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Los puros criollos. / Tecnología criolla
Published 2012Full text (Emmanuel users only)
Electronic Video -
82
Vengeance is mine : the scandalous love triangle that triggered the Boyce-Sneed feud
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83
Semi-solid processing of alloys and composites XIII : selected, peer reviewed papers from the 13th International Conference on Semi-Solid Processing of Alloys and Composites (S2P 2...
Published 2015Full text (Emmanuel users only)
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Forensic photography : a practitioner's guide
Published 2014Table of Contents: “…Title Page; Copyright; Foreword; Preface; Acknowledgements; About the Companion Website; Chapter 1: Image Processing; 1.1 Introduction; 1.2 The digital image; 1.3 Image acquisition; 1.4 Colour images; 1.5 The imaging chain and workflow; 1.6 White balance; 1.7 Image histogram; 1.8 Image processing terminology; 1.9 Digital image processing operations; 1.10 Classes of operations; 1.11 Noise reduction; 1.12 Sharpening filters; 1.13 History log; 1.14 Layers; 1.15 Bit depth and dynamic range; 1.16 File formats; 1.17 Image compression; 1.18 Image processing at image capture.…”
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87
Los puros criollos. / Sagrado corazón
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Meteorites and asteroids : classification, geology, and exploration
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Carbon Nanotubes and Nanosensors : Vibration, Buckling and Balistic Impact.
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90
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Introduction to Antennas and RF Propagation Analysis
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92
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Los puros criollos. / Himno nacional
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Los puros criollos. / Florero de Llorente
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106
Speaker Jim Wright : power, scandal, and the birth of modern politics
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107
Clowns to the left of me, jokers to the right : American life in columns
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108
Mastering Java Machine Learning.
Published 2017Table of Contents: “…Case Study -- Horse Colic Classification -- Business problem -- Machine learning mapping -- Data analysis -- Label analysis -- Features analysis -- Supervised learning experiments -- Weka experiments -- RapidMiner experiments -- Results, observations, and analysis -- Summary -- References -- Chapter 3: Unsupervised Machine Learning Techniques -- Issues in common with supervised learning -- Issues specific to unsupervised learning -- Feature analysis and dimensionality reduction -- Notation -- Linear methods -- Principal component analysis (PCA) -- Random projections (RP) -- Multidimensional Scaling (MDS) -- Nonlinear methods -- Kernel Principal Component Analysis (KPCA) -- Manifold learning -- Clustering -- Clustering algorithms -- k-Means -- DBSCAN -- Mean shift -- Expectation maximization (EM) or Gaussian mixture modeling (GMM) -- Hierarchical clustering -- Self-organizing maps (SOM) -- Spectral clustering -- Affinity propagation -- Clustering validation and evaluation -- Internal evaluation measures -- External evaluation measures -- Outlier or anomaly detection -- Outlier algorithms -- Statistical-based -- Distance-based methods -- Density-based methods -- Clustering-based methods -- High-dimensional-based methods -- One-class SVM -- Outlier evaluation techniques -- Supervised evaluation -- Unsupervised evaluation -- Real-world case study -- Tools and software -- Business problem -- Machine learning mapping -- Data collection -- Data quality analysis -- Data sampling and transformation -- Feature analysis and dimensionality reduction -- Observations on feature analysis and dimensionality reduction -- Clustering models, results, and evaluation -- Observations and clustering analysis -- Outlier models, results, and evaluation -- Summary -- References -- Chapter 4: Semi-Supervised and Active Learning -- Semi-supervised learning.…”
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109
Antenna-On-Chip Design, Challenges, and Opportunities.
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110
Art in Science : Selections from EMERGING INFECTIOUS DISEASES.
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111
Radio-frequency integrated-circuit engineering
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112
Engineering autonomous vehicles and robots : the DragonFly modular-based approach
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113
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Los puros criollos. / Almanaque Bristol
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Bioenergy research : advances and applications
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120
Spectral sensing research for surface and air monitoring in chemical, biological and radiological defense and security applications
Published 2009Table of Contents: “…Schilling [and others] -- A high-resolution 2D imaging laser radar for occluded hard target viewing and identification / R.J. …”
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