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

724 篇 会议
3 篇 期刊文献
2 册 图书

馆藏范围

729 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

474 篇 工学
- 379 篇 计算机科学与技术...
- 273 篇 软件工程
- 175 篇 信息与通信工程
- 106 篇 电气工程
- 81 篇 生物工程
- 76 篇 生物医学工程（可授...
- 47 篇 控制科学与工程
- 33 篇 电子科学与技术（可...
- 29 篇 机械工程
- 27 篇 光学工程
- 26 篇 化学工程与技术
- 18 篇 仪器科学与技术
- 14 篇 安全科学与工程
- 13 篇 交通运输工程
- 13 篇 农业工程
214 篇 理学
- 114 篇 数学
- 89 篇 生物学
- 67 篇 物理学
- 41 篇 系统科学
- 38 篇 统计学（可授理学、...
- 24 篇 化学
95 篇 医学
- 91 篇 临床医学
- 56 篇 基础医学(可授医学...
- 46 篇 药学(可授医学、理...
- 13 篇 公共卫生与预防医...
95 篇 管理学
- 57 篇 图书情报与档案管...
- 41 篇 管理科学与工程(可...
- 16 篇 工商管理
17 篇 农学
- 17 篇 作物学
11 篇 法学
- 11 篇 社会学
7 篇 教育学
6 篇 经济学
5 篇 军事学

主题

168 篇 machine learning
50 篇 deep learning
46 篇 support vector m...
46 篇 feature extracti...
41 篇 signal processin...
24 篇 signal processin...
23 篇 machine learning...
18 篇 image processing
18 篇 training
16 篇 artificial intel...
16 篇 accuracy
15 篇 electroencephalo...
14 篇 decision trees
14 篇 computer vision
13 篇 natural language...
13 篇 neural networks
13 篇 classification a...
13 篇 convolutional ne...
12 篇 data mining
12 篇 classification

机构

6 篇 xinjiang key lab...
6 篇 school of inform...
6 篇 fujian provincia...
6 篇 xinjiang key lab...
5 篇 beijing universi...
3 篇 fujian provincia...
2 篇 college of engin...
2 篇 university of jo...
2 篇 school of electr...
2 篇 china electric p...
2 篇 department of ar...
2 篇 department of it...
2 篇 valencian resear...
2 篇 ugam solutions c...
2 篇 department of co...
2 篇 chongqing univ s...
2 篇 guangzhou xinhua...
2 篇 college of elect...
2 篇 school of comput...
2 篇 guangzhou power ...

作者

10 篇 hamdulla askar
6 篇 ablimit mijit
6 篇 li zuoyong
3 篇 vysotska victori...
3 篇 teng shenghua
2 篇 veeresh
2 篇 xue jingfeng
2 篇 mohanty mihir na...
2 篇 agarwal harsh
2 篇 jin lingmin
2 篇 kalinina irina
2 篇 jia cairang
2 篇 renjith p.n.
2 篇 gozhyj aleksandr
2 篇 wen zhang
2 篇 li zheng
2 篇 selvi g. thamara...
2 篇 pandey trilok na...
2 篇 islam md. adnanu...
2 篇 kama mohd nazri

语言

700 篇 英文
28 篇 其他
4 篇 中文

检索条件"任意字段=3rd International Conference on Signal Processing and Machine Learning, SPML 2020"

共 729 条记录，以下是601-610 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：

Deep learning based Identification of Primary Speaker in Voice-Controlled Devices

Deep Learning based Identification of Primary Speaker in Voi...

引用

international conference on Intelligent Sustainable Systems (ICISS)

作者： Kavya Khatter Daksha Singhal Jayashree. R PES University

ISBN: (数字)9781728170893

ISBN: (纸本)9781728170909

At present, so many low budget recording devices available, recording lectures, meetings, conferences and events have become a very easy option for everyone but also at the same time these devices lead to unclear speeches. An advanced methodology of identifying the primary speaker is introduced to record noisy audio file given in any regional language. The speaker turns and speaker lengths are examples of features which provide greater insight in the detection of primary speakers. This also provides the transcript of the primary speaker audio chunk to the end-user. Speaker diarization is the process of identifying various chunks in given audio belonging to different homogenous speakers where the count of speakers is unknown. This process is a mixture of segmentation and clustering. Speech segmentation detects the speaker change points followed by grouping them based on the speaker. Thus, Speaker Diarization is the most important step in the Identification of the primary speaker.

关键词： Speech processing signal processing Feature extraction conferences Acoustics Mathematical model Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Road Traffic signal Control and Management System : A Survey

Road Traffic Signal Control and Management System : A Survey

引用

international conference on Intelligent Sustainable Systems (ICISS)

作者： R M Savithramma R Sumathi Computer Science & Engineering Siddaganga Institute of Technology Tumakuru India

ISBN: (数字)9781728170893

ISBN: (纸本)9781728170909

From the past few decades, technology is out breaking with its significant application in each and every field. Gradually, technology is becoming integral part of human life and effectively used to address many societal issues. One such issue is traffic in urban areas that leads to elongated waiting time at road intersections. An Intelligent Traffic signal System (ITSS) can mitigate the urban traffic congestion. Already many researchers are working towards and proposed various solutions or techniques. The solution involves combination of different technologies such as Fuzzy Logic, Wireless Sensor Network, machine learning, Artificial Neural Networks, Internet of Things, Microcontrollers and high level computing environments. The proposed ideas are capable of adapting to the traffic demands based on real time situations on the road, resulting in efficient utilization of the available road infrastructure. In this paper, an attempt has been made to classify the traffic control signal system deployed at the intersections based on technology adopted and various research contribution for developing ITSS are also summarised.

关键词： Roads Delays Control systems Urban areas Traffic congestion Real-time systems Computational modeling

来源：评论

学校读者我要写书评

暂无评论

Just-in-time Parsing with Scannerless Earley Virtual machines 2019

Just-in-time Parsing with Scannerless Earley Virtual Machine...

引用

Proceedings of the 3rd international conference on Vision, Image and signal processing

作者： Audrius Saikunas Institute of Data Science and Digital Technologies Vilnius Lithuania

ISBN: (纸本)9781450376259

Scannerless Earley Virtual machines (SEVM) is a new generalized context-free parsing method, in which grammars are internally encoded using a special instruction intermediate language. In this paper we show how just-in-time compilation can be used to translate intermediate form grammars into native machine code to achieve improved parsing performance. We also present an efficient method for lexical disambiguation, which additionally enables to significantly reduce the amount of code that needs to be just-in-time compiled. Finally, we compare our implementation of SEVM with other parser implementations and show that our parser provides acceptable performance for analysing real-world computer languages.

关键词： Just-in-time compiler Scannerless parsing Virtual machine Parsing

来源：评论

学校读者我要写书评

暂无评论

引用

Proceedings of the 2019 3rd international conference on Software and e-Business

作者： Joel C. De Goma Oscar Jensen D. Binsol Alexander Michael T. Nadado Jose Peter A. Casela School of Information Technology Mapua Univesity Makati City Philippines School of Information Technology Mapua University Makati City Philippines

ISBN: (纸本)9781450376495

Age-Related Macular Degeneration (AMD) is a leading retinal disease that causes vision loss affect people from age fifty five(55) and older. The disease is characterized by the formation of drusen or the yellow deposits containing lipids forming within the macula region of the eye. One of the various ways to diagnose AMD is through obtaining fundus photography using a specialized retinal camera. This study assesses the accuracy of the proposed methodology in recognizing AMD-positive fundus images using Digital Image processing and various machine learning models such as Naïve Bayes (NB), Neural Network (NN), Support Vector machine (SVM) and Random Forest (RF). The fundus images undergo intensity adjustment and bilateral filter it is then followed by optic disc extraction and Superpixel segmentation using Simple Linear Iterative Clustering. Features, such as Intensity-based statistics and Texton-map Histogram, are extracted and normalized. The resulting values are classified by various machine learning algorithms as positive or negative for AMD. The proposed methodology is able to determine Healthy and AMD-positive images while also providing accuracy comparison among machine learning models.

关键词： Macular Degeneration Image processing Simple Linear Iterative Clustering machine learning Bilateral Filtering

来源：评论

学校读者我要写书评

暂无评论

Low Complexity Named-Entity Recognition for Indonesian Language using BiLSTM-CNNs

Low Complexity Named-Entity Recognition for Indonesian Langu...

引用

international conference on Information and Communications Technology (ICOIACT)

作者： Sahrul Sukardi Meredita Susanty Ade Irawan Randi Fermana Putra Computer Science Universitas Pertamina Jakarta Indonesia

ISBN: (数字)9781728173566

ISBN: (纸本)9781728173573

Named-Entity Recognition (NER) is a fundamental task in Natural Language processing (NLP) and information extraction. NER is used to extract information such as names of the people, organizations, and places. NER has been used in many fields of work, one of which is in chatbot development. NLP and machine learning approaches enable a smarter chatbot with better personal analysis to users. This research builds a NER model in Indonesian Language using Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Networks (CNNs) model architecture. Unlike the former research, this model only uses word-level embedding in the CNNs layer to keep the model simple. The Named-Entities (NEs) used in this study are limited to the name of the person, organization, location, quantity, and time using the BILOU labeling format. The performance of the model built is measured using micro-averaged f1 score evaluation metric. The BiLSTM-CNNs + pretrained word2vec embedding model provides good performance compared to other models with an f1 score of 71.37%.

关键词： Resistance Measurement Neural networks Organizations machine learning Chatbot Task analysis

来源：评论

学校读者我要写书评

暂无评论

A machine learning Distracted Driving Prediction Model 2019

A Machine Learning Distracted Driving Prediction Model

引用

Proceedings of the 3rd international conference on Vision, Image and signal processing

作者： Samira Ahangari Mansoureh Jeihani Abdollah Dehzangi Department of Transportation and Infrastructure Studies Morgan State University USA Department of Computer Science Morgan State University USA

ISBN: (纸本)9781450376259

Distracted driving is known to be one of the core contributors to crashes in the U.S., accounting for about 40% of all crashes. Drivers' situational awareness, decision-making, and driving performance are impaired due to temporarily diverting their attention from the primary task of driving to other tasks not related to driving. Detecting driver distraction would help in adapting the most effective countermeasures. To find the best strategies to overcome this problem, we developed a Bayesian Network (BN) distracted driving prediction model using a driving *** this study, we use a Bayesian Network classifier as a powerful machine learning algorithm on our trained data (80%) and tested (20%) with the data collected from a driving simulator, in which the 92 participants drove six scenarios of hand-held calling, hands-free calling, texting, voice command, clothing, and eating/drinking on four different road classes (rural collector, freeway, urban arterial, and local road in a school zone). Various driving performances such as speed, acceleration, throttle, lane changing, brake, collision, and offset from the lane center were *** we investigated different optimization models to build the best BN in which a Genetic Search Algorithm obtained the best performance. As a result, we achieved a 67.8% prediction accuracy using our model to predict driver distraction. We also achieved 62.6% true positive rate, which demonstrates the ability of our model to correctly predict distractions.

关键词： Data Mining Driving Simulator machine learning Distracted Driving Bayesian Network

来源：评论

学校读者我要写书评

暂无评论

Distributed Alternating Direction Multiplier Method Based on Optimized Topology and Nodes Selection Strategy

Distributed Alternating Direction Multiplier Method Based on...

引用

international Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Shuai Zeng Haitao Lin School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9781728184067

ISBN: (纸本)9781728184074

ADMM (The Alternating Direction Multiplier Method) has been widely used in large-scale distributed machine learning, however the classical distributed ADMM algorithm lacks of optimization for network characteristics, which makes the convergence speed not reach the optimal. In this paper, A distributed ADMM with optimized network topology and nodes selection strategy is proposed. The proposed algorithm improves the performance of distributed computing by optimizing the topology structure of the network and reasonably allocating the node identity to avoid the large delay edges in the ADMM iterations as much as possible. The experimental results shown that based on proposed algorithm the calculation time of ADMM is improved, while the accuracy is controlled within an acceptable range. Compared with the classical distributed ADMM algorithm, the convergence time of distributed ADMM algorithm can be reduced by about 60% to 70%. The results also shown that the proposed algorithm is more prominent in the scenario of high delay or dynamics networks.

关键词： Delays Network topology Convex functions Convergence signal processing algorithms Topology machine learning algorithms

来源：评论

学校读者我要写书评

暂无评论

A review on depression detection and diagnoses based on visual facial cues

A review on depression detection and diagnoses based on visu...

引用

international conference on Engineering Technology and their Applications (IICETA)

作者： Sana A. Nasser Ivan A. Hashim Wisam H. Ali University of Technology Baghdad Iraq

ISBN: (数字)9781728182315

ISBN: (纸本)9781728182322

Computerized artificial intelligent machines and devices are invading all human life details rapidly. Verities of algorithms have been proposed to achieve results that can match or exceed the human results. The automatic visual facial cues based depression assessment is a fast-growing research area since it can provide help to psychiatrists and physicians in some cases when traditional other ways fail. The system has many stages, and different kinds of strategies have been used over the past years. Summarizing the previous works, going over the system stages and how the system works are needed to give a brief overview on the topic. This can provide a helpful start for researchers that tend to explore such a domain. Accordingly, the work demonstrates the topic from many aspects, touches on the general parts, and details the important associated points of it. The contribution of this paper is to make a review for the techniques used to detect depression from facial cues, as well as the established system for signal processing and extraction of features for previous studies in this field; which is new in the field of detect depression, so this review is not investigation has been done, but it's a discussion of researches that Issued and comparing the techniques utilized and proposing the best technology.

关键词： Depression Feature extraction Visualization Support vector machines machine learning Face recognition Mood

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Sentiment Databases: A Comparison of Sentiment Databases through Social Listening Statements and Azure machine learning Studio 19

Evaluation of Sentiment Databases: A Comparison of Sentiment...

引用

Proceedings of the 2019 3rd international conference on E-Business and Internet

作者： Marc Notz Jens Grambau Arno Hitzges Print and Media Hochschule der Medien Stuttgart Germany

ISBN: (纸本)9781450371704

Nowadays it happens more and more frequently that people get their opinions about products in social media or online reviews. For this purpose, product reviews themselves or channels on social media are searched in order to get an impression of what other users think about products before buying. For companies, these Social Listening Statements (SLS) can be business critical. A sentiment analysis is part of Natural Language processing (NLP). The analysis of text tries to identify and extract sentiments in a text. In this paper, two supervised machine learning algorithms for text analysis were combined with four sentiment databases to increase accuracy in recognition. For better comparability, basic sentiment databases without subject-specific terms were used. Experiments were conducted with manually and automatically generated data sets, ranging in size from 300 to 16,000 entries. The combination of these two methods resulted in an accuracy of up to 94% in detecting positive or negative sentiment in texts. The combination of sentiment databases (SD) and machine learning significantly increased the recognition.

关键词： social listening statements machine learning review research NLP sentiment lexicon opinion mining social media sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Cooperative Spectrum Sensing Over Weibull and Hoyt Fading Channels using Centralized and Distributed Schemes

Cooperative Spectrum Sensing Over Weibull and Hoyt Fading Ch...

引用

r Engineering: machine learning and Internet of Things (ICETCE), 2020 3rd international conference on

作者： Yashaswini Sharma Ritu Sharma K. K. Sharma Girraj Sharma Department of ECE MNIT Jaipur Jaipur India Department of ECE JECRC College Jaipur India

ISBN: (数字)9781728116839

ISBN: (纸本)9781728116846

Multipath fading, hidden terminal and shadowing are problems faced by users in non-cooperative type spectrum sensing techniques. A solution to this problem is Cooperative Spectrum Sensing (CSS) technique. CSS allows users to collaborate to perform spectrum sensing which may be managed by a common receiver. Further, it has two categories Distributed CSS (DCSS) and Centralized CSS (CCSS). In this paper these two schemes are compared with each other and different fusion rules are applied over them. Mathematical formulas for detection probability (P d ) of two fading channels namely Weibull and Hoyt are shown and further different fusion rules are applied on cluster-based CSS to explore the performance of centralized and distributed CSS. This concept has been earlier used for the conventional fading channels i.e. Rayleigh, Rician, Nakagami-m. In this paper results for cluster-based CSS are examined for comparatively lesser studied Weibull and Hoyt fading channels. It is noticed for different fusion rules, Weibull fading channel generates better performance as compared to Hoyt fading channel. This paper focuses on the implementation of four different fusion rules such as AND-AND, AND-OR, OR-AND along with centralized AND for these two fading channels. Results have shown that at SNrd) than the Hoyt fading channel for all four fusion rules. It is noticed that the slope of the curve for Hoyt fading channel is steep as compared to Weibull fading channel and reaches to 0.9 P d at SNR>5dB for OR-AND and AND-OR rule, while with these fusion rules, Weibull fading channel attains 0.9 P d at SNR less than 0dB. OR-AND fusion rule gives the best result amongst all 4 fusion rules for both the channels.

关键词： Cascading style sheets Sensors signal to noise ratio Weibull fading channels Mathematical model Rayleigh channels

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73页 << < 57 58 59 60 61 62 63 64 65 66 > >>

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：