Tabla de Contenidos: “…An introduction to computer vision in the food and beverage industries -- pt. 2. …”

“…PyTorch for deep learning and computer vision…”

“…Modern machine vision involves automated systems outperforming humans on image recognition, object detection, and image segmentation tasks. …”

Tabla de Contenidos: “…Hands-On Vision and Behavior for Self-Driving Cars: Explore visual perception, lane detection, and object classification with Python 3 and OpenCV 4…”

“…Visiones de guerra y de retaguardia…”
Accés lliure

“…In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. …”

Tabla de Contenidos: “…-- References -- Origami Life -- 1 Origami Molecules -- 2 Origami Design Algorithms -- 3 Origami Folding Pathways -- 4 Folded Origins -- References -- Ok: A Kinetic Model for Locally Reconfigurable Molecular Systems -- 1 Introduction -- 2 Molecular Reconfiguration: Oritatami and Nubots -- 3 The Ok model -- 3.1 Reconfiguration Events -- 3.2 Reconfiguration Distributions and Events Rates -- 3.3 Implementing the Ok model -- 4 Conclusion -- References -- Implementing a Theoretician's Toolkit for Self-Assembly with DNA Components -- 1 Introduction -- 2 Definitions and Notation -- 3 Metrics -- 4 Monomer Reuse: Hard-Coded Versus Algorithmic -- 5 Inputs -- 5.1 Seed Assemblies -- 5.2 Tile Subsets -- 5.3 Monomer Concentrations -- 5.4 Programmed Temperature Fluctuations -- 5.5 Staged Assembly -- 6 Dynamics -- 6.1 Cooperativity -- 6.2 Single Tile or Hierarchical Growth -- 6.3 Activatable/Deactivatable Glues -- 6.4 Tile Removal and Breaking of Assemblies -- 6.5 Reconfiguration Via Flexibility -- 6.6 Assembly Growth Controlled by CRNs -- 7 Conclusion -- References -- Reasoning As If -- 1 Introduction -- 2 The Snapshot Algorithm -- 3 Local Determinism -- 4 The Future of As If -- References -- Biochemical Circuits -- Scaling Up DNA Computing with Array-Based Synthesis and High-Throughput Sequencing -- 1 Introduction -- 1.1 Scaling up DNA Computing for Molecular Diagnostics -- 1.2 Scaling up DNA Computing for DNA Data Storage -- 1.3 Limitations of Current Approaches to DNA Computing -- 2 A Vision for the Future -- 3 Results -- 3.1 Nicked Double-Stranded DNA Gates Reaction Mechanism -- 3.2 Gate Design…”

“…Focusing on time as a human construct, A New Vision for Islamic Pasts and Futures interprets stories and images, paying attention to evidence and methods of interpretation. …”

Tabla de Contenidos: “…Intro -- FrontMatter -- Preface -- Acknowledgment of Reviewers -- Contents -- Acronyms -- Executive Summary -- In Remembrance -- Summary -- 1 The History of Cooperative Threat Reduction (1991-2018) -- 2 The Changing Biothreat Landscape -- 3 Addressing Biothreats through Successful Engagement -- 4 Key Roles for the Department of Defense in Biological Threat Reduction -- 5 Strategic Vision and the Way Forward -- 6 Key Findings and Recommendations -- References -- Appendix A: Committee Biographies -- Appendix B: Congressionally-Appropriated Funding for the Biological Threat Reduction Program (2007-2020) -- Appendix C: U.S. and International Agencies and Organizations Engaged in Global Health Security…”

Tabla de Contenidos: “…Front Cover -- Advanced Methods and Deep Learning in Computer Vision -- Copyright -- Contents -- List of contributors -- About the editors -- Preface -- 1 The dramatically changing face of computer vision -- 1.1 Introduction - computer vision and its origins -- 1.2 Part A - Understanding low-level image processing operators -- 1.2.1 The basics of edge detection -- 1.2.2 The Canny operator -- 1.2.3 Line segment detection -- 1.2.4 Optimizing detection sensitivity -- 1.2.5 Dealing with variations in the background intensity -- 1.2.6 A theory combining the matched filter and zero-mean constructs -- 1.2.7 Mask design-other considerations -- 1.2.8 Corner detection -- 1.2.9 The Harris `interest point' operator -- 1.3 Part B - 2-D object location and recognition -- 1.3.1 The centroidal profile approach to shape analysis -- 1.3.2 Hough-based schemes for object detection -- 1.3.3 Application of the Hough transform to line detection -- 1.3.4 Using RANSAC for line detection -- 1.3.5 A graph-theoretic approach to object location -- 1.3.6 Using the generalized Hough transform (GHT) to save computation -- 1.3.7 Part-based approaches -- 1.4 Part C - 3-D object location and the importance of invariance -- 1.4.1 Introduction to 3-D vision -- 1.4.2 Pose ambiguities under perspective projection -- 1.4.3 Invariants as an aid to 3-D recognition -- 1.4.4 Cross ratios: the `ratio of ratios' concept -- 1.4.5 Invariants for noncollinear points -- 1.4.6 Vanishing point detection -- 1.4.7 More on vanishing points -- 1.4.8 Summary: the value of invariants -- 1.4.9 Image transformations for camera calibration -- 1.4.10 Camera calibration -- 1.4.11 Intrinsic and extrinsic parameters -- 1.4.12 Multiple view vision -- 1.4.13 Generalized epipolar geometry -- 1.4.14 The essential matrix -- 1.4.15 The fundamental matrix -- 1.4.16 Properties of the essential and fundamental matrices…”

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“…AWS Python Computer Vision…”