Search Results - (((((((kant OR makant) OR mantis) OR when) OR cantor) OR anne) OR shape) OR hints) algorithms.

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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Advances in mechatronics, robotics and automation II : selected, peer reviewed papers from the 2014 2nd International Conference on Mechatronics, Robotics and Automation (ICMRA 201...

Table of Contents: “…A New Color Fidelity Fast Denoising Algorithm for High-ISO ImagesA New Video Denoising Algorithm Based on Adaptive Polyview Fusion; A Parallel Stereo Matching Algorithm Core for FPGA Modeled by DSP Builder; A Robust Algorithm for the Inspection of Fastener Head; A Video Compression Coding Algorithm for Network Content Transmission; An Efficient Shape Recognition Method Using Multiple Description Fusion; Clonal Selection Algorithm Based on Manifold Distance for Image Compression; Dot Area Coverage Percentage Measurement Method for Plate Microscopic Image Based on Color Segmentation.…”
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Mixed Models : Theory and Applications with R. by Demidenko, Eugene

Table of Contents: “…2.9 Derivatives of the log-likelihood function -- 2.10 Newton-Raphson algorithm -- 2.11 Fisher scoring algorithm -- 2.11.1 Simplified FS algorithm -- 2.11.2 Empirical FS algorithm -- 2.11.3 Variance-profile FS algorithm -- 2.12 EM algorithm -- 2.12.1 Fixed-point algorithm -- 2.13 Starting point -- 2.13.1 FS starting point -- 2.13.2 FP starting point -- 2.14 Algorithms for restricted MLE -- 2.14.1 Fisher scoring algorithm -- 2.14.2 EM algorithm -- 2.15 Optimization on nonnegative definite matrices -- 2.15.1 How often can one hit the boundary? …”
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Integrated and collaborative product development environment : technologies and implementations by Li, W. D.

Table of Contents: “…Intelligent Optimisation of Process Planning; 5.1 Intelligent Optimisation Strategies for CAPP Systems; 5.2 Knowledge Representation of Process Plans; 5.2.1 Process plan representation; 5.2.2 Machining cost criteria for process plans; 5.2.3 Precedence constraints; 5.3 A Hybrid GA/SA-based Optimisation Method; 5.3.1 Overview of the algorithm; 5.3.2 Genetic algorithm -- phase 1; 5.3.3 Simulated annealing algorithm -- phase 2; 5.3.4 Constraint handling algorithm.…”
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Special issue on the discreet element method : numerical modeling of discontinue. by Kuhn, Matthew R.

Table of Contents: “…Comparison of experimental and FEM/DEM results for gravitational deposition of identical cubesA 2D polygon/polygon contact model: algorithmic aspects; Selecting a suitable time step for discrete element simulations that use the central difference time integration scheme; Numerical studies of uniaxial powder compaction process by 3D DEM; Thin tunnel liners modelled with particle flow code; Shape selection menu for grand scale discontinua systems.…”
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Deep Learning Quick Reference : Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras. by Bernico, Michael

Table of Contents: “…Drawbacks to consider when using a neural network for regressionUsing deep neural networks for regression; How to plan a machine learning problem; Defining our example problem; Loading the dataset; Defining our cost function; Building an MLP in Keras; Input layer shape; Hidden layer shape; Output layer shape; Neural network architecture; Training the Keras model; Measuring the performance of our model; Building a deep neural network in Keras; Measuring the deep neural network performance; Tuning the model hyperparameters; Saving and loading a trained Keras model; Summary.…”
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The finite element method : its basis and fundamentals by Zienkiewicz, O. C.

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Optimal structural design : contact problems and high-speed penetration by Banichuk, Nikolaĭ Vladimirovich, Ivanova, S. I︠U︡. (Svetlana I︠U︡rʹevna)

Table of Contents: “…Shape optimization of punch moving with friction; 4. …”
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Engineering optimization : an introduction with metaheuristic applications by Yang, Xin-She

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Data Analytics in Bioinformatics : A Machine Learning Perspective. by Satpathy, Rabinarayan

Table of Contents: “…3.4.1 Comparative Analysis of ANN With Broadly Used Traditional ML Algorithms -- 3.5 Critical Analysis -- 3.6 Conclusion -- References -- Part 2: MACHINE LEARNING AND GENOMIC TECHNOLOGY, FEATURE SELECTION AND DIMENSIONALITY REDUCTION -- 4 Dimensionality Reduction Techniques: Principles, Benefits, and Limitations -- 4.1 Introduction -- 4.2 The Benefits and Limitations of Dimension Reduction Methods -- 4.3 Components of Dimension Reduction -- 4.3.1 Feature Selection -- 4.3.2 Feature Reduction -- 4.4 Methods of Dimensionality Reduction -- 4.4.1 Principal Component Analysis (PCA)…”
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Handbook of Computational Geometry. by Sack, J. R.

Table of Contents: “…Arrangements and their applications; Chapter 3. Discrete geometric shapes: Matching, interpolation, and approximation; Chapter 4. …”
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The NURBS Book by Piegl, Les

Table of Contents: “…One Curve and Surface Basics -- 1.1 Implicit and Parametric Forms -- 1.2 Power Basis Form of a Curve -- 1.3 Bézier Curves -- 1.4 Rational Bézier Curves -- 1.5 Tensor Product Surfaces -- Exercises -- Two B-Spline Basis Functions -- 2.1 Introduction -- 2.2 Definition and Properties of B-spline Basis Functions -- 2.3 Derivatives of B-spline Basis Functions -- 2.4 Further Properties of the Basis Functions -- 2.5 Computational Algorithms -- Exercises -- Three B-spline Curves and Surfaces -- 3.1 Introduction -- 3.2 The Definition and Properties of B-spline Curves -- 3.3 The Derivatives of a B-spline Curve -- 3.4 Definition and Properties of B-spline Surfaces -- 3.5 Derivatives of a B-spline Surface -- Exercises -- Four Rational B-spline Curves and Surfaces -- 4.1 Introduction -- 4.2 Definition and Properties of NURBS Curves -- 4.3 Derivatives of a NURBS Curve -- 4.4 Definition and Properties of NURBS Surfaces -- 4.5 Derivatives of a NURBS Surface -- Exercises -- Five Fundamental Geometric Algorithms -- 5.1 Introduction -- 5.2 Knot Insertion -- 5.3 Knot Refinement -- 5.4 Knot Removal -- 5.5 Degree Elevation -- 5.6 Degree Reduction -- Exercises -- Six Advanced Geometric Algorithms -- 6.1 Point Inversion and Projection for Curves and Surfaces -- 6.2 Surface Tangent Vector Inversion -- 6.3 Transformations and Projections of Curves and Surfaces -- 6.4 Reparameterization of NURBS Curves and Surfaces -- 6.5 Curve and Surface Reversal -- 6.6 Conversion Between B-spline and Piecewise Power Basis Forms -- Exercises -- Seven Conics and Circles -- 7.1 Introduction -- 7.2 Various Forms for Representing Conics -- 7.3 The Quadratic Rational Bézier Arc -- 7.4 Infinite Control Points -- 7.5 Construction of Circles -- 7.6 Construction of Conies -- 7.7 Conic Type Classification and Form Conversion -- 7.8 Higher Order Circles -- Exercises -- Eight Construction of Common Surfaces -- 8.1 Introduction -- 8.2 Bilinear Surfaces -- 8.3 The General Cylinder -- 8.4 The Ruled Surface -- 8.5 The Surface of Revolution -- 8.6 Nonuniform Scaling of Surfaces -- 8.7 A Three-sided Spherical Surface -- Nine Curve and Surface Fitting -- 9.1 Introduction -- 9.2 Global Interpolation -- 9.3 Local Interpolation -- 9.4 Global Approximation -- 9.5 Local Approximation -- Exercises -- Ten Advanced Surface Construction Techniques -- 10.1 Introduction -- 10.2 Swung Surfaces -- 10.3 Skinned Surfaces -- 10.4 Swept Surfaces -- 10.5 Interpolation of a Bidirectional Curve Network -- 10.6 Coons Surfaces -- Eleven Shape Modification Tools -- 11.1 Introduction -- 11.2 Control Point Repositioning -- 11.3 Weight Modification -- 11.4 Shape Operators -- 11.5 Constraint-based Curve and Surface Shaping -- Twelve Standards and Data Exchange -- 12.1 Introduction -- 12.2 Knot Vectors -- 12.3 Nurbs Within the Standards -- 12.4 Data Exchange to and from a NURBS System -- Thirteen B-spline Programming Concepts -- 13.1 Introduction -- 13.2 Data Types and Portability -- 13.3 Data Structures -- 13.4 Memory Allocation -- 13.5 Error Control -- 13.6 Utility Routines -- 13.7 Arithmetic Routines -- 13.8 Example Programs -- 13.9 Additional Structures -- 13.10 System Structure -- References.…”
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Nonlinear Optimization of Vehicle Safety Structures : Modeling of Structures Subjected to Large Deformations. by Christensen, Jesper

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Machine Learning for Mobile : Practical Guide to Building Intelligent Mobile Applications Powered by Machine Learning. by Gopalakrishnan, Revathi

Table of Contents: “…Chapter 2: Supervised and Unsupervised Learning AlgorithmsIntroduction to supervised learning algorithms; Deep dive into supervised learning algorithms; Naive Bayes; Decision trees; Linear regression; Logistic regression; Support vector machines; Random forest; Introduction to unsupervised learning algorithms; Deep dive into unsupervised learning algorithms; Clustering algorithms; Clustering methods; Hierarchical agglomerative clustering methods; K-means clustering; Association rule learning algorithm; Summary; References; Chapter 3: Random Forest on iOS; Introduction to algorithms…”
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Can markets compute equilibria? by Monroe, Hunter K.

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Agent-based computing

Table of Contents: “…Analysis of Algorithm -- 2.1.1. Chain-Like Agent Structure -- 2.1.2. …”
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OpenCV with Python by example : build real-world computer vision applications and develop cool demos using OpenCV for Python by Joshi, Prateek

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Advances in Knowledge-Based and Intelligent Engineering and Information Systems by Frydman, Claudia

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Urodynamics : a quick pocket guide by Vignoli, Giancarlo

Table of Contents: “…The framework of basic science -- Key symptoms analysis and diagnostic algorithms -- Physical examination and laboratory evaluation -- Urodynamic testing: when and which -- Voiding diary and Pad testing -- Non-invasive urodynamics -- Conventional urodynamics-conventional urodynamics in pediatric age -- Electromyogtrahy -- Urethral profilometry -- Videourodynamics -- Ambulatory urodynamics -- Urodynamics of upper urinary tract.…”
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Mount Sinai expert guides. Hepatology

Table of Contents: “…Cover; Title page; Copyright page; Contents; List of Contributors; Series Foreword; Preface; Abbreviation List; About the Companion Website; PART 1: Hepatology; CHAPTER 1: Approach to the Patient with Abnormal Liver Tests; Section 1: Background; Definition of disease; Disease classification; Etiology; Pathology/pathogenesis; Section 2: Prevention; Section 3: Diagnosis; Typical presentation; Clinical diagnosis; Laboratory diagnosis; Diagnostic algorithm; Potential pitfalls/common errors made regarding diagnosis of disease; Section 4: Treatment; When to hospitalize…”
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