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

1,327 篇 会议
11 篇 期刊文献
9 册 图书

馆藏范围

1,347 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

915 篇 工学
- 757 篇 计算机科学与技术...
- 498 篇 软件工程
- 303 篇 信息与通信工程
- 204 篇 电气工程
- 175 篇 生物工程
- 127 篇 生物医学工程（可授...
- 107 篇 光学工程
- 90 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
- 48 篇 机械工程
- 35 篇 化学工程与技术
- 28 篇 安全科学与工程
- 26 篇 交通运输工程
425 篇 理学
- 189 篇 生物学
- 187 篇 数学
- 151 篇 物理学
- 76 篇 统计学（可授理学、...
- 54 篇 系统科学
- 40 篇 化学
169 篇 管理学
- 106 篇 图书情报与档案管...
- 72 篇 管理科学与工程(可...
- 40 篇 工商管理
146 篇 医学
- 130 篇 临床医学
- 88 篇 基础医学(可授医学...
- 65 篇 药学(可授医学、理...
- 24 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
18 篇 经济学
- 17 篇 应用经济学
16 篇 农学
5 篇 军事学
1 篇 文学
1 篇 历史学

主题

210 篇 machine learning
134 篇 deep learning
78 篇 signal processin...
71 篇 accuracy
70 篇 feature extracti...
68 篇 signal processin...
61 篇 support vector m...
56 篇 machine learning...
45 篇 predictive model...
33 篇 neural networks
32 篇 convolutional ne...
31 篇 random forests
29 篇 computational mo...
29 篇 training
26 篇 natural language...
25 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 chitkara univers...
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 chitkara univers...
4 篇 sri lanka instit...
4 篇 advanced telecom...
4 篇 shenyang ligong ...
4 篇 graduate school ...
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

1,271 篇 英文
67 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 1347 条记录，以下是811-820 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：

Pose Comparison Based on Part Affinity Fields 2

Pose Comparison Based on Part Affinity Fields

引用

2nd IEEE international conference on Information Communication and signal processing (ICICSP)

作者： Zhou, Chujin Li, Weilong Guangxi Univ Sci & Technol Sch Int Educ Liu Zhou 545006 Guangxi Peoples R China Guangxi Univ Sci & Technol Sch Comp Sci & Commun Engn Liu Zhou 545006 Guangxi Peoples R China

ISBN: (纸本)9781728151021

Inspired by the massive demand for pose-comparison technology in today's society especially athletes and police;A real-time human body pose comparison method based on part affinity fields neural network is proposed. The neural network is used to extract the feature map. The CNN network and the L2 loss calculation are used to extract the detected confidence map and the part affinity field. The maximum weight bipartite graph is used to calculate the optimal connection between the limb parts. The example shows that the method can extract the angles of various parts of the human body more accurately as the reference basis for the pose comparison.

关键词： pose estimation deep learning part affinity field pose comparison

来源：评论

学校读者我要写书评

暂无评论

Research on Autonomous Driving Perception based on Deep learning Algorithm 2

Research on Autonomous Driving Perception based on Deep Lear...

引用

2nd international conference on Image and Video processing, and Artificial Intelligence (IPVAI)

作者： Zhou, Bolin Zheng, Jihu Chen, Chen Yin, Pei Zhai, Yang China Automot Technol & Res Ctr Co Ltd Automot Data Ctr Tianjin 300393 Peoples R China Changan Univ Sch Automobile Xian 710000 Shanxi Peoples R China

ISBN: (数字)9781510634107

ISBN: (纸本)9781510634107

Multiple source sensor fusion is the foundation of motion planning for autonomous driving system, which is the crucial part in improving the performances for unmanned operational system. In this article, based on the deep learning platform CATARC constructed, applied with Udacity's Lincoln MKZ multiple sensor data, implemented with Robotic Operation System, Computer Vision, PointCloud Library, Deep Neural Networks and Extended Kalman Filter, constructed a low-cost object pose estimation data fusion solution, aiming at technic support for the industrialization of autonomous driving technologies.

关键词： Perception Technology Deep learning Image Recognition Point Cloud Recognition Fusion Filtering

来源：评论

学校读者我要写书评

暂无评论

Adaptive waveform selection algorithm based on reinforcement learning for cognitive radar 2

Adaptive waveform selection algorithm based on reinforcement...

引用

2nd IEEE international conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019

作者： Cao, Xin Zheng, Zhe An, Di Unit 91404 of the PLA Qinhuangdao China School of Information and Electronic Beijing Institute of Technology Beijing China

ISBN: (纸本)9781728150291

Cognitive radar is a newly emerging intelligent radar that can adaptively change the transmitted signal waveform according to changes in the target and environment to improve the accuracy of target state estimation. In this paper, the running process of cognitive radar adaptive transmission is analyzed, the tracking waveform parameter selection is correlated with the target state estimation and the reinforcement learning model is established. The problem of unknown target state space is solved by the 'prioritized sweeping' method and the computational efficiency is improved by replacing 'eligibility trace'. The simulation results show that the indirect reinforcement learning method is better than the fixed waveform and the waveform selection algorithm based on the minimum mean square error for the tracking accuracy and state estimation error of the target. © 2019 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Self-Guided Hash Coding for Large-Scale Person Re-Identification 2

Self-Guided Hash Coding for Large-Scale Person Re-Identifica...

引用

2nd IEEE international conference on Multimedia Information processing and Retrieval (MIPR)

作者： Liu, Xiaobin Zhang, Shiliang Yang, Ming Peking Univ Beijing Peoples R China Horizon Robot Inc Beijing Peoples R China

ISBN: (纸本)9781728111988

The laborious manual person ID annotation results in limited training data and increased difficulty in learning discriminative representations. Meanwhile, high dimensional deep features are not ready for fast indexing and matching. Those challenges hinder the application of person Re-Identification (ReID) in large-scale data. To conquer those challenges, we propose a novel training strategy to learn compact binary hash codes. To facilitate feature learning, person images are decomposed into body parts, which are then composed across images into new positive and negative training samples. Binary code quality restrictions are also applied the during training procedure. Requiring no extra annotation costs, our algorithm iteratively generates hard training samples by itself and makes discriminative hash code learning with a limited number of labeled data possible. We hence use "self-guided" to describe this training procedure. Extensive experiments are conducted on two large-scale person ReID datasets, i.e., Market1501 and MSMT17 with distractors, showing our method is competitive compared with recent works.

关键词： Training Neurons Quantization (signal) Correlation Training data Entropy Binary codes

来源：评论

学校读者我要写书评

暂无评论

Advanced vibration signal processing using edge computing to monitor wind turbine drivetrains 2

引用

ASME 2019 2nd international Offshore Wind Technical conference, IOWTC 2019

作者： Peeters, Cédric Verstraeten, Timothy Nowé, Ann Daems, Pieter-Jan Helsen, Jan Acoustics and Vibrations Research Group Department of Applied Mechanics Vrije Universiteit Brussel Pleinlaan 2 Brussels1050 Belgium Artificial Intelligence Lab Vrije Universiteit Brussel Pleinlaan 2 Brussel1050 Belgium

ISBN: (纸本)9780791859353

This paper illustrates an integrated monitoring approach for wind turbines exploiting this Industry 4.0 context. Our combined edge-cloud processing approach is documented. We show edge processing of vibration data captured on a wind turbine gearbox to extract diagnostic features. Focus is on statistical indicators. Real-life signals collected on an offshore turbine are used to illustrate the concept of local processing. The NVIDIA Jetson platform serves as edge computation medium. Furthermore, we show an integrated failure detection and fault severity assessment at the cloud level. Health assessment and fault localization combines state-of-the-art vibration signal processing on high frequency data (10kHz and higher) with machine learning models to allow anomaly detection for each processing pipeline. Again this is illustrated using data from an offshore wind farm. Additionally, the fact that data of similar wind turbines in the farm is collected allows for exploiting system similarity over the fleet. Copyright © 2019 ASME

关键词： Offshore oil well production

来源：评论

学校读者我要写书评

暂无评论

Prediction Based Smart Farming 2

Prediction Based Smart Farming

引用

2nd international conference of Computer and Informatics Engineering (IC2IE) - Artificial Intelligence Roles in Industrial Revolution 4.0

作者： Chaganti, Sai Yasehwanth Ainapur, Prajwal Singh, Mayank Sangamesh Oktaviana R, Shinta NIIT Univ Dept ECE Neemrana Rajasthan India Politekn Negeri Jakarta Dept Comp & Informat Engn Depok Indonesia

ISBN: (纸本)9781728123844

The world population is expected to grow by over a third by 2050. Market demand for food will continue to grow. Automated drones and different robots in savvy cultivating applications offer the possibility to screen ranch arrive on a for each plant premise, which thus can diminish the measure of herbicides and pesticides that must be applied. There is a gap between current food productivity growth and needed growth. To boost the yield, farmers switched to extensive use of chemical fertilizers. Excessive fertilizer usage has its negative impact like decreased yield, wastage of fertilizer, damage to soil, and groundwater contamination. Currently, farmers mostly rely on guesswork, estimation, experience when deciding the crop that should grow, and the fertilizer that should be used. In this paper, we have proposed a solution that uses technologies like machine learning, Image processing, and the Internet of things to improvise farm productivity and at the same time, decrease the fertilizer usage. This paper describes the outcomes of a prototype implemented in Rajasthan, India.

关键词： machine learning drone imagery satellite imagery image processing

来源：评论

学校读者我要写书评

暂无评论

machine learning Methods Analysis For Calories Measuremnt of Fruits and Vegetables 5

Machine Learning Methods Analysis For Calories Measuremnt of...

引用

5th IEEE international conference on signal processing, Computing and Control (ISPCC)

作者： Mittal, Manisha Dhingra, Gittaly Kumar, Vinay Thapar Inst Engn & Technol Dept Elect & Commun Engn Patiala Punjab India

ISBN: (纸本)9781728139883

As people around the globe are becoming conscious about their weight, consume healthy and low-calorie food and keep away from obesity, it's an urge to establish a reliable system with high accuracy and efficiency for calorie and nutrition measurement in fruit/vegetable. The proposed model is developed to assist patients and dieticians to compute daily intake of calories. In this approach, 5 different machine learning models are used to predict classification accuracy. Our system includes camera and intelligent mat to capture the picture of the fruit/vegetable, in order to calculate the consumption of calorie. The proposed model achieves 88% accuracy with different testing-training cross validation dataset.

关键词： Calorie measurement feature extraction classification

来源：评论

学校读者我要写书评

暂无评论

A Correlation Analysis of the Sentiment Analysis Scores and Numerical Ratings of the Students in the Faculty Evaluation 19

A Correlation Analysis of the Sentiment Analysis Scores and ...

引用

2nd international conference on Artificial Intelligence and Pattern Recognition (AIPR)

作者： Lalata, Jay-ar P. Gerardo, Bobby Medina, Ruji Technol Inst Philippines Quezon City Aurora Blvd Quezon City Philippines West Visayas State Univ Coll Informat & Commun Technol Iloilo Philippines

ISBN: (纸本)9781450372299

This paper aims to analyze the relationship between the students' numerical rating and the qualitative measure of the students' written comments in the faculty evaluation using sentiment analysis. The dataset which consists of the numerical ratings and students' feedback obtained from the faculty evaluation system was used in the experiment. An ensemble model which consists of five machine learning algorithms was used to analyze and identify the polarity of the written comments of the students. The overall sentiment score was computed for each faculty and was compared to the numerical score using the statistical technique, Pearson's correlation coefficient. The result indicates that there is significance but very small relationship between the numerical rating and the overall sentiment scores. Based on the result, universities and colleges should exploit written comments since it is rich with observations and insights about the performance and effectiveness of a teacher. Moreover, sentiment analysis technique can be used to identify students' feeling towards teaching.

关键词： Natural language processing teacher's evaluation sentiment classification supervised machine learning opinion mining correlation

来源：评论

学校读者我要写书评

暂无评论

Classification of Nuclear Explosion Earthquake signal based on machine learning Approach 2

Classification of Nuclear Explosion Earthquake Signal based ...

引用

2nd international conference of Computer Science and Information Technology, ICoSNIKOM 2019

作者： Sinambela, Marzuki Situmorang, Marhoposan Tarigan, Kerista Humaidi, Syahrul Sebayang, Kerista Universitas Sumatera Utara Department of Physic Medan Indonesia

ISBN: (纸本)9781728154237

Identification and classification of the nuclear explosion signals have long been an important issue for some reason. The impact of the nuclear tests upon the environment is range out within minute affectation fatalities that may last for a long time. signal identification generated by a nuclear test had been analysis based on machine learning wavelet. The goal of this study to classify and detect the waveform of nuclear explosion signals. The result is then discussed in the context of the potential use of the proposed for a new perspective for the classification of nuclear explosion phases in vertical channel signals data collected within tele-seismic recording stations in Indonesia. The machine learning wavelet-based presents a useful way of observing the time-frequency component of a nuclear explosion to identifying the phase of Primer (P) wave is clear and simultaneous. © 2019 IEEE.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

2nd international Symposium on signal and Image processing, ISSIP 2018

2nd International Symposium on Signal and Image Processing, ...

引用

2nd international Symposium on signal and Image processing, ISSIP 2018

ISBN: (纸本)9789811367823

The proceedings contain 12 papers. The special focus in this conference is on signal and Image processing. The topics include: Fuzzy-Based Classification for Fusion of Palmprint and Iris Biometric Traits;Employing FPGA Accelerator in Real-Time Speaker Identification Systems;pyramid-Based Multi-scale Enhancement Method for Iris Images;character Recognition from Handwritten Image Using Convolutional Neural Networks;Malignant Melanoma Classification Using Cross-Platform Dataset with Deep learning CNN Architecture;automatic Gender Identification fromÂ Children Facial Images Using Texture Descriptors;Assessment of UWAC System Performance Using FBMC Technique;simple Exponential Smoothing and Its Control Parameter: A Reassessment;a Novel Cross-Dimensional Image processing Technique: Toward a 3D View of a 2D Image;quantum-Inspired Bat Optimization Algorithm for Automatic Clustering of Grayscale Images.

关键词：

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135页 << < 78 79 80 81 82 83 84 85 86 87 > >>

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：