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A Study on Apparent Age Estimation 15

A Study on Apparent Age Estimation

引用

IEEE international conference on Computer Vision (ICCV)

作者： Zhu, Yu Li, Yan Mu, Guowang Guo, Guodong West Virginia Univ Lane Dept CSEE Morgantown WV 26506 USA Chinese Acad Sci Key Lab Intelligent Informat Proc Inst Comp Technol Beijing 100190 Peoples R China

ISBN: (纸本)9780769557205

Age estimation from facial images is an important problem in computer vision and pattern recognition. Typically the goal is to predict the chronological age of a person given his or her face picture. It is seldom to study a related problem, that is, how old does a person look like from the face photo? It is called apparent age estimation. A key difference between apparent age estimation and the traditional age estimation is that the age labels are annotated by human assessors rather than the real chronological age. The challenge for apparent age estimation is that there are not many face images available with annotated age labels. Further, the annotated age labels for each face photo may not be consistent among different assessors. We study the problem of apparent age estimation by addressing the issues from different aspects, such as how to utilize a large number of face images without apparent age labels to learn a face representation using the deep neural networks, how to tune the deep networks using a limited number of examples with apparent age labels, and how well the machine learning methods can perform to estimate apparent ages. The apparent age data is from the ChaLearn Looking At People (LAP) challenge 2015. Using the protocol and time frame given by the challenge competition, we have achieved an error of 0.294835 on the final evaluation, and our result has been ranked the 3rd place in this competition.

关键词： Computer architecture data models databases Estimation Face Neural networks Training

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Tuning GSP Parameters with GA 1

引用

5th international conference on Intelligence Science and Big data Engineering (IScIDE)

作者： Cheng, Wei Chi Hsu, Ping Yu Cheng, Ming Shien Huang, Shih Hsiang Natl Cent Univ Dept Business Adm 300 Jhongda Rd Jhongli 32001 Taoyuan County Taiwan Ming Chi Univ Technol Dept Ind Engn & Management New Taipei 24301 Taiwan

ISBN: (数字)9783319238623

ISBN: (纸本)9783319238623;9783319238616

In data mining, association rules can be shown when customers buy products, which products will be purchased at the same time. Scholars use this feature to develop market basket analysis to formulate marketing strategies for business. As we know, the data are changing all the time. When new data generate, the old data will be replaced. In the database, time become a very important attribute. And new data mining method have been proposed, called Generalized Sequential patterns (GSP). GSP uses time stamp to find the product portfolio with sequential patterns. However, the GSP parameter is user-defined. The result of the operation may be unstable, because of the parameter setting incorrectly. Tuning the parameters used in this study combined GSP and Genetic Algorithm (GA) to improve the result continuously, to find the appropriate parameters. In the experiment, we use a medium-sized supermarket verify the results and found that after comparing with random input parameters, the parameters of the proposed method found significantly better than a random set of parameters.

关键词： Sequential pattern mining Generalized sequential patterns Genetic algorithm

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2015 international conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials, ICSTM 2015 - Proceedings

2015 International Conference on Smart Technologies and Mana...

引用

3rd international conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials, ICSTM 2015

ISBN: (纸本)9781479998555

The proceedings contain 114 papers. The topics discussed include: named entity recognition for malayalam language: a CRF based approach;an approach to identify subject specific human emotions;contemporary semantic search using natural language processing;DD-SARP: dynamic data secure anonymous routing protocol for MANETs in attacking environments;question answering system: a survey;authentication of MAV communication using Caesar cipher cryptography;RMCHS: ridge method based cluster head selection for energy efficient clustering hierarchy protocol in WSN;comparative analysis of machine learning algorithms along with classifiers for network intrusion detection;and IMMIX-intrusion detection and prevention system.

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Prequential AUC for classifier evaluation and drift detection in evolving data streams 3

Prequential AUC for classifier evaluation and drift detectio...

引用

3rd international Workshop on New Frontiers in mining Complex patterns, NFMCP 2014 held in Conjunction with European conference on machine learning and Principles and Practice of Knowledge Discovery in databases, ECML-PKDD 2014

作者： Brzezinski, Dariusz Stefanowski, Jerzy Institute of Computing Science Poznan University of Technology ul. Piotrowo 2 Poznan60–965 Poland

ISBN: (纸本)9783319178752

Detecting and adapting to concept drifts make learning data stream classifiers a difficult task. It becomes even more complex when the distribution of classes in the stream is imbalanced. Currently, proper assessment of classifiers for such data is still a challenge, as existing evaluation measures either do not take into account class imbalance or are unable to indicate class ratio changes in time. In this paper, we advocate the use of the area under the ROC curve (AUC) in imbalanced data stream settings and propose an efficient incremental algorithm that uses a sorted tree structure with a sliding window to compute AUC using constant time and memory. Additionally, we experimentally verify that this algorithm is capable of correctly evaluating classifiers on imbalanced streams and can be used as a basis for detecting changes in class definitions and imbalance ratio. © Springer international Publishing Switzerland 2015.

关键词： Trees (mathematics)

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Heart rate variability indicating stress visualized by correlations plots 3

Heart rate variability indicating stress visualized by corre...

引用

3rd international Work-conference on Bioinformatics and Biomedical Engineering, IWBBIO 2015

作者： Scherz, Wilhelm Daniel Ortega, Juan Antonio Madrid, Natividad Martínez Seepold, Ralf HTWG Konstanz Brauneggerstr. 55 Konstanz78462 Germany Universidad de Sevilla Avda. Reina Mercedes s/n Sevilla41012 Spain University Reutlingen Alteburgstraße 150 Reutlingen72762 Germany

ISBN: (纸本)9783319164793

Stress is recognized as a factor of predominant disease and in the future the costs for treatment will increase. The presented approach tries to detect stress in a very basic and easy to implement way, so that the cost for the device and effort to wear it remain low. The user should benefit from the fact that the system offers an easy interface reporting the status of his body in real time. In parallel, the system provides interfaces to pass the obtained data forward for further processing and (professional) analyses, in case the user agrees. The system is designed to be used in every day’s activities and it is not restricted to laboratory use or environments. The implementation of the enhanced prototype shows that the detection of stress and the reporting can be managed using correlation plots and automatic pattern recognition even on a very light-weighted microcontroller platform. © Springer international Publishing Switzerland 2015.

关键词： pattern recognition

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Supervised Context Classification Methods for an Industrial machinery

Supervised Context Classification Methods for an Industrial ...

引用

3rd international conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated conference on Computer Science and Information Systems (FedCSIS)

作者： Kalisch, Mateusz Silesian Tech Univ Inst Fundamentals Machinery Design Ul Konarskiego 18a PL-44100 Gliwice Poland

ISBN: (纸本)9788360810668

The paper describes a method of supervised context classification for an industrial machinery. The main objective of this study is to compare single and ensemble classifiers in order to classify groups of contexts which are based on an operating state of the device. The applied research was conducted with the assumption that only classic and well-practised classification methods would be adopted. The comparison study was carried out using real data recorded from an industrial machinery working underground in a mine in Poland. The achieved results confirm the effectiveness of the proposed approach and also show its limitations.

关键词： learning (artificial intelligence) machinery mining mining equipment pattern classification production engineering computing Poland ensemble classifiers industrial machinery mine supervised context classification methods Accuracy Bayes methods Context Decision trees Fault detection machinery Mathematical model

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A Method for Building a Labeled Named Entity recognition Corpus Using Ontologies 1

引用

3rd international conference on Computer Science, Applied Mathematics and Applications (ICCSAMA)

作者： Ngoc-Trinh Vu Van-Hien Tran Thi-Huyen-Trang Doan Hoang-Quynh Le Mai-Vu Tran Vietnam Natl Univ Hanoi Univ Engn & Technol Knowledge Technol Lab Hanoi Vietnam Vietnam Natl Oil & Gas Grp Vietnam Petr Inst Hanoi Vietnam

ISBN: (数字)9783319179964

ISBN: (纸本)9783319179964;9783319179957

Building a labeled corpus which contains sufficient data and good coverage along with solving the problems of cost, effort and time is a popular research topic in natural language processing. The problem of constructing automatic or semi-automatic training data has become a matter of the research community. For this reason, we consider the problem of building a corpus in phenotype entity recognition problem, classs-specific feature detectors from unlabeled data based on over 10260 unique terms (more than 15000 synonyms) describing human phenotypic features in the Human Phenotype Ontology (HPO) and about 9000 unique terms (about 24000 synonyms) of mouse abnormal phenotype descriptions in the Mammalian Phenotype Ontology. This corpus evaluated on three corpora: Khordad corpus, Phenominer 2012 and Phenominer 2013 corpora with Maximum Entropy and Beam Search method. The performance is good for three corpora, with F-scores of 31.71% and 35.77% for Phenominer 2012 corpus and Phenominer 2013 corpus;78.36% for Khordad corpus.

关键词： Named entity recognition Phenotype machine learning Biomedical ontology

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The prediction of fatigue using speech as a biosignal 1

引用

3rd international conference on Statistical Language and Speech Processing, SLSP 2015

作者： Baykaner, Khan Huckvale, Mark Whiteley, Iya Ryumin, Oleg Andreeva, Svetlana Speech Hearing and Phonetic Sciences UCL London United Kingdom Centre for Space Medicine UCL Dorking Surrey United Kingdom Gagarin Cosmonaut Training Centre Star City Russia

ISBN: (数字)9783319257891

ISBN: (纸本)9783319257884

Automatic systems for estimating operator fatigue have application in safety-critical environments. We develop and evaluate a system to detect fatigue from speech recordings collected from speakers kept awake over a 60-hour period. A binary classification system (fatigued/not-fatigued) based on time spent awake showed good discrimination, with 80 % unweighted accuracy using raw features, and 90 % with speaker-normalized features. We describe the data collection, feature analysis, machine learning and cross-validation used in the study. Results are promising for real-world applications in domains such as aerospace, transportation and mining where operators are in regular verbal communication as part of their normal working activities. © Springer international Publishing Switzerland 2015.

关键词： learning systems

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A Direct Method for Determining the Lower Convex Hull of a Finite Point Set in 3D 1

引用

3rd international conference on Computer Science, Applied Mathematics and Applications (ICCSAMA)

作者： Thanh An Phan Thanh Giang Dinh Vietnam Acad Sci & Technol Inst Math Hanoi Vietnam Univ Lisbon Inst Super Tecn CEMAT Lisbon Portugal Vinh Univ Dept Math Vinh City Vietnam

ISBN: (数字)9783319179964

ISBN: (纸本)9783319179964;9783319179957

Determining the convex hull, its lower convex hull, and Voronoi diagram of a point set is a basic operation for many applications of pattern recognition, image processing, and data mining. To date, the lower convex hull of a finite point set is determined from the entire convex hull of the set. There arises a question "How can we determine the lower convex hull of a finite point set without relying on the entire convex hull?" In this paper, we show that the lower convex hull is wrapped by lower facets starting from an extreme edge of the lower convex hull. Then a direct method for determining the lower convex hull of a finite point set in 3D without the entire convex hull is presented. The actual running times on the set of random points (in the uniform distribution) show that our corresponding algorithm runs significantly faster than the incremental convex hull algorithm and some versions of the gift-wrapping algorithm.

关键词： Convex Hull Extreme Edge Gift-wrapping Algorithm Lower Convex Hull pattern recognition Voronoi Diagram

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To optimize graph based power iteration for big data based on MapReduce paradigm 3rd

To optimize graph based power iteration for big data based o...

引用

3rd international conference on mining Intelligence and Knowledge Exploration, MIKE 2015

作者： Jayalatchumy, Dhanapal Thambidurai, Perumal Department of CSE PKIET Karaikal India PKIET Karaikal India

ISBN: (纸本)9783319268316

The next big thing in the IT world is Big data. The values generated from storing and processing of Big data cannot be analyzed using traditional computing techniques. The main aim of this paper is to design a scalable machine learning algorithm to scaleup and speedup clustering algorithm without losing its accuracy. Clustering using power iteration is fast and scalable. However, it requires matrix computation which makes the algorithm infeasible for Big data. Moreover, power method converges slowly based on eigen vector. Hence, in this paper an investigation is done on convergence factor by applying a modified constraint that minimizes the computational cost by making the algorithm converge quickly. MapReduce parallel environment for Big data is verified for the proposed algorithm using different sizes of datasets with different nodes in the cluster selecting speedup, scalability, and efficiency as the indicators. The performance of the proposed algorithm has been shown with respect to the execution time and the number of nodes. The results show that the proposed method is feasible and valid. It improves the overall performance and efficiency of the algorithm that can meet the needs of large scale processing. © Springer international Publishing Switzerland 2015.

关键词： MapReduce

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