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

1,022 篇 会议
7 篇 期刊文献
5 册 图书

馆藏范围

1,034 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

795 篇 工学
- 710 篇 计算机科学与技术...
- 624 篇 软件工程
- 214 篇 生物工程
- 171 篇 信息与通信工程
- 122 篇 生物医学工程（可授...
- 85 篇 控制科学与工程
- 65 篇 光学工程
- 58 篇 机械工程
- 53 篇 化学工程与技术
- 47 篇 电气工程
- 37 篇 材料科学与工程（可...
- 26 篇 安全科学与工程
- 25 篇 电子科学与技术（可...
433 篇 理学
- 227 篇 生物学
- 205 篇 数学
- 98 篇 系统科学
- 79 篇 物理学
- 70 篇 统计学（可授理学、...
- 35 篇 化学
208 篇 管理学
- 131 篇 图书情报与档案管...
- 99 篇 管理科学与工程(可...
- 48 篇 工商管理
109 篇 医学
- 105 篇 临床医学
- 102 篇 基础医学(可授医学...
- 86 篇 药学(可授医学、理...
- 30 篇 公共卫生与预防医...
85 篇 教育学
- 84 篇 教育学
48 篇 法学
- 45 篇 社会学
26 篇 农学
- 24 篇 作物学
23 篇 经济学
- 23 篇 应用经济学
3 篇 军事学
2 篇 文学

主题

167 篇 machine learning
72 篇 deep learning
32 篇 support vector m...
32 篇 machine learning...
30 篇 education
28 篇 training
27 篇 students
24 篇 learning algorit...
21 篇 feature extracti...
21 篇 convolutional ne...
20 篇 computational mo...
18 篇 neural networks
18 篇 decision trees
17 篇 covid-19
17 篇 artificial intel...
17 篇 forecasting
16 篇 predictive model...
15 篇 learning systems
15 篇 data mining
15 篇 computer vision

机构

21 篇 department of co...
6 篇 department of co...
4 篇 nanchang vocatio...
3 篇 natural sciences...
3 篇 department of en...
3 篇 school of comput...
3 篇 daffodil interna...
3 篇 international sc...
3 篇 college of infor...
3 篇 school of inform...
3 篇 department of ma...
3 篇 computer and inf...
2 篇 beijing normal u...
2 篇 university of sc...
2 篇 college of compu...
2 篇 department of bu...
2 篇 wuxi institute o...
2 篇 graphic era univ...
2 篇 jinan university...
2 篇 college of compu...

作者

5 篇 pravin a.
4 篇 nagarajan g.
4 篇 prem jacob t.
3 篇 pereira ana i.
3 篇 zhang bo
3 篇 yan li
3 篇 bilgaiyan saurab...
3 篇 zolkin a.l.
3 篇 munister v.d.
3 篇 zhang xin
3 篇 yang jie
3 篇 wang lin
2 篇 gupta shagun
2 篇 dehuri satchidan...
2 篇 singh ashutosh k...
2 篇 lima jose
2 篇 mishra bhabani s...
2 篇 bhuiyan mohammad...
2 篇 zhang lei
2 篇 zhang song

语言

1,025 篇 英文
9 篇 其他
2 篇 中文

检索条件"任意字段=2021 2nd International Conference on Machine Learning and Computer Application, ICMLCA 2021"

共 1034 条记录，以下是31-40 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：

Research and application of heterogeneous data collection and analysis platform based on behavior simulation 2

Research and application of heterogeneous data collection an...

引用

2021 2nd international conference on machine learning and computer application, icmlca 2021

作者： Hao, Zhenliang Chang, ZhiJun Qi, Bolin Li, Xu Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Documentation and Information Center of Chinese Academy of Sciences Beijing China Beijing Zhongke Zhihe Digital Technology Co. Ltds Shenyang China

ISBN: (纸本)9783800757398

The competition for data resources has become an important part of the current market competition. The main sources of the college entrance examination data currently studied are third-party websites, or manually input data from the official website. Both of these methods have major shortcomings. First of all, in terms of accuracy and limitation, there is no guarantee that the data is accurate. Secondly, in the process of using data, it will be clamped by a third party, so we use behavior simulation technology to collect data from the official website, and then resolve the data by solving the heterogeneity problem. Finally, the completeness and accuracy of the college entrance examination data can be guaranteed through this system platform. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Websites

来源：评论

学校读者我要写书评

暂无评论

Deep learning for Neural Style Transfer 2

Deep Learning for Neural Style Transfer

引用

2021 2nd international conference on machine learning and computer application, icmlca 2021

作者： Duan, Jiahui Feng, Yajing Li, Zicheng Mo, Jianxing School of Computer Science University of Birmingham United Kingdom School of Information Shanxi University of Finance and Economics China Faculty of Engineering The University of Hong Kong Hong Kong Business College of Southwest University United States

ISBN: (纸本)9783800757398

The neural style transfer (NST) is an important task in the computer vision area. It aims to combine the content in an image with other images and generate an image with a specific style. This technique has been applied to many downstream image-related tasks and applications. Recently, the NST has made great progress with Convolution Neural Network (CNN), Generative Adversarial Network (GAN), and their variants. Thus, it is necessary to make a review of current work in NST. In this review, we firstly introduce the definition of NST and different types of NST algorithms. Then, we demonstrate some commonly used datasets and some indicators to evaluate the performance of different NST models. Finally, we analyze related work of NST and summarize some potential challenges and remained problems of state-of-the-art (SOTA) researches. This review will not only provide a good reference for researchers but also provide guidelines for some novices. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

MobileNet investigation: its application and reproducing edge detectors using depth-wise separable convolution 2

MobileNet investigation: its application and reproducing edg...

引用

2021 2nd international conference on machine learning and computer application, icmlca 2021

作者： Ai, Lun Luo, Zhen Wang, Chunyang Wu, Yifan International School Beijing University of Posts and Telecommunications Beijing Beijing100088 China Mathematics and The Information Science Department Henan University of Economics and Law Henan Zhengzhou450003 China College of Computer and Information Science College of Software Southwest University Chongqing Chongqing400700 China Information and Computing Science North China University of Science and Technology Hunan Changsha410219 China

ISBN: (纸本)9783800757398

MobileNet has a wide range of applications, and its depth-wise separable convolution deduced the computational cost dramatically compared to traditional convolution methods. In this study, experiments are carried out to examine depth-wise separable convolution's ability in terms of reproducing edge detector kernels. MobileNet's depth-wise separable convolution achieves great performance through reproducing kernels based on our LpP metric. The visualization results show that random initialization can reduce the calculation amount of the model and have higher efficiency. This study also compares three models, including InceptionV3, ResNet50, and MobileNetV2, on face mask detection tasks. The experiment result indicates that the MobileNetV2 model achieved the highest accuracy of 99.08%. A ground truth analysis on a test image containing three different face mask situations is performed to further discuss the model performance of MobileNetV2. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Deep learning techniques for Sarcasm Detection 2

Deep Learning techniques for Sarcasm Detection

引用

2021 2nd international conference on machine learning and computer application, icmlca 2021

作者： Liu, Xuanning EE Department University of Liverpool LiverpoolL3 8LG United Kingdom

ISBN: (纸本)9783800757398

Sarcasm is a literary technique used to expose the shortcomings or contradictions of the object. It frequently appears on various online platforms (e.g., Twitter and Facebook), expressing the subjective views and opinions of the sender of the behavior. Sarcasm detection is very beneficial to various online platforms, which help realize sentiment analysis, opinion mining and advertisement push. Therefore, the research on sarcasm detection has reached a peak contemporarily. With the development of deep learning and the successful application of network platforms in natural language processing, in recent years, some studies have applied deep learning to address sarcasm detection tasks. These studies put forward new models based on techniques (e.g., convolutional neural networks and Transformers), which were tested by a large number of experiments to explore the performance of the models. The model proposed by the research is compared with the classic model and continuously improved. This paper reviews some previous work based on convolutional neural networks, transformers and other networks, lists important factors (e.g., data sets and matrices), introduces some research frameworks and solutions, and gives an evaluation of classification model index. The work done in this article will provide a good reference for later researchers. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

How to Use machine learning to Find Alpha in Stock Market 2

How to Use Machine Learning to Find Alpha in Stock Market

引用

2021 2nd international conference on machine learning and computer application, icmlca 2021

作者： Sang, Biying University of Edinburgh EdinburghEH3 9BB United Kingdom

ISBN: (纸本)9783800757398

Nowadays, the selection range of alpha factors is gradually narrowing and its excess return alpha is also declining. Fortunately, for the above problems, machine learning (especially deep learning) shows many advantages. These excellent characteristics make machine learning likely to become the most important tool to obtain excess returns in the future. In this article, three machine learning algorithms, support vector machine, adaptive boosting and neural network, are discussed. The other various algorithms are derived and evolved on the basis of these three algorithms. The three machine learning algorithms are summarized and analyzed according to the derivation law of machine learning algorithms. Based on the original linear simple algorithm, support vector machine forecasts data by adding different dimensions, but its learning ability and sample complexity are complementary, so its accuracy will be reduced in the case of sample complexity. Adaptive boost (adaptive boosting) is evolved from the decision tree, which is more inclined to the improvement of learning ability. That is, it improves the accuracy of prediction, but its ability to solve complex samples is limited. Neural network simulates human neuron construction. It can not only solve a large number of complex sample data, but also has high learning ability, which solves the defects of support vector machine and Adaptive boost. By summarizing the representative algorithms in different evolution stages of machine learning algorithms, neural network can predict the performance of stocks well and find more accurate alpha factors, which have greater development prospects and application space in the growing stock market. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Multi-stage Multi-task learning and Attention Module for Multi-choice Reading Comprehension 2

Multi-stage Multi-task Learning and Attention Module for Mul...

引用

2021 2nd international conference on machine learning and computer application, icmlca 2021

作者： Liu, Jiawen Binren, Xie School of Public Administration Northwest University Shanxi Xi'an710127 China Faculty of Science Xi'an University of Technology Shanxi Xi'an710127 China

ISBN: (纸本)9783800757398

Multi-choice machine Reading Comprehension (MRC) requires model to decide the correct answer from a set of answer options when given a passage and a question. MRC is one of the most difficult tasks in Reading Comprehension because it often requires more advanced reading comprehension skills such as logical reasoning, summarization, and arithmetic operations, compared to the extractive counterpart where answers are usually spans of text within given passages. Moreover, in addition to a powerful Pre-trained Language Model (PrLM) as encoder, multi-choice MRC especially relies on a matching network design which is supposed to got the relationships among the attributes of passage, question and answers. We introduce the new method, a Multistage Multi-task learning framework for multi-choice MRCOur method consists of two stages: Firstly, We Multi-task learning framework to train extra datasets, its coarse-tuning stage. Secondly, We using the first part of the model continue trained for better with limited data. Furthermore, we propose a new the head module for MRC, it is the multi-head self-attention framework. We tested our method on two complex datasets as Dreams and RACE. Our model can boost the model to make promising progress compared to the baseline. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： learning systems

来源：评论

学校读者我要写书评

暂无评论

Design and application of Autonomous Driving System based on Multi-sensor Fusion 2

Design and Application of Autonomous Driving System based on...

引用

2021 2nd international conference on machine learning and computer application, icmlca 2021

作者： Xie, JingWei Li, Dan School of Innovation and Entrepreneurship of Dalian University Dalian China Electrical and Electronic Teaching and Research Section of Dalian Development Zone Vocational Secondary School Dalian China

ISBN: (纸本)9783800757398

A method of multi-sensor data fusion using deep learning is proposed for the autonomous driving system. First, the real-time road condition information is collected through the binocular camera mounted on the car model, and the road and the obstacles on the road are identified with the semantic segmentation of the deep neural network image. At the same time, supplemented with other information collected by the laser sensor and ultrasonic sensor on the car model, as well as the road information obtained by Beidou navigation, the Kalman filter parameters are optimized with deep learning and passed via algorithm fusion to the car model actuator for automatic operation. The signals collected by multiple groups of the same type of sensors on the car model are optimized by an improved Kalman filter algorithm to achieve fast and accurate output of real-time results. The actual vehicle experiment results of the smart car model show that the solution can realize tasks such as autonomous navigation and driving, automatic obstacle avoidance, automatic route planning and prediction in a variety of complex road environments, with an operating speed equivalent to 80 km/h and a safety rate of 99.8%. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Roads and streets

来源：评论

学校读者我要写书评

暂无评论

A Review of Deep learning Techniques for Fake News Detection 2

A Review of Deep Learning Techniques for Fake News Detection

引用

2021 2nd international conference on machine learning and computer application, icmlca 2021

作者： Lin, Yufan Shan, Zijian Zou, Siwei CAS Boston University BostonMA02215 United States School of Computer Science China University of Geosciences Hubei Wuhan430030 China School of Economics Management Dalian University of Technology Liaoning Dalian116086 China

ISBN: (纸本)9783800757398

Fake news, as a kind of public information, releases false information to deceive people for a specific purpose. Fake news not only causes serious damage to the credibility of the public media but also damages the rights of the parties. So, it is necessary to detect fake news from both online social media and traditional media. For decades, different approaches for fake news detection have been proposed. And these methods can be categorized into manual detection and automatic detection. In this paper, we make a comprehensive review of automatic fake news detection. We first introduce the definition of fake news and fake news detection. Then, some commonly used datasets and evaluation metrics are demonstrated. Besides, we also revise some deep learning approaches for automatic fake news detection. Finally, we discuss some potential challenges and problems for the future. The survey provides a good introduction to fake news detection for both NLP researchers and social media scientists. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

Lower Limb Rehabilitation Motion Angle Measurement Based On Deep learning YOLOv3 Model 2

Lower Limb Rehabilitation Motion Angle Measurement Based On ...

引用

2021 2nd international conference on machine learning and computer application, icmlca 2021

作者： Yang, Yunlong Wang, Liancheng Yao, Yufeng He, Chenxi Yin, Hesheng Weihai Furui Robotics Co. Ltd Weihai China Tianzhi Institute of Innovation and Technology Weihai Economic and Technological Development Zone Weihai China Weihai China State Key Laboratory of Robotics Harbin Institute of Technology System Department of Mechanical Engineering Harbin China

ISBN: (纸本)9783800757398

The aging of the population and the high incidence of hemiplegia have led to an increasing demand for easy-to-use rehabilitation training. The feedback sensing system which can measure and analyze the lower limb rehabilitation motions is highly significant for improving the rehabilitation outcome. computer vision-based human motion angle measurement has attracted significant interest. This study aims to measure and analyze the lower limb motion angle in the sagittal plane with a single RGB camera. This paper proposes a method for extracting and monitoring of the lower limb marker points based on YOLOv3 and DarkNet-53 convolutional neural networks, and optimizes the pixel coordinates of the target point based on Kalman. The measurement accuracy of the proposed method is tested by JACO robotic arm, and the test shows that the standard deviation (SD) of the measurement is less than 0.5°. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

machine learning-Based Experimental Design in Chemical Industry: Taking C4 Olefin Preparation from Ethanol as an Example 2

Machine Learning-Based Experimental Design in Chemical Indus...

引用

2021 2nd international conference on machine learning and computer application, icmlca 2021

作者： Wei, Qianqian Pan, Yating School of Statistics and Mathematics Yunnan University of Finance and Economics Kunming China

ISBN: (纸本)9783800757398

With the acceleration of global carbon-neutralizing process, green chemical industry has attracted more and more attention. Finding appropriate parameters for experiments is important for green chemical reaction. This work focuses on using experiment parameters to predict chemical reaction yield of products based on machine learning methods, which takes C4 olefin preparation from ethanol as an example. To explore how experiment parameters influence the reaction yield of products, figures are plotted to show the correlations between parameters and reaction index. Then the conversion models and selectivity models are constructed based on polynomial regression, decision tree, random forest, Light GBM and neural networks. Different evaluations of the models all indicate that LightGBM performs best to predict the conversion of ethanol, while the selectivity of C4 olefin prefers neural network. Comprehensively we propose a hybrid method to predict yield of C4 olefin which significantly exceeded all single regression models. Furthermore, the sensitivity of optimized conversion/selectivity/yield models are shown in heatmaps that imply the robustness of our models. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Chemical industry

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104页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：