application of computer intelligent image recognition algorithm, which provides a certain research foundation for related staff. © 2022 SPIE.

关键词： Image recognition

来源：评论

学校读者我要写书评

暂无评论

Prediction of Covid -19 using CXR Images in Transfer learning 2

Prediction of Covid -19 using CXR Images in Transfer Learnin...

引用

2nd international conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Pande, Soumitra Subodh Mahesh, C. Ananthnath, G.V.S. Jegajothi, B. Buvaneswari, B. Suganthi, D. Ericsson Global India Private Limited Bangalore India Saveetha Institute of Medical and Technical Sciences Department of Artificial Intelligence and Machine Learning Tamilnadu Chennai India Kmm Institute of Postgraduate Studies Ramireddipalli Department of Computer Science Tirupati517102 India Saveetha School of Engineering Department of Ece Chennai India Panimalar Engineering College Department of Information Technology Chennai India Saveetha College of Liberal Arts & Sciences Saveetha Institute of Medical & Technical Sciences Department of Computer Science Chennai602105 India

ISBN: (纸本)9798350325799

In 2019, the deadly COVID virus, which originated in Wuhan, China, spread throughout the entire world. It is considered to be one of the worst pandemics of this period. The epidemic had a significant influence on unemployment, and it may have even caused some fatalities. Its primary function is to assist in making judgements that are better, faster, and more trustworthy. The field of medicine is becoming an increasingly important one for the application of artificial intelligence and machine learning. This is particularly true for medical areas that make use of a wide variety of biomedical images, as well as diagnostic methods that rely on the collection and processing of a significant number of digital images. This study intended to find a way to detect anomalies in chest X-ray (CXR) images using only the most essential characteristics of deep learning. Earlier detection increases the likelihood of successful treatment;otherwise, the condition may even be fatal. This study will classify X-rays with a certain proportion of accuracy according to whether or not it is normal or abnormal. This will allow us to give the patient the appropriate treatment after viewing their X-ray. ResNet-101, DenseNet-169 and InceptionV3 are used to classify the CXR images. The ResNet-101 gives higher accuracy when compared with the other models. © 2023 IEEE.

关键词： Viruses

来源：评论

学校读者我要写书评

暂无评论

FPGA-based image signal processing CEPST module design 2

FPGA-based image signal processing CEPST module design

引用

2nd international conference on Frontiers of Applied Optics and Computer Engineering, AOCE 2025

作者： Tsai, Lifen Chen, Chinta Yang, Chihchung Tang, Lijie Wang, Xiahui Xue, Wuyang Ma, Huan Zhaoqing University Guangdong China Zhaoqing University Guangdong China

ISBN: (纸本)9781510689404

CEPST algorithm is an important step in image processing, which is widely used in computer vision, pattern recognition, and machine learning. In order to improve the efficiency and performance of CEPST algorithm, more and more studies have implemented the task of CEPST algorithm on FPGA boards in recent years. FPGA boards offer parallel computing capabilities, low power consumption, and low latency, making them suitable for high-performance computing and real-time applications. In this paper, the Vivado tool is used to implement the method of CEPST algorithm. Vivado has a complete toolchain and debugging environment, supports a variety of hardware description languages, and provides a rich set of IP cores and acceleration libraries to facilitate FPGA design and development. This paper details the steps of CEPST algorithm using Vivado, from algorithm design to simulation. The CEPST algorithm was designed to improve the accuracy and speed, and further improve the performance of the overall system. © The Authors.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Network Access Control In Space-Air-Ground Integrated Network Based On Reinforcement learning 2

Network Access Control In Space-Air-Ground Integrated Networ...

引用

2nd international conference on signal Image processing and Communication, ICSIPC 2022

作者： Qu, Hua Zou, MengYang Yuan, Xiaodong Zhao, Jihong Zhou, Feng School of Software Engineering Xi’an Jiaotong University Xi’an China School of Electronic and Information Engineering Xi’an Jiaotong University Xi’an China School of Communication and Information Engineering Xi’an University of Posts&Telecommunications Xi’an China

ISBN: (纸本)9781510657694

Space-Air-Ground Integrated network(SAGIN) is a heterogeneous network which combines ground network, air network and space *** SAGIN, a sub-network access algorithm based on reinforcement learning is proposed to make full use of multi-dimensional network resources, improve network delay and reduce packet loss *** algorithm learns from the environment iteratively and revises the model constantly, so as to make the optimal access choice. In the simulation experiment, the ASA-RL algorithm has obvious improvement over the comparison algorithm in terms of communication delay and packet loss rate. © 2022 SPIE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Customer Churn Prediction in Bank Based on Different machine learning Models 2

Customer Churn Prediction in Bank Based on Different Machine...

引用

2nd international signal processing, Communications and Engineering Management conference, ISPCEM 2022

作者： Li, Xiaofeng Chen, Zhongwei School of Information Engineering Guangxi University of Foreign Languages Guangxi Nanning530222 China

ISBN: (纸本)9781665492713

With the rise of internet finance, the competition in the banking industry has become increasingly fierce. Preventing the loss of customers and retaining old customers has become an important concern of major banks. Firstly, according to an existing open dataset, this paper makes a descriptive statistical analysis of each feature, and uses Logistic, Random Forest and Scv models to predict customer churn, such as AUC curves, Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Error (MSE). The better-performing models listed above are then chosen. Finally, Svm is selected as the best performance model, and according to descriptive statistics and feature importance, some suggestions are put forward for banks to retain customers. © 2022 IEEE.

关键词： Sales

来源：评论

学校读者我要写书评

暂无评论

Imbalanced Data Classification using Optimized Support Vector machine for IoMT Application 2

Imbalanced Data Classification using Optimized Support Vecto...

引用

2nd international conference on Ambient Intelligence in Health Care, ICAIHC 2023

作者： Pattanayak, Binod Kumar Mohanty, Mihir Narayan Satpathy, Smitarani Arjun Das, Jay Bijay Dept. of CSE ITER Odisha Bhubaneswar751030 India Advanced Signal Processing Lab ITER Odisha Bhubaneswar751030 India

ISBN: (纸本)9798350344882

In this digital age, most of the applications need to be Internet of Things based for easy access. Biomedical research has made significant growth related to it. The visual pathological information provides comparatively better information as compared to signals that help physicians with further analysis and suggestions. Medical data often exhibit class imbalance, where the number of samples in different classes is not proportional. This imbalance can pose significant challenges to traditional classification algorithms. This report explores the application of Support Vector machines (SVM) to imbalanced medical data classification, discussing the inherent issues, techniques for addressing class imbalance, and experimental results showcasing the effectiveness of SVM in handling imbalanced medical datasets. As a result, the retrieval process over the internet will be faster. In this paper, authors have considered three different cancerous image data of breast cancer, brain tumor, and liver cancer for analysis and detection using a machine learning approach. The data is collected from the UCI machine learning repository. The statistical features like class, radius, and area are considered and optimized using the Brain Storm Optimization algorithm for good accuracy. The optimized features are applied to the support vector machine classifier. Further, use for different kernels such as radial basis function (RBF), linear, polynomial, and sigmoid are used with SVM and verified for comparison. It is found that the RBF kernel provides SVM better accuracy as compared to other kernels. © 2023 IEEE.

关键词： Brain

来源：评论

学校读者我要写书评

暂无评论

Study on the Coupling Mechanism of Machining Process Parameters and Part Machining Accuracy Prediction in Intelligent Production Line 2

Study on the Coupling Mechanism of Machining Process Paramet...

引用

2nd IEEE international conference on Control, Electronics and Computer Technology, ICCECT 2024

作者： Duan, Hongjun Chen, Guorong Huang, Jiaming Yang, Junliang Wang, Bocheng School of Intelligent Technology and Engineering Chongqing University of Science and Technology Chongqing China

ISBN: (纸本)9798350380958

This paper studies part machining accuracy prediction. Firstly, the coupling mechanism of intelligent production line machining process parameters is studied, and a parameter coupling model based on correlation analysis is proposed, which can consider the interaction and influence between different parameters and optimize the machining process to a certain extent. Then, a machine learning-based part machining accuracy prediction method is proposed for the actual situation of intelligent production line machining. The method combines error network diagrams for multi-process machining units and enables the prediction of part machining accuracy by combining the production results of the previous process with the process parameters of the current process. Finally, the effectiveness and feasibility of the proposed parameter coupling model and accuracy prediction method are verified through experiments. The experimental results show that the proposed method can significantly improve the accuracy and stability of part machining, and also provide a certain theoretical and practical basis for the optimization of intelligent production lines. This study has important theoretical and practical significance for improving machining quality, reducing costs and improving enterprise competitiveness. © 2024 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134页 << < 15 16 17 18 19 20 21 22 23 24 > >>

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：