Search Results - (((((((want OR fine) OR semantic) OR carter) OR cantor) OR anne) OR maarten) OR mantis) algorithms.

Acquisition and understanding of process knowledge using problem solving methods by Gómez-Pérez, José Manuel

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Optimization theory and related topics : Israel mathematical conference proceedings : a workshop in memory of Dan Butnariu, January 11-14, 2010, Haifa, Israel

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Life sciences, information sciences

Table of Contents: “…Semantics --…”
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Integrated systems engineering : a postprint volume from the IFAC Conference, Baden-Baden, Germany, 27-29 September 1994

Table of Contents: “…An Optimisation-Based Algorithm for Designing Free-Form Trajectories Under Various Constraints /…”
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When life is linear : from computer graphics to bracketology by Chartier, Timothy P.

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Design for embedded image processing on FPGAs by Bailey, Donald G. (Donald Graeme), 1962-

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Interactive displays : natural human interface technologies

Table of Contents: “…Gesture Detection Algorithm /…”
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Advances in Knowledge-Based and Intelligent Engineering and Information Systems by Frydman, Claudia

Table of Contents: “…Covers; Editorial advisory board; Guest editorial; Towards semantically-aided domain specific business process modeling; Topological and topical characterisation of Twitter user communities; Selection methods and diversity preservation in many-objective evolutionary algorithms; Towards a common and semantic representation of e-portfolios; Logical foundations of hierarchical model checking…”
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Artificial neural systems : principle and practice by Lorrentz, Pierre

Table of Contents: “…INTRODUCTIONDENSITY BASED ALGORITHMS: CLUSTERING ALGORITHMS; NATURE-BASED ALGORITHMS; Evolutionary Algorithm and Programming ; Genetic Algorithm; GA Operators; APPLICATIONS OF GENETIC ALGORITHM; NETWORK METHOD: EDGES AND NODES; MULTI-LAYERED PERCEPTRON; REAL-TIME APPLICATIONS OF STATE-OF-THE-ART ANN SYSTEMS; DEFINITION OF ARTIFICIAL NEURAL NETWORKS (ANN); Intelligence; An Artificial Neural Network (ANN) system; PERFORMANCE MEASURES; Receiver's Operating Characteristics (ROC); Hypothesis Testing; Chi-squared (Goodness-of-fit) Test; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES…”
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Communicating process architectures 2002. by World Occam And Transputer User Group. Technical Meeting (25th: 2002: University Of Reading, U. K.)

Table of Contents: “…Cover; Title page; Contents; Preface; Programme Committee; Papers; Semantics of prialt in Handel-C"! Acceptances, Behaviours and Infinite Activity in CSPP; HCSP: Imperative State and True Concurrency; Consolidating the Agreement Problem Protocol Verification Environment; On the Complexity of Buffer Allocation in Message Passing Systems; Java PastSet -- A Structured Distributed Shared Memory System; Synchronous Active Objects Introduce CSP's Primitives in Java; Configurable Collective Communication in LAM-MPI; Cache-Affinity Scheduling for Fine Grain Multithreading.…”
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Digital journalism, drones, and automation : the language and abstractions behind the news by Dowd, Cate

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3D Shape Analysis : Fundamentals, Theory and Applications. by Tabia, Hedi

Table of Contents: “…7.2 Problem Formulation7.3 Mathematical Tools; 7.4 Isometric Correspondence and Registration; 7.5 Nonisometric (Elastic) Correspondence and Registration; 7.6 Summary and Further Reading; 8 Semantic Correspondences; 8.1 Introduction; 8.2 Mathematical Formulation; 8.3 Graph Representation; 8.4 Energy Functions for Semantic Labeling; 8.5 Semantic Labeling; 8.6 Examples; 8.7 Summary and Further Reading; Part IV: Applications; 9 Examples of 3D Semantic Applications; 9.1 Introduction; 9.2 Semantics: Shape or Status; 9.3 Semantics: Class or Identity; 9.4 Semantics: Behavior; 9.5 Semantics: Position…”
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Mastering machine learning with scikit-learn : learn to implement and evaluate machine learning solutions with scikit-learn by Hackeling, Gavin

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Machine Learning with Scikit-Learn Quick Start Guide : Classification, Regression, and Clustering Techniques in Python. by Jolly, Kevin

Table of Contents: “…Chapter 2: Predicting Categories with K-Nearest NeighborsTechnical requirements; Preparing a dataset for machine learning with scikit-learn; Dropping features that are redundant; Reducing the size of the data; Encoding the categorical variables; Missing values; The k-NN algorithm; Implementing the k-NN algorithm using scikit-learn; Splitting the data into training and test sets; Implementation and evaluation of your model; Fine-tuning the parameters of the k-NN algorithm; Scaling for optimized performance; Summary; Chapter 3: Predicting Categories with Logistic Regression.…”
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Global Navigation Satellite System (GNSS) Receivers for Weak Signals. by Ziedan, Nesreen

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Modeling Reality : How Computers Mirror Life. by Białynicki-Birula, Iwo

Table of Contents: “…Contents; 1 From building blocks to computers: Models and modeling; 2 The game of life: A legendary cellular automaton; 3 Heads or tails: Probability of an event; 4 Galton's board: Probability and statistics; 5 Twenty questions: Probability and information; 6 Snowflakes: The evolution of dynamical systems; 7 The Lorenz butterfly: Deterministic chaos; 8 From Cantor to Mandelbrot: Self-similarity and fractals; 9 Typing monkeys: Statistical linguistics; 10 The bridges of Königsberg: Graph theory; 11 Prisoner's dilemma: Game theory; 12 Let the best man win: Genetic algorithms.…”
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Industrial control systems

Table of Contents: “…INTELLIGENT CONTROL SYSTEM FOR AN INDUSTRIAL MANIPULATORAbstract; 1Introduction; 2AdaptiveLearningTechniqueforLarge-ScaleTeachingSignals; 2.1Background; 2.2Model-basedroboticservosystem; 2.2.1Computedtorquecontrolmethod; 2.2.2TeachingsignalforRNN; 2.3Independentrecurrentneuralnetworksforanindustrialrobotwithsixjoints; 2.3.1AdaptivelearningofRNNs; 2.3.2LearningresultsofRNNs; 2.4AdvancedservosystemusingintegratedRNNs; 3FineGainTuningforModel-BasedRoboticServoControllersUsingGeneticAlgorithms; 3.1Background; 3.2RoboticServoController; 3.2.1ResolvedAccelerationControl.…”
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F♯ for Machine Learning Essentials. by Mukherjee, Sudipta

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Advances in intelligent IT : active media technology 2006

Table of Contents: “…Title page; Preface; Organization; Contents; Keynotes; Active Media Technologies (AMT) from the Standpoint of the Wisdom Web; Anytime Learning and Classification for Online Applications; Domain-Driven Data Mining: Methodologies and Applications; Regular Papers; Web Service Request Transformatter; A Head-Tracker Based on the Lucas-Kanade Optical Flow Algorithm; A Fair Peer Selection Algorithm for an Ecommerce-Oriented Distributed Recommender System; Intelligent Decision Making with the Semantic Web; Relevence Assessment of Topic Ontology; Information Extraction from a Whole Web Site.…”
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Anaphora Resolution. by Mitkov, Ruslan

Table of Contents: “…4.1 Early work in anaphora resolution4.2 Student; 4.3 Shrdlu; 4.4 Lunar; 4.5 Hobbs's naïve approach; 4.5.1 The algorithm; 4.5.2 Evaluation of Hobbs' s algorithm; 4.6 The BFP algorithm; 4.7 Carter's shallow processing approach; 4.8 Rich and LuperFoy's distributed architecture; 4.9 Carbonell and Brown's multi-strategy approach; 4.10 Other work; 4.11 Summary; Chapter Five: The present: knowledge-poor and corpus-based approaches in the 1990s and beyond; 5.1 Main trends in recent anaphora resolution research; 5.2 Collocation patterns-based approach; 5.3 Lappin and Leass's algorithm; 5.3.1 Overview.…”
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