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

550 篇 会议
28 篇 期刊文献
7 册 图书

馆藏范围

585 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

470 篇 工学
- 425 篇 计算机科学与技术...
- 199 篇 软件工程
- 110 篇 电气工程
- 67 篇 信息与通信工程
- 45 篇 生物工程
- 42 篇 生物医学工程（可授...
- 26 篇 控制科学与工程
- 20 篇 光学工程
- 13 篇 仪器科学与技术
- 11 篇 机械工程
- 10 篇 化学工程与技术
- 9 篇 交通运输工程
- 8 篇 电子科学与技术（可...
- 7 篇 土木工程
140 篇 理学
- 69 篇 数学
- 56 篇 生物学
- 33 篇 物理学
- 24 篇 统计学（可授理学、...
- 19 篇 系统科学
- 8 篇 化学
90 篇 管理学
- 63 篇 图书情报与档案管...
- 35 篇 管理科学与工程(可...
- 19 篇 工商管理
46 篇 医学
- 36 篇 临床医学
- 22 篇 基础医学(可授医学...
- 13 篇 药学(可授医学、理...
- 7 篇 特种医学
- 6 篇 公共卫生与预防医...
11 篇 法学
- 9 篇 社会学
11 篇 教育学
- 10 篇 教育学
8 篇 经济学
6 篇 农学

主题

74 篇 machine learning
55 篇 data mining
36 篇 pattern recognit...
33 篇 deep learning
20 篇 feature extracti...
18 篇 artificial intel...
16 篇 support vector m...
15 篇 learning systems
11 篇 image classifica...
9 篇 training
8 篇 neural networks
8 篇 face recognition
8 篇 manifold learnin...
8 篇 supervised learn...
7 篇 pattern classifi...
7 篇 big data
7 篇 clustering algor...
7 篇 classification (...
7 篇 machine learning...
7 篇 data models

机构

4 篇 ukrainian cathol...
3 篇 harbin inst tech...
3 篇 guilin univ elec...
3 篇 fujian univ tech...
3 篇 college of compu...
3 篇 kunming univ col...
3 篇 nanjing univ sci...
3 篇 concordia univ d...
2 篇 shanghai jiao to...
2 篇 australian e-hea...
2 篇 telangana hydera...
2 篇 key lab data gov...
2 篇 idiap ch-1920 ma...
2 篇 department of ma...
2 篇 univ toronto dep...
2 篇 univ montreal di...
2 篇 chitkara univers...
2 篇 natl univ singap...
2 篇 pattern analysis...
2 篇 univ katolik ind...

作者

3 篇 li junbao
3 篇 maier andreas
3 篇 bengio s
3 篇 deepa r.
3 篇 deng fei
3 篇 pan jeng-shyang
3 篇 hu cong
3 篇 zhang daoqiang
3 篇 amelio alessia
3 篇 maier-hein klaus
3 篇 he chunhui
2 篇 vrahatis aristid...
2 篇 jin zhong
2 篇 collobert r
2 篇 tax dmj
2 篇 sharma r
2 篇 cilia nicole dal...
2 篇 fontanella franc...
2 篇 genov r
2 篇 stiefelhagen rai...

语言

568 篇 英文
12 篇 中文
9 篇 其他
1 篇 俄文

检索条件"任意字段=1st International Workshop on Machine Learning and Data Mining in Pattern Recognition"

共 585 条记录，以下是361-370 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：

Multidimensional wavelet neuron for pattern recognition tasks in the internet of things applications 1st

Multidimensional wavelet neuron for pattern recognition task...

引用

1st international Conference on Computer Science, Engineering and Education Applications, ICCSEEA2018

作者： Vynokurova, Olena Peleshko, Dmytro Oskerko, Semen Lutsan, Vitalii Peleshko, Marta IT Step University 83a Zamarstynivs’ka str. Lviv79019 Ukraine Lviv State University of Life Safety 35 Kleparivska Lviv79000 Ukraine

ISBN: (纸本)9783319910079

data mining and processing of Big data is key problem in developing intelligent Internet of Things (IoT) applications. In this article, the multidimensional wavelet neuron for pattern recognition tasks is proposed. Also, the learning algorithm based on the quadratic error criterion is synthesized. This approach combines the benefits of the neural networks, the neuro-fuzzy system, and the wavelet functions approximation. The proposed multidimensional wavelet neuron can be used to solve a very large class of information processing problems for the Internet of Things applications when signals are fed in online mode from many sensors. The proposed approach is uncomplicated for computational realization and can be implemented in hardware for IoT systems. The proposed learning algorithm is characterized by a high rate of convergence and high approximation properties. © Springer international Publishing AG, part of Springer Nature 2019.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

machine learning for Dynamically Predicting the Onset of Renal Replacement Therapy in Chronic Kidney Disease Patients Using Claims data 1

引用

1st international workshop on Applications of Medical Artificial Intelligence (AMAI)

作者： Lopez-Martinez, Daniel Chen, Christina Chen, Ming-Jun Google Res Palo Alto CA 94304 USA

ISBN: (数字)9783031177217

ISBN: (纸本)9783031177217;9783031177200

Chronic kidney disease (CKD) represents a slowly progressive disorder that can eventually require renal replacement therapy (RRT) including dialysis or renal transplantation. Early identification of patients who will require RRT (as much as 1 year in advance) improves patient outcomes, for example by allowing higher-quality vascular access for dialysis. Therefore, early recognition of the need for RRT by care teams is key to successfully managing the disease. Unfortunately, there is currently no commonly used predictive tool for RRT initiation. In this work, we present a machine learning model that dynamically identifies CKD patients at risk of requiring RRT up to one year in advance using only claims data. To evaluate the model, we studied approximately 3 million Medicare beneficiaries for which we made over 8 million predictions. We showed that the model can identify at risk patients with over 90% sensitivity and specificity. Although additional work is required before this approach is ready for clinical use, this study provides a basis for a screening tool to identify patients at risk within a time window that enables early proactive interventions intended to improve RRT outcomes.

关键词： Dialysis Kidney transplant Chronic kidney disease Claims data Dynamic modeling

来源：评论

学校读者我要写书评

暂无评论

The Comparison of Some Hidden Markov Models for Sign Language recognition 1

The Comparison of Some Hidden Markov Models for Sign Languag...

引用

1st international Conference of the Indonesian-Association-for-pattern-recognition (INAPR)

作者： Suharjito Gunawan, Herman Thiracitta, Narada Witjaksono, Gunawan Bina Nusantara Univ Dept Comp Sci BINUS Grad Program Comp Sci Jakarta 11480 Indonesia Bina Nusantara Univ Sch Comp Sci Dept Comp Sci Jakarta 11480 Indonesia

ISBN: (纸本)9781538694220

Sign language is one of the most popular communication technique. While it is popular, most people don't know how to use it. The problem lies in the difficulty of how many signs there to be memorized. That's why Sign Language recognition (SLR) is needed. Sign Language recognition (SLR) is a very interesting area for some researcher because of the complexity of its problem especially using video-based recognition of complex sign language. That's why Sign Language recognition (SLR) has been developed for a long time. Unfortunately, every research about Sign Language recognition has its own limitation. Some research got low accuracy, too expensive, insufficient dataset, and many other else. Every researcher also has their own way of doing a thing but usually, the pattern in Sign Language recognition (SLR) are dataset collection, preprocessing data, feature extraction, training, and classification. For the dataset, we will use Argentina Sign Language that provides data as video. After that, we need to preprocess it using edge detection and skin detection using the help of Contrast Adaptive Histogram Equalization (CLAHE) for image enhancement. Then we will extract its feature by its movement. At last, we will train and classify the data using some modified Hidden Markov Model. In this research, we get an accuracy of 83% by classifying 10 signs using Gaussian Hidden Markov Model (Gaussian HMM) and 72% by classifying 10 signs using Multinomial Hidden Markov Model (Multinomial HMM).

关键词： comparation hidden markov model machine learning recognition sign language

来源：评论

学校读者我要写书评

暂无评论

1st international Conference on Big data Analysis and Deep learning, ICBDL 2018

1st International Conference on Big Data Analysis and Deep L...

引用

1st international Conference on Big data Analysis and Deep learning, ICBDL 2018

ISBN: (纸本)9789811308680

The proceedings contain 42 papers. The special focus in this conference is on Big data Analysis and Deep learning. The topics include: Multi-label land cover indices classification of satellite images using deep learning;real-time hand pose recognition using faster region-based convolutional neural network;school mapping for schools of basic education in Myanmar;GBSO-RSS: GPU-based BSO for rules space summarization;machine learning based live VM migration for efficient cloud data center;dynamic replication management scheme for distributed file system;Frequent pattern mining for dynamic database by using hadoop GM-Tree and GTree;investigation of the use of learning management system (moodle) in University of Computer studies, Mandalay;user preference information retrieval by using multiplicative adaptive refinement search algorithm;predictive big data analytics using multiple linear regression model;proposed framework for stochastic parsing of Myanmar language;FDTD based numerical calculation of electromagnetic wave radiation in multi-layer circular cylindrical human head;improved convergence in eddy-current analysis by singular value decomposition of subdomain problem;development and validation of parallel acoustic analysis method for the sound field design of a large space;secret audio messages hiding in images;Location based personal task reminder system using GPS technology;front caster capable of reducing horizontal forces on step climbing;mobile location based indexing for range searching;building travel speed estimation model for Yangon City from public transport trajectory data;comparison between block-encoding and quadtree compression methods for raster maps;evaluation for teacher’s ability and forecasting student’s career based on big data;behavior analysis for nursing home monitoring system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Explainable AI Framework for Treatment Failure Model for Oncology Patients 3rd

An Explainable AI Framework for Treatment Failure Model for ...

引用

21st Artificial Intelligence in Medicine (AIME) Conference / 3rd international workshop on Explainable Artificial Intelligence in Healthcare (XAI-Healthcare) / 1st international workshop on Process mining Applications for Healthcare (PM4H)

作者： Zaidi, Syed Hamail Hussain Hashmat, Bilal Farooq, Muddassar CureMD Res 80 Pine St 21St Floor New York NY 10005 USA

ISBN: (纸本)9783031543029;9783031543036

The black box nature of current AI models has raised serious concerns about accountability, bias and trust in the models that might undermine their relevance and usefulness in the field of medicine where human lives are at risk. AI in medicine has the ability to derive meaningful inferences from real world data - an emerging school of thought namely Real World Evidence (RWE) studies - that can assist medical practitioners to improve evidence based quality of care. In the field of oncology, the accuracy and performance of inference models are as important as clinically relevant and sound explanations of the inference. In this paper, we present an Explainable AI (XAI) framework for our AI model that predicts the suitability of a chemotherapy treatment at the time of its prescription based on RWE. The framework provides explanations both for a specific patient and also for the model. It provides explanations like feature analysis, counterfactual, and top risk factors that contribute to a treatment failure. As a result, the framework adds an explainability layer between treatment failure predictive model and oncologists, thereby enabling evidence based assistance to oncologists in designing chemotherapy plans.

关键词： Explainability machine learning Model Agnostic Oncology

来源：评论

学校读者我要写书评

暂无评论

21st international workshops on Financial Cryptography and data Security, FC 2017 held in conjuction with 5th workshop on Encrypted Computing and Applied Homomorphic Cryptography, WAHC 2017, 4th workshop on Bitcoin and Blockchain Research, BITCOIN 2017, 2nd workshop on Advances in Secure Electronic Voting Schemes, VOTING 2017, 1st workshop on Trusted Smart Contracts, WTSC 2017 and 1st workshop on Targeted Attacks, TA 2017

21st International Workshops on Financial Cryptography and D...

引用

21st international workshops on Financial Cryptography and data Security, FC 2017 held in conjuction with 5th workshop on Encrypted Computing and Applied Homomorphic Cryptography, WAHC 2017, 4th workshop on Bitcoin and Blockchain Research, BITCOIN 2017, 2nd workshop on Advances in Secure Electronic Voting Schemes, VOTING 2017, 1st workshop on Trusted Smart Contracts, WTSC 2017 and 1st workshop on Targeted Attacks, TA 2017

ISBN: (纸本)9783319702773

The proceedings contain 39 papers. The special focus in this conference is on Financial Cryptography and data Security. The topics include: Preface: Bitcoin 2017: 4th workshop on bitcoin and blockchain research;Preface: VOTING 2017: Second workshop on advances in secure electronic voting schemes;Preface: WTSC 2017: First workshop on trusted smart contracts;Preface: TA 2017: First workshop on targeted attacks;Simple encrypted arithmetic library - SEAL v2.1;switch commitments: A safety switch for confidential transactions;pieceWork: Generalized outsourcing control for proofs of work;enhancing bitcoin transactions with covenants;decentralized prediction market without arbiters;An analysis of bitcoin OP_RETURN metadata;constant-deposit multiparty lotteries on bitcoin;exchange pattern mining in the bitcoin transaction directed hypergraph;incentivizing blockchain forks via whale transactions;mixing coins of different quality: A game-theoretic approach;smart contracts make bitcoin mining pools vulnerable;towards privacy-preserving multi-party bartering;batchVote: Voting rules designed for auditability;existential assertions for voting protocols;marked mix-nets;pseudo-code algorithms for verifiable re-encryption mix-nets;Using selene to verify your vote in JCJ;a roadmap to fully homomorphic elections: stronger security, better verifiability;enabling vote delegation for boardroom voting;practical governmental voting with unconditional integrity and privacy;findel: Secure derivative contracts for ethereum;decentralized execution of smart contracts: Agent model perspective and its implications;multi-level access in searchable symmetric encryption;a concurrent perspective on smart contracts;an Empirical analysis of smart contracts: Platforms, applications, and design patterns;trust in smart contracts is a process, as well;defining the ethereum virtual machine for interactive theorem provers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Fusing traffic sensor data for real-time road conditions

Fusing traffic sensor data for real-time road conditions

引用

1st international workshop on Sensing and Big data mining, SenseMine 2013

作者： Bouillet, Eric Chen, Bei Cooper, Chris Dahlem, Dominik Verscheure, Olivier IBM Research Ireland Ireland IBM UK United Kingdom

ISBN: (纸本)9781450324304

Transport authorities have been deploying and utilising sensor infrastructures in order to improve upon the level of transport-related services within cities. As existing resources are more and more constrained, novel means of utilising the data originating from these sensors are sought. Advanced IT infrastructures enable real-time processing use cases, such as travel time estimations along defined corridors. One major challenge is to deploy general purpose machine learning algorithms that are able to learn relationships between the covariates and a defined response variable. We introduce a data fusion approach using generalised additive models (GAM) to estimate journey times online in a real-time streaming platform. We experiments with bluetooth sensors and weather information to improve the estimation of journey times along a defined A3 corridor in south-central London. Our approach is able to continuously improve the journey time estimation as new (high-frequency) data becomes available. Our fusion platform also generalises to be able to process more data sources and it scales to city-wide deployments. This way, existing legacy sensor deployments can be utilised for novel value-added services and investments into infrastructural sensor deployments can be assessed in a data-driven way and on a needs basis. © 2013 ACM.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

A Generative Dyadic Aspect Model for Evidence Accumulation Clustering

引用

1st international workshop on Similarity-Based pattern recognition (SIMBAD)

作者： Lourenco, Andre Fred, Ana Figueiredo, Mario Inst Telecomunicacoes Lisbon Portugal

ISBN: (纸本)9783642244704

Evidence accumulation clustering (EAC) is a clustering combination method in which a pair-wise similarity matrix (the so-called co-association matrix) is learnt from a clustering ensemble. This co-association matrix counts the co-occurrences (in the same cluster) of pairs of objects, thus avoiding the cluster correspondence problem faced by many other clustering combination approaches. starting from the observation that co-occurrences are a special type of dyads, we propose to model co-association using a generative aspect model for dyadic data. Under the proposed model, the extraction of a consensus clustering corresponds to solving a maximum likelihood estimation problem, which we address using the expectation-maximization algorithm. We refer to the resulting method as probabilistic ensemble clustering algorithm (PEnCA). Moreover, the fact that the problem is placed in a probabilistic framework allows using model selection criteria to automatically choose the number of clusters. To compare our method with other combination techniques (also based on probabilistic modeling of the clustering ensemble problem), we performed experiments with synthetic and real benchmark data-sets, showing that the proposed approach leads to competitive results.

关键词： Unsupervised learning clustering clustering Combination generative models model Selection

来源：评论

学校读者我要写书评

暂无评论

Proceedings of the 1st ACM workshop on Audio and Music Computing for Multimedia, AMCMM'06

Proceedings of the 1st ACM Workshop on Audio and Music Compu...

引用

1st ACM workshop on Audio and Music Computing for Multimedia, AMCMM'06, co-located with the 2006 ACM international Multimedia Conference

ISBN: (纸本)1595935010

The proceedings contain 18 papers. The topics discussed include: a system for the automatic segmentation and classification of chord sequences;automatic chord recognition from audio using a supervised HMM trained with audio-from-symbolic data;detecting harmonic change in musical audio;lightweight measures for timbral similarity of musical audio;a dictionary based approach for robust and syllable-independent audio input transcription for query by humming systems;pitch-shifting audio signals using sparse atomic approximations;music structure analysis by finding repeated parts;similarity matrix processing for music structure analysis;measuring playlist diversity for recommendation systems;predicting success from music sales data: a statistical and adaptive approach;incorporating machine-learning into music similarity estimation;and a real-time multimedia composition layer.

关键词： Acoustic signal processing

来源：评论

学校读者我要写书评

暂无评论

Patient-Specific Modeling for pattern Identification in Clinical Events Using data mining Models and Evolutionary Computing 1st

引用

1st international Conference on Soft Computing: Theories and Applications, SoCTA 2016

作者： Yadav, Sourabh Saroliya, Anil Amity School of Engineering and Technology Amity University JaipurRajasthan India

ISBN: (纸本)9789811056864

Nowadays due to the technological advancement in collecting, processing and producing the information available, it is quite challenging to obtain the relevant information out from various sources of data. According to earlier research in homeopathy, a pattern system of treatment is being followed, which ultimately helps in finding the cure for the disease. One of the main goals of this system of treatment is to individualize the model in a manner that patient-specific prediction can be fixated with the help of pattern identification. By adopting the context of homeopathy system, the aim of this paper focuses on identifying appropriate parameters from a large quantity of raw clinical data, which are responsible for developing celiac disease in the human body. The result is based on the extensive quantitative research of a clinical database, shows that one parameter is correlating with another and such kind of pattern identification will be useful in the curing of celiac disease. © 2018, Springer Nature Singapore Pte Ltd.

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59页 << < 33 34 35 36 37 38 39 40 41 42 > >>

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：