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Enhanced Tissue-Specific Molecular pattern Extraction Via Recursive Maximum Margin Criterion

Enhanced Tissue-Specific Molecular Pattern Extraction Via Re...

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3rd international conference on Civil and Architecture Engineering (ICCAE’2014);3rd international conference on Automation, Robotics and Mechanical Engineering (ICAMR’2014);3rd international conference on Machine Learning and Computer Science (IMLCS’2014);3rd international conference on Management, Humanity and Economics (ICMHE’2014);3rd international conference on Power, Control and VLSI Engineering (ICPCVE’2014)

作者： Kirill A.Veselkov Reza Mirnezami Zoltan Takats the Section of Computational and Systems Medicine at Imperial College London Sir Alexander Fleming Building the section of Biosurgery and Surgical Technology at Imperial College London 10 th Floor QEQM BuildingSt Mary's Hospital

Mass Spectrometry Imaging (MSI) is a rapidly advancing bioanalyitical approach that enables the simultaneous measurement of thousands of molecular species from intact tissue sections in a spatially resolved manner. It provides the opportunity to develop a fully automated chemical histology approach for accurate tissue classification. Such "machine-learned" tissue identification platforms require efficient and robust extraction of tissue-specific discriminating molecular ion patterns. Here, we present a comparative analysis of several supervised feature extraction methods and propose the use of a Recursive Maximum Margin Criterion (RMMC) method for enhanced extraction of tissue-specific discriminating molecular patterns.

关键词： Biomedical computing, dimensionality reduction, imaging mass spectrometry, pattern recognition, supervised feature extraction.

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Face recognition Using Local Ternary pattern and Booth's Algorithm

Face Recognition Using Local Ternary Pattern and Booth's Alg...

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international conference on Eco-friendly Computing and Communication Systems (ICECCS)

作者： Abdullah Gubbi Mohammad Fazle Azeem Nishatbanu Z.H. Nayakwadi Dept of E & C P.A. College of Engnineering Mangalore Karnataka India EE Dept. AMU Aligarh India Dept of Computer science Muscat Sultanate of Oman

In the literature of face recognition many methods have been proposed which extract local texture features for robust pattern classification. But for final computation of the feature the information about central pixel is not taken into account. In this paper, we propose a novel method which utilizes Local Ternary pattern and Booth's Algorithm techniques to capture the local face features, which utilize central pixel for computation of the feature. Face images are spatially varied and classification works better with local descriptors, a Non-overlapping block wise processing is done on image to limit the features. The Support Vector Machine (SVM) and KNN classifier with proposed similarity measure is used for face classification. Finally, ROC and CMC are plotted for analysis of the system. Experiments are conducted on ORL and faces94 datasets demonstrates that the proposed method has better classification accuracy than previously proposed methods.

关键词： Face recognition Databases Support vector machines Feature extraction Face Principal component analysis

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Towards efficient semantically enriched complex event processing and pattern matching (position paper) 3

Towards efficient semantically enriched complex event proces...

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3rd international Workshop on Ordering and Reasoning, OrdRing 2014, Co-located with the 13th international Semantic Web conference, ISWC 2014

作者： Gillani, Syed Picard, Gauthier Laforest, Frédérique Zimmermann, Antoine Institute Henri Fayol EMSE Saint Etienne France Telecom Saint Etienne Université Jean Monnet Saint Etienne France

Management and recognition of event patterns is becoming thoroughly ingrained in many application areas of Semantically enabled Complex Event Processing (SCEP). However, the reliance of state-of-the-art technologies on relational and rdF triple model without having the notion of time has severe limitations. This restricts the system to employ temporal reasoning at rdF level and use historical events to predict new situations. Additionally, the semantics of traditional query languages makes it quite challenging to implement distributed event processing. In our vision, SCEP needs to consider rdF as a first class citizen and should implement parallel and distributed processing to deal with large amount of data streams. In this paper, we discuss various challenges and limitations of state-of-the-art technologies and propose a possible solution to extend rdF data model for stream processing and pattern matching. Furthermore, we describe a high-level query design that enables efficient parallel and distributed pattern matching through query rewriting.

关键词： pattern matching

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Controlling software design of 2D scanning mirror in infrared detecting and tracking system

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2013 3rd international conference on Machinery Electronics and Control Engineering, ICMECE 2013

作者： Liu, Xiang Yan Dai, Xiao Bing He, Xu Dong Institute for Pattern Recognition and Artificial Intelligence School of Automation Huazhong University of Science and Technology Wuhan 430074 China School of Mechanical Engineering and Automation Wuhan University of Textile Wuhan 430073 China

ISBN: (纸本)9783037859032

Firstly, this paper introduced infrared detecting and tracking system (IR D&T System) and several commonly used scanning solutions in IR D&T System briefly. Secondly, it analyzed how 2D scanning mirror works and PID (Proportion, Integration and Differentiation) algorithm. Thirdly, it introduced commands format and controlling method of the 2D scanning mirror used in image-spectrum integrated instrument developed by our group. And then it designed controlling software of the 2D scanning mirror using its secondary development package (SDK) and VC++. The software communicates with 2D scanning mirror through serial port. The MSCOMM serial communication control is used in communication software design. The controlling software is integrated to software of image-spectrum integrated instrument successfully and experiment results verified the correctness of controlling algorithm and engineering usability of the software. © (2014) Trans Tech Publications, Switzerland.

关键词： Software design

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Finding the optimal sequence of features selection based on reinforcement learning

Finding the optimal sequence of features selection based on ...

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IEEE international conference on Cloud Computing and Intelligence Systems (CCIS)

作者： Song Bi Lei Liu Cunwu Han Dehui Sun The Beijing Key Laboratory of Fieldbus Technology and Automation North China University of Technology Beijing China

ISBN: (纸本)9781467369541

This paper proposes a method for generating an optimal feature selecting sequence which is cost-effective for pattern classification. The sequence describes the order that feature selects for the process like classification. We model the procedure of feature selecting using Markov decision process (MDP), and use dynamic programming (DP) to learn a strategy to generate the orders only with the feedback of circumstance. To simplify the problem, we design a simple test scene that classifying three objects, whose values of synthetic features are generated randomly, into three classes. The results of experiments show that our method can reduce the computational time of extracting features.

关键词： Feature extraction Learning (artificial intelligence) Computational efficiency Object recognition pattern classification Service robots Robot sensing systems

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Visual feature-based violent video detection

Visual feature-based violent video detection

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IEEE international conference on Cloud Computing and Intelligence Systems (CCIS)

作者： Xin Ji Ou Wu Chenlong Wang Jinfeng Yang College of Aviation Automation Civil Aviation University of China Tianjin China Chinese Academy of Sciences National Laboratory of Pattern Recognition Beijing China School of Software Beijing Jiaotong University Beijing China

ISBN: (纸本)9781467369541

In this paper, a novel violent video detection scheme is presented based on visual views. The violent segment is detected by using motion angle, motion intensity, shot & explosion and blood analysis. In addition, in order to improve the compute efficiency and time savings Hidden Information SVM is used. Experimental result shows that the proposed method is effective in violent video detection.

关键词： Blood Explosions Support vector machines Feature extraction Visualization Motion pictures Image color analysis

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Universalization of narrow methods: Case study on autoencoders

Universalization of narrow methods: Case study on autoencode...

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IEEE international conference on Cloud Computing and Intelligence Systems (CCIS)

作者： Alexey Potapov Vita Batishcheva Shuchao Pang Mechanics and Optics National Research University of Information Technology St. Petersburg Russia Petersburg State University St. Petersburg Russia College of Computer Science and Technology Jilin University Changchun China

The problem of bridging the gap between efficient but narrow methods of machine learning, and universal but inefficient methods was considered. Our main claim, which is methodologically important to the field of Artificial General Intelligence (AGI), is that neither narrow nor basic universal methods are sufficient for AGI. This claim was illustrated on example of pattern recognition task using stacked autoencoders and their two extensions with more exhaustive search and richer solution space. These three types of classifiers were evaluated on the base of a criterion that account for both error rate and training time. Depending on the urgency of the task to be solved, less or more universal methods appeared to be better. Thus, AGI might start with narrow methods, but should be able to perform their “universalization” (i.e. extension of the model space possibly up to Turing-complete space if it is appropriate in a certain situation).

关键词： Training Simulated annealing Error analysis Computational modeling Logistics pattern recognition Artificial intelligence

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Keynote Speech: Constructing Fuzzy Rule Bases for pattern recognition

Keynote Speech: Constructing Fuzzy Rule Bases for Pattern Re...

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2013 3rd international conference on Education and Education Management(EEM 2013)

作者： Gerald Schaefer Department of Computer Science Loughborough University

pattern recognition problems occur in many domains and consequently well performing classification algorithms are highly sought after. In my talk, I will focus on a particular group of classifiers that generate rule bases consisting of a set of fuzzy if‐then rules. The antecedent part of a rule characterises the input features using fuzzy sets, while the consequent part is established in a learning stage. Starting with a basic fuzzy classifier I will show that, through a simple modification, it can be turned into a cost sensitive classification method, that classification performance can be improved through an error correction learning approach, and that a small yet powerful rule base can be generated through an optimisation approach based on genetic algorithms.

关键词： Constructing Fuzzy Rule Bases for pattern recognition Keynote Speech Fuzzy

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Constructing Fuzzy Rule Bases for pattern recognition

Constructing Fuzzy Rule Bases for Pattern Recognition

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2013 3rd international conference on Education and Education Management(EEM 2013)

作者： Gerald Schaefer Department of Computer Science Loughborough University

关键词： Constructing Fuzzy Rule Bases for pattern recognition Fuzzy

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Abstract channels and their robust information-leakage ordering

Abstract channels and their robust information-leakage order...

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3rd international conference on Principles of Security and Trust, POST 2014 - Held as Part of the European Joint conferences on Theory and Practice of Software, ETAPS 2014

作者： McIver, Annabelle Morgan, Carroll Smith, Geoffrey Espinoza, Barbara Meinicke, Larissa Macquarie University Australia University of New South Wales NICTA Australia Florida International University United States University of Queensland Australia

ISBN: (纸本)9783642547911

The observable output of a probabilistic system that processes a secret input might reveal some information about that input. The system can be modelled as an information-theoretic channel that specifies the probability of each output, given each input. Given a prior distribution on those inputs, entropy-like measures can then quantify the amount of information leakage caused by the channel. But it turns out that the conventional channel representation, as a matrix, contains structure that is redundant with respect to that leakage, such as the labeling of columns, and columns that are scalar multiples of each other. We therefore introduce abstract channels by quotienting over those redundancies. A fundamental question for channels is whether one is worse than another, from a leakage point of view. But it is difficult to answer this question robustly, given the multitude of possible prior distributions and leakage measures. Indeed, there is growing recognition that different leakage measures are appropriate in different circumstances, leading to the recently proposed g-leakage measures, which use gain functions g to model the operational scenario in which a channel operates: the strong g-leakage pre-order requires that channel A never leak more than channel B, for any prior and any gain function. Here we show that, on abstract channels, the strong g-leakage pre-order is antisymmetric, and therefore a partial order. It was previously shown [1] that the strong g-leakage ordering is implied by a structural ordering called composition refinement, which requires that A = BR, for some channel R;but the converse was not established in full generality, left open as the so-called Coriaceous Conjecture. Using ideas from [2], we here confirm the Coriaceous Conjecture. Hence the strong g-leakage ordering and composition refinement coincide, giving our partial order both structural- and leakage-testing significance. © 2014 Springer-Verlag.

关键词： Information theory

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