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No Reference Image Quality Assessment Using Block Based Features and Artificial Neural Network

No Reference Image Quality Assessment Using Block Based Feat...

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4th ObCom international conference on Recent Trends in Computing, Communication and Information Technology

作者： Bagade, J. V. Dandawate, Y. H. Singh, Kulbir VIIT Dept Informat Technol Pune 48 Maharashtra India VIIT Dept Elect & Telecommun Pune 48 Maharashtra India Thapar Univ Dept Elect & Telecommun Patiala 147004 Punjab India

ISBN: (纸本)9783642292156

In last decade, there has been explosive growth in multimedia technologies and its applications. For fast transmission, compression of image data is necessary. Due to this images are lead to distortion like blocking, ringing and blurring. the channel noise also gets introduced if transmitted over communication channel. Due to the distortion, image quality assessment plays an important role. In majority applications, original image is not available for reference. In such application, the metric which evaluates quality without reference is called "no reference quality" metric. Since human perception has limitation and in automated quality assessment application there is an immense need of developing no reference quality assessment framework. In this paper, we propose no reference image quality assessment scheme using the machine learning approach. Based on the degradation such as blocking, ringing artifacts, the related features such as average absolute difference between in-block image sample and zero-crossing rate, spatial frequency measure and spatial activity measures are computed for JPEG gray scale images. the earlier related work uses such parameters and mathematical predictors. Many time the correlation of extracted features, DMOS and output of predictor do not present correct assessment. In the proposed approach, properly trained back propagation artificial neural network with MOS as target is used. the result indicates that accuracy of quality assessment is better.

关键词： Image Quality Assessment Artificial Neural Networks No Reference quality Compression artifacts blocking and ringing artifacts block based features quality score machine learning approach back propagation neural network Mean Opinion Score

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Adaptive Splitting and Selection Algorithm for Classification of Breast Cytology Images

Adaptive Splitting and Selection Algorithm for Classificatio...

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4th international conference on Computational Collective Intelligence - Technologies and applications (ICCCI)

作者： Krawczyk, Bartosz Filipczuk, Pawel Wozniak, Michal Wroclaw Univ Technol Dept Syst & Comp Networks PL-50370 Wroclaw Poland Univ Zielona Gora Inst Control Computat Engn Zielona Gora Poland

ISBN: (纸本)9783642346309

the article presents an application of Adaptive Splitting and Selection (AdaSS) classifier in the medical decision support system for breast cancer diagnosis. Apart from the canonical malignant versus nonmalignant problem we introduced a third class - fibroadenoma, which is a benign tumor of the breast often occurring in women. Medical images are delivered by the Regional Hospital in Zielona Gora, Poland. For the process of segmentation and feature extraction a mixture of Gaussians is used. AdaSS is a combined classifier, based on an evolutionary splitting of feature space into clusters. To increase the overall accuracy of the classification we propose to add a feature selection step to the optimization criterion of the native AdaSS algorithm. Experimental investigation proves that the introduced method is more accurate than previously used classification approaches.

关键词： machine learning multiple classifier system clustering and selection evolutionary algorithm breast cancer computer-aided diagnostics

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Development of the Web application that create a handmade picture book with originality

Development of the Web application that create a handmade pi...

引用

2012 4th IEEE international conference on Digital Game and Intelligent Toy Enhanced learning, DIGITEL 2012

作者： Funabashi, Naoya Fujimoto, Takayuki Graduate School of Engineering Toyo University Kujirai2100 Kawagoe-City Saitama 350-8585 Saitama Japan

ISBN: (纸本)9780769546636

In recent years, in recent years, in child-rearing, the education using a Picture Book attracts attention. However, a Picture Book is not cheap. Rather, the price of Picture Books is higher than other books. this is a bad point of a Picture Book. It is educationally worthy to give the child of infancy many Picture Books. However, the price of Picture Book is expensive, and there are not many homes which can purchase many Picture Books. Of course, saving of expense is possible if a Picture Book is made by itself. However, it is not easy. It is not only a problem of money. Infants are always asking for the stimulus. therefore, children demand one new Picture Book after another. A Picture Book cannot be forever offered to children. So, there is also business which makes an original Picture Book in recent years. It is very in fashion also as a gift. However, many of such Picture Books are the services chosen from the limited template or the limited material. that is, it cannot necessarily be said that originality is high. A Picture Book is an element indispensable to child-rearing and education. However, it is expensive. And a handmaid is difficult. In this research, we developed the "original Picture Book creation supporting system" which fulfilled two needs of "creating an original Picture Book" and "A Picture Book is got cheaply. " Even if our system does not have special capability or environment, anyone can create an original Picture Book for free easily. © 2012 IEEE.

关键词： web applications Creativity picture Child Child Rearing

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4th international conference on Human-Centered Software Engineering, HCSE 2016

4th International Conference on Human-Centered Software Engi...

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4th international conference on Human-Centered Software Engineering, HCSE 2016

ISBN: (纸本)9783642343469

the proceedings contain 28 papers. the special focus in this conference is on Human-Centered Software Engineering. the topics include: Human factors engineering as the methodological Babel fish;translating user needs into software design;improving software effort estimation using an expert-centred approach;a compositional model for gesture definition;a development process for usable large scale interactive critical systems;agile user experience development in a large software organization;Smartphone applications usability evaluation;methods towards API usability;a structural analysis of usability problem categories;requirements sensemaking using concept maps;towards conflict management in user interface composition driven by business needs;a model for assessing organizational learning in software development organizations;a personality based design approach using subgroup discovery;assessing use complexity of software;support for the application of creativity techniques in requirements engineering;exploring local cultural perspectives in user interface development in an Indian offshoring context;improving support for visual task modelling;lessons learned from evaluating the usability of mobile spreadsheet applications;ProtoTask, new task model simulator;the usage of usability techniques in scrum projects;visualizing sensor data and graphical controls based environment for user interface evaluation.

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RPig: A scalable framework for machine learning and advanced statistical functionalities

RPig: A scalable framework for machine learning and advanced...

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IEEE international conference on Cloud Computing Technology and Science (CloudCom)

作者： MingXue Wang Sidath B. Handurukande Mohamed Nassar Network Management Laboratory Ericsson Ireland Limited Ireland

In many domains such as Telecom various scenarios necessitate the processing of large amounts of data using statistical and machine learning algorithms. A noticeable effort has been made to move the data management systems into MapReduce parallel processing environments such as Hadoop and Pig. Nevertheless these systems lack the features of advanced machine learning and statistical analysis. Frame-works such as Mahout on top of Hadoop support machine learning but their implementations are at the preliminary stage. For example Mahout does not provide Support Vector machine (SVM) algorithms and it is difficult to use. On the other hand traditional statistical software tools such as R containing comprehensive statistical algorithms for advanced analysis are widely used. But such software can only run on a single computer and therefore it is not scalable. In this paper we propose an integrated solution RPig which takes the advantages of R (for machine learning and statistical analysis capabilities) and parallel data processing capabilities of Pig. the RPig framework offers a scalable advanced data analysis solution for machine learning and statistical analysis. Analysis jobs can be easily developed with RPig script in high level languages. We describe the design implementation and an eclipse-based RPigEditor for the RPig framework. Using application scenarios from the Telecom domain we show the usage of RPig and how the framework can significantly reduce the development effort. the results demonstrate the scalability of our framework and the simplicity of deployment for analysis jobs.

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ANN Based application of Pharmacogenetics to Personalized Cancer Treatment

ANN Based Application of Pharmacogenetics to Personalized Ca...

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the 2012 4th international conference on machine learning and Computing（ICMLC 2012）

作者： Bekir Karlik Emre Oztoprak Department of Computer Engineering of Mevlana University Konya Turkey Medicine Faculty of Mevlana University Konya Turkey

Artificial Neural Networks （ANN） may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications in biomedical *** is used in pharmaceutical （pharmacokinetic and pharmacogenetic） areas to model complex interactions and predict the nonlinear relationship between causal factors and response *** aim of this study is indicate a novel approach on application of pharmacogenetics to personalized cancer treatment using data of TPMT polymorphisms and ANN.

关键词： artificial neural networks personalized medicine pharmacogenetics TPMT drug cancer.

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An Improved Approach to Sentence Ordering For Multi-document Summarization

An Improved Approach to Sentence Ordering For Multi-document...

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the 2012 4th international conference on machine learning and Computing（ICMLC 2012）

作者： Tiedan Zhu 1 ,Xinxin Zhao 2 1 Beijing Institute of Technology 2 Beijing Institute of computer application Technology

While sentence ordering for single-document summarization can be determined from the ordering of sentences in the input article,this is not the case for multi-document summarization where summary sentences may be drawn from different input *** this paper,we propose the logical-closeness criterion,which can be used to measure the similarity between two *** on the logical-closeness,we propose an improved agglomerative algorithm to arrange the order of *** of our augmented algorithm shows an improvement of the ordering over other baseline strategies.

关键词： Sentence Ordering,Multi-document Summarization,Natural Language Processing

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Texture Image Segmentation using FCM

Texture Image Segmentation using FCM

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the 2012 4th international conference on machine learning and Computing（ICMLC 2012）

作者： Kanchan S.Deshmukh M.G.M’s College of Computer Sci.& IT NandedIndia

Texture analysis such as segmentation and classification plays a vital role in computer vision and pattern *** is widely applied to many areas such as industrial automation,bio-medical image processing and remote *** image segmentation system called "Colour Texture segmentation using fuzzy c-means clustering (CTSFCM)" is *** uses the perceptually uniform CIEL*U*V* colour space for *** speed up segmentation algorithm and reduce the computational complexity for clustering,prominent pixels are *** and their labels are automatically found out using Fuzzy c-means (FCM) clustering *** the proposed method fuzzy entropy is used to decide number of *** pixels are classified to relevant clusters based on minimum Euclidian distance.A post-processing filtering stage is applied to improve segmentation *** of the advantages of this method is that it does not need to specify the priori information to segment a colour region besides;there is no apparently distortion or colour change after *** results show that the system has desired ability for segmentation of colour images in a variety of vision *** application of the proposed method is *** effectiveness of proposed method has been demonstrated by various experiments.

关键词： Segmentation,Texture segmentation,Fuzzy colour image segmentation.

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application of Chaos theory and Data Mining to Seizure Detection of Epilepsy

Application of Chaos Theory and Data Mining to Seizure Detec...

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the 2012 4th international conference on machine learning and Computing（ICMLC 2012）

作者： Chien-Liang Chen Jenn-Long Liu Jhih-Yu Syu Dept.of Information Management Fortune Institute TechnologyKaohsiung 831Taiwan Dept.of Information Engineering I-Shou UniversityKaohsiung 840Taiwan Dept.of Information Management I-Shou UniversityKaohsiung 840Taiwan

this study applies Chaos theory to investigate the seizure detection of epilepsy with three groups of data （Groups H,S and E）,showing the electroencephalography （EEG） changes of *** three groups,Group H （normal state）,Group S （during seizures） and Group E （after seizures）,contain 100 series of EEG signals *** detected data are processed by chaotic theory to transform the signals to four parameters with Delay Time （τ）,Embedding Dimension （dm）,Correlation Dimension （CD） value,and Largest Lyapunov Exponent （LLE）.Furthermore,well-known classification software for data mining,termed See5 based on entropy theory,is used to find out the classification rules for the EEG signals of epilepsy patients.

关键词： Chaos theory Epilepsy Decision Tree Classification Rule

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An Overview of Hierarchical Temporal Memory:A New Neocortex Algorithm

An Overview of Hierarchical Temporal Memory:A New Neocortex ...

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4th international conference on Modelling,Identification and Control(ICMIC 2012)

作者： Xi Chen, Associate professor in the Institute of System engineer Huazhong University of Science & Technology, Image Processing Intelligent Control Key Laboratory of Education Ministry of China, Wu Hubei, China, 430074 Wei Wang, Candidate for Master of Institute of System engineering, Huazhong University of Science Technology, Image Processing and Intelligent Control Key Laborator Education Ministry of China Wei Li: Associate professor in the Department of Control Scienc Engineering, Image Processing and Intelligent Control Key Laborator Education Ministry of China

the overview presents the development and application of Hierarchical Temporal Memory (HTM). HTM is a new machine learning method which was proposed by Jeff Hawkins in 2005. It is a biologically inspired cognitive method based on the principle of how human brain works. the method invites hierarchical structure and proposes a memory-prediction framework, thus making it able to predict what will happen in the near future. this overview mainly introduces the developing process of HTM, as well as its principle, characteristics, advantages and applications in vision, image processing and robots movement, some potential applications by using HTM , such as thinking process, are also put forward.

关键词： hierarchical Bayesian network, spatial-temporal, memory-prediction, temporal sequence, pattern recognition.

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