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检索条件"任意字段=14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013"

共 80 条记录，以下是41-50 订阅

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16th international conference on intelligent data engineering and automated learning (ideal)

作者： Ferchichi, Abdelwaheb Gouider, Mohamed Salah Ben Said, Lamjed Univ Tunis SOIE Ave Liberte Le Bardo 2000 Tunisia

ISBN: (纸本)9783319248349;9783319248332

Large amount of data generated by sensors, and increased use of privacy-preserving techniques have led to an increasing interest in mining uncertain data streams. Traditional distance measures such as the Euclidean distance do not always work well for uncertain data streams. In this paper, we present EVIDIST, a new distance measure for uncertain data streams, where uncertainty is modeled as sample observations at each time slot. We conduct an extensive experimental evaluation of EVIDIST (Evidential Distance) on the 1-NN classification task with 15 real datasets. the results show that, compared with Euclidean distance, EVIDIST increases the classification accuracy by about 13 % and is also far more resilient to error.

关键词： data mining Distance measure Similarity Uncertain data streams

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Deep learning on Natural Viewing Behaviors to Differentiate Children with Fetal Alcohol Spectrum Disorder

Deep Learning on Natural Viewing Behaviors to Differentiate ...

引用

14th international conference on intelligent data engineering and automated learning (ideal)

作者： Tseng, Po-He Paolozza, Angelina Munoz, Douglas P. Reynolds, James N. Itti, Laurent Univ So Calif Dept Comp Sci Los Angeles CA 90089 USA Queens Univ Ctr Neurosci Studies Kingston ON K7L 3N6 Canada

ISBN: (纸本)9783642412783;9783642412776

Computational models of visual attention have attracted strong interest by accurately predicting how humans deploy attention. However, little research has utilized these models to detect clinical populations whose attention control has been affected by neurological disorders. We designed a framework to decypher disorders from the joint analysis of video and patients' natural eye movement behaviors (watch television for 5 minutes). We employ convolutional deep neural networks to extract visual features in real-time at the point of gaze, followed by SVM and Adaboost to classify typically developing children vs. children with fetal alcohol spectrum disorder (FASD), who exhibit impaired attentional control. the classifier achieved 74.1% accuracy (ROC: 0.82). Our results demonstrate that there is substantial information about attentional control in even very short recordings of natural viewing behavior. Our new method could lead to high-throughput, low-cost screening tools for identifying individuals with deficits in attentional control.

关键词： deep learning sparse representation eye movement natural scenes clinical populations

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intelligent Wristbands for the Automatic Detection of Emotional States for the Elderly 19th

Intelligent Wristbands for the Automatic Detection of Emotio...

引用

19th international conference on intelligent data engineering and automated learning (ideal)

作者： Rincon, Jaime A. Costa, Angelo Novais, Paulo Julian, Vicente Carrascosa, Carlos Univ Politecn Valencia D Sistemas Informat & Comp Valencia Spain Univ Minho Algoritmi Ctr Dept Informat Braga Portugal

ISBN: (纸本)9783030034931;9783030034924

Over the last few years, research on computational intelligence is being conducted to detect emotional states of people. this paper proposes the use of intelligent wristbands for the automatic detection of emotional states to develop an application which allows to monitor older people in order to improve their quality of life. the paper describes the hardware design and the cognitive module that allows the recognition of the emotional states. the proposed wristband also integrates a camera that improves the emotion detection.

关键词： Wearable devices Emotional models Ambient assisted living

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Users Intention Based on Twitter Features Using Text Analytics 1

引用

20th international conference on intelligent data engineering and automated learning (ideal)

作者： Mishael, Qadri Ayesh, Aladdin Yevseyeva, Iryna De Montfort Univ Sch Comp Sci & Informat Leicester Leics England

ISBN: (数字)9783030336073

ISBN: (纸本)9783030336073;9783030336066

Online Social networks are widely used in current times. In this paper, we investigate twitter posts to identify features that feed in intention mining calculation. the posts features are divided into three sets: tweets textual features, users features, and network contextual features. In this paper, our focus is on tweets analysing textual features. As a result of this paper, we were able to create intentions profiles for 2960 users based on textual features. the prediction accuracy of three classifiers was compared for the data set, using ten intention categories to test the features. the best accuracy was achieved for SVM classifier. In the future, we plan to include user and network contextual features aiming at improving the prediction accuracy.

关键词： Intention mining Online Social Network Feature selection Machine learning

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Investigating the Behaviour of Radial Basis Function Networks in Regression and Classification of Geospatial data

Investigating the Behaviour of Radial Basis Function Network...

引用

11th international conference on intelligent data engineering and automated learning

作者： Guidali, Andrea Binaghi, Elisabetta Guglielmin, Mauro Pascale, Marco Univ Insubria Dept Comp Sci & Commun Via Mazzini 5 I-21100 Varese Italy Univ Insubria Dept Structural & Funct Biol I-21100 Varese Italy

ISBN: (纸本)9783642153808

this work investigates learning and generalisation capabilities of Radial Basis Function Networks used to solve function regression and classification tasks in the environmental context. In particular RBFN is applied to solve the problem of snow cover thickness estimation in which critical aspects such as minimal training condition, weak pattern description and inconsistency among data arise. the RBFN shows good performances and high flexibility in coping with regression, hard and soft classifications which are complementary tasks in the analysis of complex environmental phenomena.

关键词： Radial Basis Function Networks Regression Classification Fuzzy sets Geospatial data

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A Study of Fuzzy Clustering to Archetypal Analysis 19th

A Study of Fuzzy Clustering to Archetypal Analysis

引用

19th international conference on intelligent data engineering and automated learning (ideal)

作者： Mendes, Goncalo Sousa Nascimento, Susana Univ Nova Lisboa Dept Comp Sci Fac Ciencias & Tecnol Lisbon Portugal Univ Nova Lisboa NOVA LINCS Fac Ciencias & Tecnol Lisbon Portugal

ISBN: (纸本)9783030034962;9783030034955

this paper presents a comparative study between a method for fuzzy clustering which retrieves pure individual types from data, the fuzzy clustering with proportional membership (FCPM), and an archetypal analysis algorithm based on Furthest-Sum approach (FS-AA). A simulation study comprising 82 data sets is conducted with a proper data generator, FCPM-DG, whose goal is twofold: first, to analyse the ability of archetypal clustering algorithm to recover Archetypes from data of distinct dimensionality;second, to analyse robustness of FCPM and FS-AA algorithms to outliers. the effectiveness of these algorithms are yet compared on clustering 12 diverse benchmark data sets from machine learning. the evaluation conducted with five primer unsupervised validation indices shows the good quality of the clustering solutions.

关键词： Archetypal analysis Fuzzy clustering Synthetic multidimensional data Fuzzy validation indices

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LBP and Machine learning for Diabetic Retinopathy Detection

引用

15th international conference on intelligent data engineering and automated learning (ideal)

作者： de la Calleja, Jorge Tecuapetla, Lourdes Auxilio Medina, Ma Barcenas, Everardo Urbina Najera, Argelia B. Univ Politecn Puebla Mexico City 72640 DF Mexico

ISBN: (纸本)9783319108407;9783319108391

Diabetic retinopathy is a chronic progressive eye disease associated to a group of eye problems as a complication of diabetes. this disease may cause severe vision loss or even blindness. Specialists analyze fundus images in order to diagnostic it and to give specific treatments. Fundus images are photographs taken of the retina using a retinal camera, this is a noninvasive medical procedure that provides a way to analyze the retina in patients with diabetes. the correct classification of these images depends on the ability and experience of specialists, and also the quality of the images. In this paper we present a method for diabetic retinopathy detection. this method is divided into two stages: in the first one, we have used local binary patterns (LBP) to extract local features, while in the second stage, we have applied artificial neural networks, random forest and support vector machines for the detection task. Preliminary results show that random forest was the best classifier with 97.46% of accuracy, using a data set of 71 images.

关键词： machine learning local binary patterns medical image analysis

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Sample Size Issues in the Choice between the Best Classifier and Fusion by Trainable Combiners

引用

15th international conference on intelligent data engineering and automated learning (ideal)

作者： Raudys, Sarunas Fumera, Giorgio Raudys, Aistis Pillai, Ignazio Vilnius State Univ Fac Math & Informat Naugarduko St 24 LT-03225 Vilnius Lithuania Univ Cagliari Dept Elect & Elect Eng I-09123 Cagliari Italy

ISBN: (纸本)9783319108407;9783319108391

We consider an open issue in the design of pattern classifiers, i.e., choosing between the best classifier among a given ensemble, and combining all the available ones using a trainable fusion rule. While the latter choice can in principle outperform the former, their actual effectiveness is affected by small sample size problems. this raises the need of investigating under which conditions one choice is better than the other one. We provide a first contribution, by deriving an analytical expressions of the expected error probability of best classifier selection, and by comparing it with the one of a well known linear fusion rule, implemented with the Fisher linear discriminant.

关键词： data dimensionality sample size complexity collective decision expert fusion accuracy classification

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Integration of strategies based on relevance feedback into a tool for the retrieval of mammographic images

引用

7th international conference on intelligent data engineering and automated learning (ideal 2006)

作者： Fornells, A. Golobardes, E. Vilasis, X. Marti, J. Ramon Llull Univ Res Grp Intelligent Syst Barcelona 08022 Spain Ramon Llull Univ Automat & Control Sect Barcelona 08022 Spain Univ Gieona Comp Vis & Robot Grp Girona 17071 Spain

ISBN: (纸本)3540454853

the incidence of breast cancer varies greatly among countries, but statistics show that every year 720,000 new cases will be diagnosed world-wide. However, a high percentage of these cases can be 100% healed if they are detected in early stages. Because symptoms are not visible as far as advanced stages, it makes the treatments more aggressive and also less efficient. therefore, it is necessary to develop new strategies to detect the formation in early stages. We have developed a tool based on a Case-Based Reasoning kernel for retrieving mammographic images by content analysis. One of the main difficulties is the introduction of knowledge and abstract concepts from domain into the retrieval process. For this reason, the article proposes integrate the human experts perceptions into it by means of an interaction between human and system using a Relevance Feedback strategy. Furthermore, the strategy uses a Self-Organization Map to cluster the memory and improve the time interaction.

关键词： breast cancer bioinformatics tools Relevance Feedback knowledge discovery & retrieval data Case-Based Reasoning Self-Organization Map

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Automatic Validation of Flowmeter data in Transport Water Networks: Application to the ATLLc Water Network

引用

15th international conference on intelligent data engineering and automated learning (ideal)

作者： Garcia, Diego Quevedo, Joseba Puig, Vicenc Saludes, Jordi Espin, Santiago Roquet, Jaume Valero, Fernando UPC Adv Control Syst SAC Campus TerrassaRambla St Nebridi 10 Barcelona 08222 Spain ATLL Concessionaria Generalitat Catalunya S Sant E-08970 Barcelona Spain

ISBN: (纸本)9783319108407;9783319108391

In this paper, a methodology for data validation and reconstruction of flow meter sensor data in water networks is presented. the raw data validation is inspired on the Spanish norm (AENOR-UNE norm 500540). the methodology consists in assigning a quality level to data. these quality levels are assigned according to the number of tests that data have passed. the methodology takes into account not only spatial models but also temporal models relating the different sensors. the methodology is applied to real-data acquired from the ATLLc Water Network. the results demonstrate the performance of the proposed methodology in detecting errors in measurements and in reconstructing them.

关键词： Flowmeters

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