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

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  1. 221

    Parts-feeding systems for assembly : organisation, logistics and automation

    Published 2015
    Table of Contents: “…A model for kitting operations planningRobust optimization approach to production system with failure in rework and breakdown under uncertainty: evolutionary methods; Re-layout of an assembly area: a case study at Bosch Rexroth Oil Control; A simple mechanical measurement system for the posture evaluation of wing components using the PSO and ICP algorithms; Implementation framework for a fully flexible assembly system (F-FAS); A genetic algorithm for supermarket location problem; New Kanban model for tow-train feeding system design.…”
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  2. 222

    3D face modeling, analysis and recognition by Daoudi, Mohamed, Ph. D., Srivastava, Anuj, Veltkamp, Remco C., 1963-

    Published 2013
    Table of Contents: “…3.5.4 Extension to Facial Surfaces Shape Analysis3.6 The Dense Scalar Field (DSF); 3.7 Statistical Shape Analysis; 3.7.1 Statistics on Manifolds: Karcher Mean; 3.7.2 Learning Statistical Models in Shape Space; 3.8 Applications of Statistical Shape Analysis; 3.8.1 3D Face Restoration; 3.8.2 Hierarchical Organization of Facial Shapes; 3.9 The Iso-geodesic Stripes; 3.9.1 Extraction of Facial Stripes; 3.9.2 Computing Relationships between Facial Stripes; 3.9.3 Face Representation and Matching Using Iso-geodesic Stripes; Exercises; Glossary; References.…”
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  3. 223

    Wavelet theory approach to pattern recognition

    Published 2009
    Table of Contents: “…Comparison with other wavelets. 7.4. Algorithm and experiments -- ch. 8. Skeletonization of ribbon-like shapes with new wavelet function. 8.1. …”
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  4. 224
  5. 225

    Numerical Methods for Eigenvalue Problems. by Börm, Steffen

    Published 2012
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  6. 226
  7. 227

    Optimization of Observation and Control Processes. by Malyshev, V. V.

    Published 2000
    Table of Contents: “…Optimization of Informational Noise When Observing a Dynamic Object""; ""4.6. Example of Observing a Maneuvering Object""; ""Chapter 5. …”
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  8. 228
  9. 229

    The Finite Element Method : a Practical Course. by Liu, G. R.

    Published 2013
    Table of Contents: “…3.4.3.3 On other means of construct shape functions3.4.4 Properties of the shape functions; 3.4.5 Formulation of finite element equations in local coordinate system; 3.4.6 Coordinate transformation; 3.4.7 Assembly of global FE equation; 3.4.8 Imposition of displacement constraints; 3.4.9 Solving the global FE equation; 3.5 Static analysis; 3.6 Analysis of free vibration (eigenvalue analysis); 3.7 Transient response; 3.7.1 Central difference algorithm; 3.7.2 Newmark's method (Newmark, 1959); 3.8 Remarks; 3.8.1 Summary of shape function properties.…”
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  10. 230

    Data mining techniques : for marketing, sales, and customer relationship management by Berry, Michael J. A.

    Published 2004
    Table of Contents: “…-- The virtuous cycle of data mining -- Data mining methodology and best practices -- Data mining applications in marketing and customer relationship management -- The lure of statistics : data mining using familiar tools -- Decision trees -- Artificial neural networks -- Nearest neighbor approaches : memory-based reasoning and collaborative filtering -- Market basket analysis and association rules -- Link analysis -- Automatic cluster detection -- Knowing when to worry : hazard functions and survival analysis in marketing -- Genetic algorithms -- Data mining throughout the customer life cycle -- Data warehousing, OLAP, and data mining -- Building the data mining environment -- Preparing data for mining -- Putting data mining to work.…”
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  13. 233

    An introduction to computational engineering with Matlab by Yang, Xin-She

    Published 2006
    Table of Contents: “…Optimization in Engineering -- 12.1 Introduction -- 12.2 Bioinspired Algorithms -- 12.2.1 Genetic Algorithms -- 12.2.2 Neural Networks…”
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  14. 234

    Java Deep Learning Projects : Implement 10 Real-World Deep Learning Applications Using Deeplearning4j and Open Source APIs. by Karim, Rezaul

    Published 2018
    Table of Contents: “…; Artificial Neural Networks; Biological neurons; A brief history of ANNs; How does an ANN learn?; ANNs and the backpropagation algorithm; Forward and backward passes; Weights and biases; Weight optimization; Activation functions.…”
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  15. 235

    Deep Learning with TensorFlow : Explore neural networks and build intelligent systems with Python, 2nd Edition. by Zaccone, Giancarlo

    Published 2018
    Table of Contents: “…; Artificial neural networks; The biological neurons; The artificial neuron; How does an ANN learn?; ANNs and the backpropagation algorithm; Weight optimization; Stochastic gradient descent; Neural network architectures; Deep Neural Networks (DNNs); Multilayer perceptron; Deep Belief Networks (DBNs).…”
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  16. 236
  17. 237

    Biological small angle scattering : theory and practice by Lattman, Eaton E. (Eaton Edward), 1940-, Grant, Thomas D. (Staff scientist), Snell, Edward H.

    Published 2018
    Table of Contents: “…3.6 Summary4. Shape Reconstructions from Small Angle Scattering Data; 4.1 Calculating Scattering Profiles from Three-Dimensional Models; 4.1.1 Debye Equation; 4.1.2 Gaining a Feel for the Spherical Harmonic Function; 4.1.3 Spherical Harmonic Representation of Envelopes; 4.1.4 Expansion of the Structure Factor Equation in Spherical Harmonics; 4.1.5 Zernicke Polynomial Expansion; 4.1.6 Solvent Considerations; 4.2 Ab Initio Modeling; 4.2.1 Modeling by Simple Shapes; 4.2.2 Simple Model Examples; 4.2.3 Envelope Fitting Using Analytical Functions…”
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    Creating E-Learning Games with Unity. by Horachek, David

    Published 2014
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  20. 240

    Seismic Data Interpretation using Digital Image Processing by Al-Shuhail, Abdullatif A., Al-Dossary, Saleh A., Mousa, Wail A.

    Published 2017
    Table of Contents: “…5.5 Two-Dimensional Second-Order Derivative Operator5.5.1 The Coherence Attribute; 5.5.2 The Dip Attribute; 5.6 The Curvature Attribute; 5.7 Curvature of the Surface; 5.7.1 Curve, Velocity, and Curvature; 5.7.2 Surface, Tangent Plane, and Norm; 5.8 Shape Operator, Normal Curvature, and Principal Curvature; 5.8.1 Normal Curvature; 5.8.2 Shape Operator; 5.8.3 The Principal Curvatures; 5.8.4 Calculation of the Principal Curvatures; 5.8.5 Summary of Calculation of Principal Curvature for a Surface; 5.9 The Randomness Attribute; 5.10 Technique for Two-Dimensional Images.…”
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