Search Results - (((((((ken OR want) OR semantic) OR wien) OR cantor) OR anne) OR blaney) OR hints) algorithms.

Computational models of argument : Proceedings of COMMA 2012

Table of Contents: “…Simari -- Automated Deployment of Argumentation Protocols / Michael Rovatsos -- On Preferred Extension Enumeration in Abstract Argumentation / Katie Atkinson -- Towards Experimental Algorithms for Abstract Argumentation / Katie Atkinson.…”
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Automata and Computability. by Kozen, Dexter, 1951-

Table of Contents: “…Miscellaneous Exercises Turing Machines and Effective ComputabilityHints for Selected Miscellaneous Exercises; Solutions to Selected Miscellaneous Exercises; References; Notation and Abbreviations; Index.…”
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Robotics : science and systems III

Table of Contents: “…Semantic Modeling of Places using Objects / Ananth Ranganathan and Frank Dellaert -- Design of a Bio-inspired Dynamical Vertical Climbing Robot / Jonathan E. …”
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Mathematical morphology and its applications to image and signal processing

Table of Contents: “…Geodesic Set Definition in Case of Empty Intersection -- The Morphological-Affine Object Deformation -- Affine Invariant Mathematical Morphology Applied to a Generic Shape Recognition Algorithm -- Filtering -- Folding Induced Self-Dual Filters -- Flexible Linear Openings and Closings -- Some Applications of Aperture Filters -- GA Optimisation of Multidimensional Grey-Scale Soft Morphological Filters with Applications in Archive Film Restoration -- Connectivity and Connected Operators -- New Insight on Digital Topology -- Approximate Connectivity and Mathematical Morphology -- Multiresolution Connectivity: An Axiomatic Approach -- Connected Operators Based on Region-Tree Pruning -- Segmentation -- Image Segmentation Based on the Derivative of the Morphological Profile -- Flooding and Segmentation -- A Morphological Multi-Scale Gradient for Color Image Segmentation -- Automatic Watershed Segmentation of Color Images -- Motion Segmentation using Seeded Region Growing -- A Segmentation Pyramid for the Interactive Segmentation of 3-D Images and Video Sequences -- Partition Lattice Operators for Extraction of Semantic Video Objects -- Texture Analysis -- Morphological Granulometric Deconstruction -- Surface Texture Classification from Morphological Transformations -- Content Dependent Image Sampling using Mathematical Morphology: Application to Mipmapping -- Multiresolution Techniques and Scale-Spaces -- Morphological Pyramids and Wavelets Based on the Quincunx Lattice -- Morphological Scale-Space Operators: An Algebraic Framework -- An Idempotent Scale-Space Approach for Morphological Segmentation -- Algorithms -- Efficient Dilation, Erosion, Opening and Closing Algorithms -- Fast Morphological Attribute Operations using Tarjan's Union-Find Algorithm -- A Change Detector Based on Level Sets -- A General Algorithm for Computing Distance Transforms in Linear Time -- The Ordered Queue and the Optimality of the Watershed Approaches -- Discrete 3D Wave Propagation for Computing Morphological Operations from Surface Patches and Unorganized Points -- Applications -- Two-Stage Lossy/Lossless Compression of Grayscale Document Images -- Boosting OCR Classifier by Optimal Edge Noise Filtering -- Morphological Bank Check Logo Segmentation with Few a Priori Knowledge -- Morphological Pseudo Convex Hull to Correct Handwriting Baseline Skew -- Morphological Segmentation of Text and Figures in Renaissance Books (XVI Century) -- Application of Mathematical Morphology and Markov Random Field Theory to the Automatic Extraction of Linear Features in Airborne Images -- Testing Some Morphological Approaches to Face Localization -- Quantitative Description of Telecommunication Networks by Simulation -- Author Index.…”
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Learning-based local visual representation and indexing by Rongrong, Ji, Yao, Hongxun, Gao, Yue, Duan, Ling-Yu, Dai, Qionghai

Table of Contents: “…3.4.1 Cross-database Case3.4.2 Incremental Transfer; 3.5 Experiments; 3.5.1 Quantitative results; 3.6 Summary; Chapter 4: Supervised Dictionary Learning via Semantic Embedding ; 4.1 Introduction; 4.2 Semantic Labeling Propagation; 4.2.1 Density Diversity Estimation ; 4.3 Supervised Dictionary Learning; 4.3.1 Generative Modeling ; 4.3.2 Supervised Quantization ; 4.4 Experiments; 4.4.1 Database and Evaluations; 4.4.2 Quantitative Results; 4.5 Summary; Chapter 5: Visual Pattern Mining; 5.1 Introduction; 5.2 Discriminative 3D Pattern Mining; 5.2.1 The Proposed Mining Scheme.…”
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Media Backends : Digital Infrastructures and Sociotechnical Relations. by Parks, Lisa

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Pattern discovery in biomolecular data : tools, techniques, and applications

Table of Contents: “…Discovering patterns in DNA sequences by the algorithmic significance method / Aleksandar Milosavljevic -- Assembling blocks / Jorja G. …”
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Advanced Analytics with R and Tableau. by Stirrup, Jen

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Big Data, IoT, and Machine Learning : Tools and Applications. by Agrawal, Rashmi

Table of Contents: “…Chapter 3 Reviews Analysis of Apple Store Applications Using Supervised Machine Learning -- 3.1 Introduction -- 3.2 Literature Review -- 3.2.1 Machine Learning Algorithms -- 3.2.2 Feature Extraction Algorithms -- 3.3 Proposed Methodology -- 3.3.1 Data Collection -- 3.3.2 Feature Extraction -- 3.3.3 Data Analysis and Sentiment Analysis -- Text Processing -- 3.3.4 Text Normalisation -- 3.4 Feature Extraction Algorithm -- 3.4.1 CountVectorizer -- 3.4.2 TfidfVectorizer (TF-IDF) -- 3.5 Supervised ML Classification -- 3.6 Experiment Design -- 3.7 Experimental Results and Analysis…”
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Knowledge discovery for business information systems

Table of Contents: “…Problem Description -- 3. The FUP Algorithm for the Insertion Only Case -- 4. The FUP Algorithm for the Deletions Only Case -- 5. …”
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Introduction to graph theory by Voloshin, Vitaly I. (Vitaly Ivanovich), 1954-

Table of Contents: “…What Is Mathematical Induction; 7.2. Graph Theory Algorithms and Their Complexity; 7.3. Answers and Hints to Selected Exercises; 7.4. …”
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Advanced Artificial Intelligence.

Table of Contents: “…Applications of temporal and spatial logic; 4.7.4. Randell algorithm; Exercises; Chapter 5 Case-Based Reasoning; 5.1 Overview; 5.2 Basic Notations; 5.3 Process Model; 5.4 Case Representation; 5.4.1 Semantic Memory Unit; 5.4.2 Memory Network; 5.5 Case Indexing; 5.6 Case Retrieval; 5.7 Similarity Relations in CBR; 5.7.1 Semantic similarity; 5.7.2 Structural similarity; 5.7.3 Goal's features; 5.7.4 Individual similarity; 5.7.5 Similarity assessment; 5.8 Case Reuse; 5.9 Case Retainion; 5.10 Instance-Based Learning.…”
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Web-based learning : men and machines - proceedings of the first international conference on web-based learning in china (icwl 2002). by REGGIE, KWAN

Table of Contents: “…Patterns of Web Based Learning in the Semantic Web Era ; PART THREE Tools.…”
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Internet+ and electronic business in China : innovation and applications

Table of Contents: “…Emotional analysis of online reviews on e-business platforms -- Chapter 14. Semantic search of online reviews on e-business platforms -- Part IV. …”
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Comorbidity in migraine

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Slantwise moves : games, literature, and social invention in nineteenth-century America by Guerra, Douglas

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Technologies for Engineering Manufacturing Systems Control in Closed Loop. by Preuße, Sebastian

Table of Contents: “…Intro; 1 Introduction; 2 Basic Principles; 2.1 Technologies for studying Behavior; 2.2 Plants; 2.3 Controllers; 2.3.1 IEC 61131-3; 2.3.2 IEC 61499-1; 2.4 System Models; 2.4.1 Syntax; 2.4.2 Semantics; 2.5 Basics of Specifications; 2.5.1 Computation Tree Logic; 2.5.2 Extended Computation Tree Logic; 2.5.3 Timed Computation Tree Logic; 2.5.4 Symbolic Timing Diagrams; 2.6 Closed-Loop Composition; 2.7 Model Checking; 2.7.1 General Remarks; 2.7.2 Model Checking Algorithm; 2.8 Summary; 3 Formal Modeling of Plant, Controller, and the Closed Loop; 3.1 Demonstration Example; 3.2 Formal Plant Modeling.…”
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Mastering Scala machine learning by Kozlov, Alexander

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Computational intelligence in aerospace sciences

Table of Contents: “…Coello Coello and Oliver Schütze ; Function landscapes and the difficulty of global optimization / Marco Locatelli ; Stochastic methods for single objective global optimization / Christian Lorenz Müller ; Uncertainty quantification in computational science / Gianluca Iaccarino ; Basic concepts of game theory for aerospace engineering applications / Lina Mallozzi -- Autonomy and robotics: Nonlinear state estimation algorithms for autonomous vehicles / Kumar Pakki Bharani Chandra and Da-Wei Gu ; Path planning algorithms in 2-D and 3-D obstacle-rich environments / Rosli Omar, Batu Pahat, Da-Wei Gu; Semantics of perception and action for symbolic reasoning in aerospace systems Sandor M. …”
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Information Theory Meets Power Laws : Stochastic Processes and Language Models. by Dębowski, Łukasz Jerzy, $$d 1975- $$e author

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