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

1,856 篇 会议
6 册 图书
1 篇 期刊文献

馆藏范围

1,863 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,364 篇 工学
- 1,248 篇 计算机科学与技术...
- 997 篇 软件工程
- 318 篇 生物工程
- 309 篇 信息与通信工程
- 189 篇 生物医学工程（可授...
- 160 篇 控制科学与工程
- 124 篇 电气工程
- 118 篇 光学工程
- 83 篇 机械工程
- 74 篇 化学工程与技术
- 64 篇 安全科学与工程
- 62 篇 网络空间安全
- 53 篇 电子科学与技术（可...
- 48 篇 仪器科学与技术
747 篇 理学
- 390 篇 数学
- 326 篇 生物学
- 166 篇 统计学（可授理学、...
- 150 篇 物理学
- 134 篇 系统科学
- 83 篇 化学
440 篇 管理学
- 250 篇 管理科学与工程(可...
- 224 篇 图书情报与档案管...
- 128 篇 工商管理
174 篇 医学
- 165 篇 临床医学
- 158 篇 基础医学(可授医学...
- 117 篇 药学(可授医学、理...
- 62 篇 公共卫生与预防医...
78 篇 教育学
- 78 篇 教育学
75 篇 法学
- 68 篇 社会学
50 篇 农学
- 49 篇 作物学
45 篇 经济学
4 篇 军事学

主题

326 篇 machine learning
128 篇 deep learning
77 篇 support vector m...
66 篇 machine learning...
55 篇 forecasting
46 篇 feature extracti...
37 篇 decision trees
36 篇 accuracy
35 篇 computational mo...
34 篇 computer vision
31 篇 predictive model...
30 篇 training
28 篇 data mining
28 篇 students
28 篇 convolutional ne...
26 篇 neural networks
22 篇 object detection
22 篇 artificial intel...
21 篇 sentiment analys...
20 篇 internet of thin...

机构

12 篇 chitkara univers...
7 篇 shenyang ligong ...
6 篇 uttaranchal inst...
5 篇 department of co...
5 篇 maharishi school...
5 篇 alibaba cloud bi...
4 篇 school of comput...
4 篇 college of compu...
4 篇 key laboratory o...
4 篇 lovely professio...
4 篇 jilin agricultur...
4 篇 uttaranchal univ...
4 篇 key laboratory o...
4 篇 department of co...
4 篇 master of comput...
4 篇 school of inform...
3 篇 school of comput...
3 篇 vivekananda glob...
3 篇 department of el...
3 篇 college of compu...

作者

4 篇 liu gang
4 篇 kumar rakesh
4 篇 waseemullah
4 篇 liu peng
3 篇 zhang tao
3 篇 kumar ajay
3 篇 rakesh kumar
3 篇 babu tina
3 篇 siddhant
3 篇 sharma arun
3 篇 faisal rehman
3 篇 wang xiaofei
3 篇 sharif hanan
3 篇 singh sunil kuma...
3 篇 rehman faisal
3 篇 tina babu
3 篇 yang wei
3 篇 sharma avinash
3 篇 prajwal
3 篇 vinay kukreja

语言

1,803 篇 英文
58 篇 其他
16 篇 中文

检索条件"任意字段=3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022"

共 1863 条记录，以下是341-350 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：

Benchmarking AutoML-Supported Lead Time Prediction 3

Benchmarking AutoML-Supported Lead Time Prediction

引用

3rd international conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Bender, Janek Trat, Martin Ovtcharova, Jivka FZI Res Ctr Informat Technol Haid & Neu Str 10-14 D-76135 Karlsruhe Germany

In manufacturing companies, especially in small and medium enterprises (SME) in the make-to-order domain, predicting accurate lead times for highly customisable products poses a challenge. One avenue to tackle this challenge is using machine learning to create data-driven models. With the advent of Automated machine learning (AutoML), there is a potential also for non-data-scientists in the SMEs to utilise machine learning in a self-sufficient manner In this paper, we benchmarked three AutoML solutions on data from two SMEs and compared their models with manual predictions currently in productive use as well as simple mean models. We furthermore investigated how these solutions support the model development process. While we found that the models generated by the AutoML solutions outperformed manual predictions, labour-intensive parts of the model development process such as data understanding and pre-processing as well as feature engineering were not supported sufficiently by the benchmarked solutions. (C) 2022 The Authors. Published by Elsevier B.V.

关键词： AutoML production data-driven analytics machine learning lead time prediction

来源：评论

学校读者我要写书评

暂无评论

Prediction on basketball team-rankings in CBA using past stats with weighted linear regression 3

Prediction on basketball team-rankings in CBA using past sta...

引用

3rd international conference on Electronic Information Engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Zhang, Xiwen Lee, Juiwei Yu, Yuanzheng Lu, Chenglin Nanjing Foreign Language School Nanjing210008 China Shenzhen College of International Edcuation Shenzhen518017 China Hamden Hall Country Day School HamdenCT06517 United States Wuhan Britain-China School Wuhan430022 China

ISBN: (纸本)9781510680449

This study examines the application of weighted linear regression in predicting the team standings in Chinese Basketball Association (CBA) at the end of a regular season. Using historical game stats from 2017-2022 as training set, a linear regression model has been developed to predict the outcomes of CBA regular season based on the average performance of each team, which includes 20 features in the box score. The result of the analysis indicates that the weighted linear regression model is capable of make predictions of the team rankings with an accuracy of 61.4%. While key features like points/rebounds/assists per game got considered with different positive weights, unfavorable features like turnovers and personal fouls are considered to have negative weights. The findings of this research have practical implications for CBA and other sports leagues that aren't as well studied as the NBA. The predictions of league rankings indicate the winning probability and strength of the teams, which could be referenced by fans, coaches, team officials, and even gamblers. Furthermore, the methodology discussed in this paper can be extended to other statistically recorded sports and other sports with stats records and other domains where predictive modeling is possible. Overall, the effectiveness of weighted linear regression model in predicting the outcomes of games in unpopular basketball leagues like CBA has been proved valid through this research;and the unlimited potential of machine learning in the real world has been underlined. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

Parameter selection and application on the smoothly clipped absolute deviation method 3

Parameter selection and application on the smoothly clipped ...

引用

3rd international conference on computer Vision, Image and Deep learning and international conference on computer Engineering and applications, CVIDL and ICCEA 2022

作者： Yang, Qiqiang Zi, Xuemin Tianjin University of Technology and Education School of Science Hexi District Tianjin China

ISBN: (纸本)9781665459112

With the development of science and technology, high-dimensional data has become a popular topic in scientific research. However, most variables are meaningless in high-dimensional data. Therefore, the sparsity problem in high-dimensional data is worth to be focus in the statistical methodology and application in decades. Smoothly clipped absolute deviation (SCAD) method is often used to solve the problem of high-dimensional variable selection. The selection of regular parameters is obtained by generalized cross-validation, and the coordinate descent algorithm is often used to estimate the model coefficients in the past. In this paper, AIC and BIC are used to find the optimal regularization parameters, and the path calibration sparse shooting algorithm is used to estimate the model coefficients. Our algorithm has a strong guarantee in theory. We can achieve global linear convergence to the only sparse local optimal, and the convergence speed is fast. It is found that residual sum of squares of model obtained by path calibration sparse shooting algorithm combined with BIC, which is the smallest in solving SCAD problem by numerical experiments. © 2022 IEEE.

关键词： Calibration

来源：评论

学校读者我要写书评

暂无评论

machine learning-based Study of the Influence Factors on the Wins of NBA Teams 3

Machine Learning-based Study of the Influence Factors on the...

引用

3rd international conference on Intelligent Computing and Human-computer Interaction, ICHCI 2022

作者： Su, Kaihang School of Information Guangdong University of Finance & Economics No.21 Chisha Road Haizhu District Guangzhou510220 China

ISBN: (纸本)9781510661301

This paper is a sample of machine learning algorithms applied to analyse how different factors affect the game's result among all National Basketball Association teams. To achieve the study's objectives, this paper selects cluster analysis methods in supervised and unsupervised learning, such as the support vector machines, the nearest-neighbour classification, and the k-means algorithm to build the model. The first step is to classify the training and test sets, to calculate the accuracy and thus obtain the most efficient method of distinguishing between strong and weak teams, and subsequently to visualize the results by downscaling the influencing factors to find the main influence factors that differentiate between strong and weak teams. Finally, the cluster analysis led to the conclusion that the degree to which a team's playing style fits the league's seasonal rules and the values of the variables of the basic data is not directly related to the team's win rate. © 2023 SPIE.

关键词： Cluster analysis

来源：评论

学校读者我要写书评

暂无评论

application of E-Healthcare Based on machine learning in an Internet of Things Ecosystem 3

Application of E-Healthcare Based on Machine Learning in an ...

引用

3rd international conference on Innovative Sustainable Computational Technologies, CISCT 2023

作者： Pattnayak, Parthasarathi Patnaik, Sanghamitra Mohanty, Arpeeta Das, Tulip School of Computer Applications KIIT Deemed to Be University Bhubaneswar India School of Law KIIT Deemed to Be University Bhubaneswar India SRI SRI University Faculty of Emerging Technologies Cuttack India

ISBN: (纸本)9798350303360

Particularly in the biology and healthcare industries, advancements in technology have made it possible to collect enormous amounts of data. The obtained data is typically of an unstructured kind and can be presented in several ways, including visually, audibly, textually, etc. Technology breakthroughs, fitness bands, sensors, smart devices, even healthcare apps all have a significant impact on the healthcare industry. These innovations have brought medical care to a new level. As a result, everyone is worried about their current health and possible outcomes. Effective evaluation of clinical records and healthcare services is thus the most crucial component of the healthcare sector. By using machine learning, judgements can be made accurately and diseases can be identified earlier. Additionally, the quick and precise diagnosis of diseases is the main goal of this effort. The ischemic stroke dataset is examined in this work to enable quicker and more accurate diagnosis. There have been several ML algorithms documented from the literature, however reliability is the main issue, especially for healthcare datasets. © 2023 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Poet Attribution of Urdu Ghazals using Deep learning 3

Poet Attribution of Urdu Ghazals using Deep Learning

引用

3rd IEEE international conference on Artificial Intelligence, ICAI 2023

作者： Siddiqui, Iqra Rubab, Fizza Siddiqui, Haania Samad, Abdul Habib University Computer Science Karachi Pakistan

ISBN: (纸本)9798350322125

Poet attribution focuses on determining ownership of a piece of poetry by insights obtained from analyzing his existing poetry. Its significance is immense including in detection of plagiarism and characterization of poetry of a poet. Urdu, Pakistan's lingua franca with the richest poetic tradition, has been a subject of misinformation and misattribution. This paper presents a novel approach to poet attribution in Urdu Ghazals through the application of machine and deep learning models. Our aim is to establish an accurate and comprehensive characterization of ghazals that captures the unique writing style of each poet. To achieve this, we trained and tested a range of machine learning, deep learning, and transformer-based classification models on a dataset containing 17,609 couplets of 15 notable ghazal poets. We used classifiers such as SVM and logistic regression to obtain preliminary results, achieving an accuracy of 64% with SVM. However, to achieve even better results, we employed deep learning models such as MLP, CNNs, and GRUs, with LSTMs resulting in the highest accuracy of 59.96%. We then used transformer-based models, including roBERTa and BERT, which achieved an outstanding accuracy of approximately 80% in classifying 15 poets. This work represents a significant contribution to the field of computational poetry analysis, as it is the first to explore poet attribution in Urdu Ghazals using deep learning and transformer-based models. Our analytical approach enables us to examine and analyze each model's capabilities in capturing the writing style of Urdu Ghazal poets, leading to a more comprehensive and accurate characterization of these works. © 2023 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Enhancing Convolutional Models for Indoor Radio Mapping via Ray Marching

Enhancing Convolutional Models for Indoor Radio Mapping via ...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Wu, Mengfan Skocaj, Marco Boban, Mate Munich Research Center Huawei Technologies Germany School of Electrical Engineering and Computer Science TU Berlin Germany

ISBN: (纸本)9798350368741

In this paper, we present an enhanced convolutional model for indoor radio map generation, focusing on the integration of a novel ray-marching feature. We describe our machine learning pipeline developed for the ICASSP 2025 Signal Processing Grand Challenge, specifically the First Indoor Pathloss Radio Map Prediction Challenge. Our method incorporates a ray-marching feature that, combined with a UNet architecture enhanced by dilated convolution layers, significantly improves indoor pathloss prediction accuracy. Our approach achieved a 3rd-place ranking in the challenge with a weighted RMSE of 10.33 on the test dataset. © 2025 IEEE.

关键词： feature engineering machine learning radio maps Wireless communications

来源：评论

学校读者我要写书评

暂无评论

NeuroPCA: Enhancing Alzheimer's disorder Disease Detection through Optimized Feature Reduction and machine learning 3

NeuroPCA: Enhancing Alzheimer's disorder Disease Detection t...

引用

3rd international conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2024

作者： Sagili, Sreenivas Reddy Chidambaranathan, Senthilnathan Nallametti, Nagarjuna Bodele, Harana M. Raja, Laxmi Gayathri, P.G. Rochester Institute of Technology Department of Computer Science United States Virtusa Corporation 20 Corporate Pl South Piscataway United States Cvr College of Engineering Department of Csit Telangana Hyderabad India J D College of Engineering & Management Department of Electronics and Telecommunications Nagpur India Coimbatore India Kongunadu College of Engineering and Technology Department of Artificial Intelligence and Data Science India

ISBN: (纸本)9798350369083

Alzheimer's (memory loss disorder) disorder Disease (AD) poses a significant diagnostic challenge due to its complex etiology and subtle onset of clinical symptoms. The Early and accurate detection will be a crucial for effective management and intervention. The integration of machine learning-Driven (ML) techniques based on neuro imaging and clinical data may offers a promising avenue for enhancing of AD detection. However, the highest dimensionality of such data could be impede the efficacy and accuracy of ML models due to curse of dimensionality and over fitting. This research will introduces the "NeuroPCA System,"a novelist diagnostic framework by employing Principal Components based Analysis (PCA) for features reduction, tailored specifically for Alzheimer's (memory loss disorder) disorder Disease detection. The NeuroPCA System will systematically reduces the dimensionality of input health data (e.g., MRI, PET scans, and genetic information) while by preserving the most informative variance components crucial for distinguish between AD patients and healthy controls. The proposed methodology may encompasses preprocessing of the multi-modal dataset to normalized feature scales, followed by the application of PCA to extracts the principal components that capturing of the maximum variance in the dataset. The reduced feature set will then utilized to train and validate a suite of machine learning-Driven models like Supportive Vector machines (SVM) for classify subjects into AD and non-AD groups. The effectiveness of the NeuroPCA System may evaluated depends on classification accuracy, sensitivity, specificity, and computational efficiency, by using a cross- validated dataset of diagnosed AD patients and a control group. The NeuroPCA System also demonstrates a significant improvement in model performance and computational efficiency, by highlighting the potential of PCA for feature reduction in the context of Alzheimer's (memory loss disorder) disorder Disease detect

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

3rd international conference on Smart Electronics and Communication, ICOSEC 2022 - Proceedings

3rd International Conference on Smart Electronics and Commun...

引用

3rd international conference on Smart Electronics and Communication, ICOSEC 2022

ISBN: (纸本)9781665497640

The proceedings contain 294 papers. The topics discussed include: cooperative spectrum sensing with hard decision fusion based on modified correlation detection scheme in additive Laplacian noise;Archimedes spiral antenna for the microwave hyperthermia application;research on inter-symbol interference suppression technology and fusion algorithm of optical communication system;marketing data collection and chaotic clustering based on the computer network era;PHP implementation of a comprehensive evaluation platform for innovative talent training quality based on internet data clustering and integration;multi-bit collection and hierarchical classification algorithm of computer application fundamentals based teaching data under the background of hybrid clustering algorithm;centralized analysis algorithm of multi-dimensional traditional data for smart new computer network course platform;pomegranate leaf disease classification using feature extraction and machine learning;a study of cloud-based VPN establishment using network function virtualization technique;and analysis of the application of user experience and interactive intelligent data protocol in industrial design under the Internet + mode.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Advanced Camouflage Robot for Military Spying applications using Sensor Fusion and machine learning 3

Advanced Camouflage Robot for Military Spying Applications u...

引用

3rd IEEE international conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Kulkarni, Neeraj P Khan, Subim N. Rathod, Rahul Ramkishan Choure, Ajay Raosaheb Chinchole, Mahesh Gokul Jspm Rajarshi Shahu College of Engineering Tathawade Pune India Soet D Y Patil University Ambi Pune India Bhivarabai Sawant Institute Of Technology And Research E&tc Department Wagholi Pune India Nutan Maharashtra Institute of Engineering and Technology E&tc Department Pune India

ISBN: (纸本)9798350354348

The current defense application scenario. the ability to blend into the environment is crucial for reducing detection and enhancing operational efficiency. This paper presents the development of an advanced camouflage robot to dynamically adapt its color to match its surroundings. The proposed system utilizes a combination of machine learning, computer vision, and sensor fusion to achieve camouflaging using the RGB LED panels mounted on the robot to adapt to the color of the surroundings. The robot is equipped with a video camera system that captures real-time video feed of the environment. The captured video is then processed by a trained machine learning model, which analyzes the color distribution in the surroundings. Simultaneously, the robot uses RGB color sensors to accurately detect the colors present in its immediate vicinity. The data from both the camera and the sensors are integrated to determine the predominant color around the robot. The hybrid camouflaging approach involves feeding the combined data into the machine learning model, which then calculates the color of maximum distribution. The robot then activates its RGB panels, adjusting their color to blend with the identified predominant color in the environment thereby making it difficult to locate. This process allows the robot to effectively camouflage itself, minimizing its visual footprint. KNN and sensor fusion techniques are used to achieve this task. © 2024 IEEE.

关键词： Nearest neighbor search

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187页 << < 31 32 33 34 35 36 37 38 39 40 > >>

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：