# Search result: Catalogue data in Spring Semester 2021

Computational Science and Engineering Bachelor | ||||||

Bachelor Studies (Programme Regulations 2016) | ||||||

Basic Courses | ||||||

Block G4 Students that enrol for the second year in the CSE Bachelor Programme and whose first year examination did not involve the subject "Physics I" will instead of "Physics II" (402-0034-10L) take the "Physics I and II" (402-0043-00L and 402-0044-00L) courses with performance assessment as a yearly course. As of FS 2018 the course unit 151-0122-00L Fluid Dynamics for CSE gets replaced in Block G4 by 151-0102-00L Fluid Dynamics I. | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |
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402-0034-10L | Physics II | W | 4 credits | 2V + 2U | W. Wegscheider | |

Abstract | This is a two-semester course introducing students into the foundations of Modern Physics. Topics include electricity and magnetism, light, waves, quantum physics, solid state physics, and semiconductors. Selected topics with important applications in industry will also be considered. | |||||

Objective | The lecture is intended to promote critical, scientific thinking. Key concepts of Physics will be acquired, with a focus on technically relevant applications. At the end of the two semesters, students will have a good overview over the topics of classical and modern Physics. | |||||

Content | Introduction into Quantum Physics, Absorption and Emission of Electromagnetic Radiation, Basics of Solid State Physics, Semiconductors | |||||

Lecture notes | Lecture notes will be available in German. | |||||

Literature | Paul A. Tipler, Gene Mosca, Michael Basler und Renate Dohmen Physik: für Wissenschaftler und Ingenieure Spektrum Akademischer Verlag, 2009, 1636 Seiten, ca. 80 Euro. Paul A. Tipler, Ralph A. Llewellyn Moderne Physik Oldenbourg Wissenschaftsverlag, 2009, 982 Seiten, ca. 75 Euro. | |||||

Prerequisites / Notice | No testat requirements for this lecture. | |||||

402-0044-00L | Physics II | W | 4 credits | 3V + 1U | T. Esslinger | |

Abstract | Introduction to the concepts and tools in physics with the help of demonstration experiments: electromagnetism, optics, introduction to modern physics. | |||||

Objective | The concepts and tools in physics, as well as the methods of an experimental science are taught. The student should learn to identify, communicate and solve physical problems in his/her own field of science. | |||||

Content | Electromagnetism (electric current, magnetic fields, electromagnetic induction, magnetic materials, Maxwell's equations) Optics (light, geometrical optics, interference and diffraction) Short introduction to quantum physics | |||||

Lecture notes | The lecture follows the book "Physik" by Paul A. Tipler. | |||||

Literature | Paul A. Tipler and Gene Mosca Physik Springer Spektrum Verlag | |||||

151-0102-00L | Fluid Dynamics I | O | 6 credits | 4V + 2U | T. Rösgen | |

Abstract | An introduction to the physical and mathematical foundations of fluid dynamics is given. Topics include dimensional analysis, integral and differential conservation laws, inviscid and viscous flows, Navier-Stokes equations, boundary layers, turbulent pipe flow. Elementary solutions and examples are presented. | |||||

Objective | An introduction to the physical and mathematical principles of fluid dynamics. Fundamental terminology/principles and their application to simple problems. | |||||

Content | Phenomena, applications, foundations dimensional analysis and similitude; kinematic description; conservation laws (mass, momentum, energy), integral and differential formulation; inviscid flows: Euler equations, stream filament theory, Bernoulli equation; viscous flows: Navier-Stokes equations; boundary layers; turbulence | |||||

Lecture notes | Lecture notes (extended formulary) for the course are made available electronically. | |||||

Literature | Recommended book: Fluid Mechanics, Kundu & Cohen & Dowling, 6th ed., Academic Press / Elsevier (2015). | |||||

Prerequisites / Notice | Voraussetzungen: Physik, Analysis | |||||

529-0483-00L | Statistical Physics and Computer Simulation | O | 4 credits | 2V + 1U | S. Riniker, P. H. Hünenberger | |

Abstract | Principles and applications of statistical mechanics and equilibrium molecular dynamics, Monte Carlo simulation, Stochastic dynamics. Exercises using a MD simulation program to generate ensembles and subsequently calculate ensemble averages. | |||||

Objective | Introduction to statistical mechanics with the aid of computer simulation, development of skills to carry out statistical mechanical calculations using computers and interpret the results. | |||||

Content | Principles and applications of statistical mechanics and equilibrium molecular dynamics, Monte Carlo simulation, stochastic dynamics, free energy calculation. Exercises using a MD simulation program to generate ensembles and subsequently calculate ensemble averages. | |||||

Literature | will be announced in the lecture | |||||

Prerequisites / Notice | Since the exercises on the computer do convey and test essentially different skills as those being conveyed during the lectures and tested at the written exam, the results of a small programming project will be presented in a 10-minutes talk by pairs of students who had been working on the project. Additional information will be provided in the first lecture. | |||||

Core Courses | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

151-0116-00L | High Performance Computing for Science and Engineering (HPCSE) for CSE | O | 7 credits | 4G + 2P | P. Koumoutsakos, S. M. Martin | |

Abstract | This course focuses on programming methods and tools for parallel computing on multi and many-core architectures. Emphasis will be placed on practical and computational aspects of Bayesian Uncertainty Quantification and Machine Learning including the implementation of these algorithms on HPC architectures. | |||||

Objective | The course will teach - programming models and tools for multi and many-core architectures - fundamental concepts of Uncertainty Quantification and Propagation (UQ+P) for computational models of systems in Engineering and Life Sciences. - fundamentals of Deep Learning | |||||

Content | High Performance Computing: - Advanced topics in shared-memory programming - Advanced topics in MPI - GPU architectures and CUDA programming Uncertainty Quantification: - Uncertainty quantification under parametric and non-parametric modeling uncertainty - Bayesian inference with model class assessment - Markov Chain Monte Carlo simulation Machine Learning - Deep Neural Networks and Stochastic Gradient Descent - Deep Neural Networks for Data Compression (Autoencoders) - Recurrent Neural Networks | |||||

Lecture notes | Link Class notes, handouts | |||||

Literature | - Class notes - Introduction to High Performance Computing for Scientists and Engineers, G. Hager and G. Wellein - CUDA by example, J. Sanders and E. Kandrot - Data Analysis: A Bayesian Tutorial, D. Sivia and J. Skilling - An introduction to Bayesian Analysis - Theory and Methods, J. Gosh, N. Delampady and S. Tapas - Bayesian Data Analysis, A. Gelman, J. Carlin, H. Stern, D. Dunson, A. Vehtari and D. Rubin - Machine Learning: A Bayesian and Optimization Perspective, S. Theodorides | |||||

Prerequisites / Notice | Attendance of HPCSE I | |||||

252-0232-00L | Software Engineering | O | 6 credits | 2V + 1U | F. Friedrich Wicker, M. Schwerhoff | |

Abstract | This course introduces both theoretical and applied aspects of software engineering. It covers: - Software Architecture - Informal and formal Modeling - Design Patterns - Software Engineering Principles - Code Refactoring - Program Testing | |||||

Objective | The course has two main objectives: - Obtain an end-to-end (both, theoretical and practical) understanding of the core techniques used for building quality software. - Be able to apply these techniques in practice. | |||||

Content | While the lecture will provide the theoretical foundations for the various aspects of software engineering, the students will apply those techniques in project work that will span over the whole semester - involving all aspects of software engineering, from understanding requirements over design and implementation to deployment and change requests. | |||||

Lecture notes | no lecture notes | |||||

Literature | Will be announced in the lecture | |||||

Bachelor's Thesis If you wish to have recognised 402-2000-00L Scientific Works in Physics instead of 401-2000-00L Scientific Works in Mathematics (as allowed for the CSE programme), take contact with the Study Administration Office (Link) after having passed the performance assessment. | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

401-2000-00L | Scientific Works in MathematicsTarget audience: Third year Bachelor students; Master students who cannot document to have received an adequate training in working scientifically. | O | 0 credits | M. Burger | ||

Abstract | Introduction to scientific writing for students with focus on publication standards and ethical issues, especially in the case of citations (references to works of others.) | |||||

Objective | Learn the basic standards of scientific works in mathematics. | |||||

Content | - Types of mathematical works - Publication standards in pure and applied mathematics - Data handling - Ethical issues - Citation guidelines | |||||

Lecture notes | Moodle of the Mathematics Library: Link | |||||

Prerequisites / Notice | Directive Link | |||||

401-2000-01L | Lunch Sessions – Thesis Basics for Mathematics StudentsDetails and registration for the optional MathBib training course: Link | Z | 0 credits | Speakers | ||

Abstract | Optional course "Recherchieren in der Mathematik" (held in German) by the Mathematics Library. | |||||

Objective | ||||||

402-2000-00L | Scientific Works in PhysicsTarget audience: Master students who cannot document to have received an adequate training in working scientifically. Directive Link | W | 0 credits | C. Eichler | ||

Abstract | Literature Review: ETH-Library, Journals in Physics, Google Scholar; Thesis Structure: The IMRAD Model; Document Processing: LaTeX and BibTeX, Mathematical Writing, AVETH Survival Guide; ETH Guidelines for Integrity; Authorship Guidelines; ETH Citation Etiquettes; Declaration of Originality. | |||||

Objective | Basic standards for scientific works in physics: How to write a Master Thesis. What to know about research integrity. | |||||

401-3990-01L | Bachelor's Thesis Only for Computational Science and Engineering BSc, Programme Regulations 2012 and 2016. Successful participation in the course unit 401-2000-00L Scientific Works in Mathematics or 402-2000-00L Scientific Works in Physicsis is required. For more information, see Link | O | 8 credits | 11D | Supervisors | |

Abstract | The BSc thesis concludes the curriculum. In their BSc thesis, students should demonstrate their ability to carry out independent, structured scientific work. The purpose of the BSc thesis is to deepen knowledge in a certain subject and to bring students into closer contact with applications in an existing computational group. The BSc thesis requires approximately 160 hours of work. | |||||

Objective | In their Bsc thesis students should demonstrate their ability to carry out independent, structured scientific work. The purpose is to deepen knowledge in a certain subject and to enable students to collaborate in an existing scientific group to take a computational approach to problems encountered in applications. | |||||

Prerequisites / Notice | The supervisor responsible for the Bachelor thesis defines the task and determines the start and the submission date. The Bachelor thesis concludes with a written report. The Bachelor thesis is graded. | |||||

For All Programme Regulations | ||||||

Fields of Specialization | ||||||

Astrophysics | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

402-0394-00L | Theoretical CosmologySpecial Students UZH must book the module AST513 directly at UZH. | W | 10 credits | 4V + 2U | L. M. Mayer, J. Yoo | |

Abstract | This is the second of a two course series which starts with "General Relativity" and continues in the spring with "Theoretical Astrophysics and Cosmology", where the focus will be on applying general relativity to cosmology as well as developing the modern theory of structure formation in a cold dark matter Universe. | |||||

Objective | Learning the fundamentals of modern physical cosmology. This entails understanding the physical principles behind the description of the homogeneous Universe on large scales in the first part of the course, and moving on to the inhomogeneous Universe model where perturbation theory is used to study the development of structure through gravitational instability in the second part of the course. Modern notions of dark matter and dark energy will also be introduced and discussed. | |||||

Content | The course will cover the following topics: - Homogeneous cosmology - Thermal history of the universe, recombination, baryogenesis and nucleosynthesis - Dark matter and Dark Energy - Inflation - Perturbation theory: Relativistic and Newtonian - Model of structure formation and initial conditions from Inflation - Cosmic microwave background anisotropies - Spherical collapse and galaxy formation - Large scale structure and cosmological probes | |||||

Lecture notes | In 2021, the lectures will be live-streamed online at ETH from the Room HPV G5 at the lecture hours. The recordings will be available at the ETH website. The detailed information will be provided by the course website and the SLACK channel. | |||||

Literature | Suggested textbooks: H.Mo, F. Van den Bosch, S. White: Galaxy Formation and Evolution S. Carroll: Space-Time and Geometry: An Introduction to General Relativity S. Dodelson: Modern Cosmology Secondary textbooks: S. Weinberg: Gravitation and Cosmology V. Mukhanov: Physical Foundations of Cosmology E. W. Kolb and M. S. Turner: The Early Universe N. Straumann: General relativity with applications to astrophysics A. Liddle and D. Lyth: Cosmological Inflation and Large Scale Structure | |||||

Prerequisites / Notice | Knowledge of General Relativity is recommended. | |||||

Physics of the Atmosphere | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

701-1216-00L | Numerical Modelling of Weather and Climate | W | 4 credits | 3G | C. Schär, J. Vergara Temprado, M. Wild | |

Abstract | The course provides an introduction to weather and climate models. It discusses how these models are built addressing both the dynamical core and the physical parameterizations, and it provides an overview of how these models are used in numerical weather prediction and climate research. As a tutorial, students conduct a term project and build a simple atmospheric model using the language PYTHON. | |||||

Objective | At the end of this course, students understand how weather and climate models are formulated from the governing physical principles, and how they are used for climate and weather prediction purposes. | |||||

Content | The course provides an introduction into the following themes: numerical methods (finite differences and spectral methods); adiabatic formulation of atmospheric models (vertical coordinates, hydrostatic approximation); parameterization of physical processes (e.g. clouds, convection, boundary layer, radiation); atmospheric data assimilation and weather prediction; predictability (chaos-theory, ensemble methods); climate models (coupled atmospheric, oceanic and biogeochemical models); climate prediction. Hands-on experience with simple models will be acquired in the tutorials. | |||||

Lecture notes | Slides and lecture notes will be made available at Link | |||||

Literature | List of literature will be provided. | |||||

Prerequisites / Notice | Prerequisites: to follow this course, you need some basic background in atmospheric science, numerical methods (e.g., "Numerische Methoden in der Umweltphysik", 701-0461-00L) as well as experience in programming. Previous experience with PYTHON is useful but not required. | |||||

Chemistry | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

529-0474-00L | Quantum Chemistry | W | 6 credits | 3G | M. Reiher, T. Weymuth | |

Abstract | Introduction into the basic concepts of electronic structure theory and into numerical methods of quantum chemistry. Exercise classes are designed to deepen the theory; practical case studies using quantum chemical software to provide a 'hands-on' expertise in applying these methods. | |||||

Objective | Nowadays, chemical research can be carried out in silico, an intellectual achievement for which Pople and Kohn have been awarded the Nobel prize of the year 1998. This lecture shows how that has been accomplished. It works out the many-particle theory of many-electron systems (atoms and molecules) and discusses its implementation into computer programs. A complete picture of quantum chemistry shall be provided that will allow students to carry out such calculations on molecules (for accompanying experimental work in the wet lab or as a basis for further study of the theory). | |||||

Content | Basic concepts of many-particle quantum mechanics. Derivation of the many-electron theory for atoms and molecules; starting with the harmonic approximation for the nuclear problem and with Hartree-Fock theory for the electronic problem to Moeller-Plesset perturbation theory and configuration interaction and to coupled cluster and multi-configurational approaches. Density functional theory. Case studies using quantum mechanical software. | |||||

Lecture notes | Hand-outs in German will be provided for each lecture (they are supplemented by (computer) examples that continuously illustrate how the theory works). All information regarding this course, including links to the online streaming, will be available on this web page: Link | |||||

Literature | Textbooks on Quantum Chemistry: F.L. Pilar, Elementary Quantum Chemistry, Dover Publications I.N. Levine, Quantum Chemistry, Prentice Hall Hartree-Fock in basis set representation: A. Szabo and N. Ostlund, Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory, McGraw-Hill Textbooks on Computational Chemistry: F. Jensen, Introduction to Computational Chemistry, John Wiley & Sons C.J. Cramer, Essentials of Computational Chemistry, John Wiley & Sons | |||||

Prerequisites / Notice | Basic knowledge in quantum mechanics (e.g. through course physical chemistry III - quantum mechanics) required | |||||

227-0161-00L | Molecular and Materials Modelling | W | 4 credits | 2V + 2U | D. Passerone, C. Pignedoli | |

Abstract | The course introduces the basic techniques to interpret experiments with contemporary atomistic simulation, including force fields or ab initio based molecular dynamics and Monte Carlo. Structural and electronic properties will be simulated hands-on for realistic systems. The modern methods of "big data" analysis applied to the screening of chemical structures will be introduced with examples. | |||||

Objective | The ability to select a suitable atomistic approach to model a nanoscale system, and to employ a simulation package to compute quantities providing a theoretically sound explanation of a given experiment. This includes knowledge of empirical force fields and insight in electronic structure theory, in particular density functional theory (DFT). Understanding the advantages of Monte Carlo and molecular dynamics (MD), and how these simulation methods can be used to compute various static and dynamic material properties. Basic understanding on how to simulate different spectroscopies (IR, X-ray, UV/VIS). Performing a basic computational experiment: interpreting the experimental input, choosing theory level and model approximations, performing the calculations, collecting and representing the results, discussing the comparison to the experiment. | |||||

Content | -Classical force fields in molecular and condensed phase systems -Methods for finding stationary states in a potential energy surface -Monte Carlo techniques applied to nanoscience -Classical molecular dynamics: extracting quantities and relating to experimentally accessible properties -From molecular orbital theory to quantum chemistry: chemical reactions -Condensed phase systems: from periodicity to band structure -Larger scale systems and their electronic properties: density functional theory and its approximations -Advanced molecular dynamics: Correlation functions and extracting free energies -The use of Smooth Overlap of Atomic Positions (SOAP) descriptors in the evaluation of the (dis)similarity of crystalline, disordered and molecular compounds | |||||

Lecture notes | A script will be made available and complemented by literature references. | |||||

Literature | D. Frenkel and B. Smit, Understanding Molecular Simulations, Academic Press, 2002. M. P. Allen and D.J. Tildesley, Computer Simulations of Liquids, Oxford University Press 1990. C. J. Cramer, Essentials of Computational Chemistry. Theories and Models, Wiley 2004 G. L. Miessler, P. J. Fischer, and Donald A. Tarr, Inorganic Chemistry, Pearson 2014. K. Huang, Statistical Mechanics, Wiley, 1987. N. W. Ashcroft, N. D. Mermin, Solid State Physics, Saunders College 1976. E. Kaxiras, Atomic and Electronic Structure of Solids, Cambridge University Press 2010. | |||||

Fluid Dynamics | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

151-0208-00L | Computational Methods for Flow, Heat and Mass Transfer Problems | W | 4 credits | 4G | D. W. Meyer-Massetti | |

Abstract | Numerical methods for the solution of flow, heat & mass transfer problems are presented and illustrated by analytical & computer exercises. | |||||

Objective | Knowledge of and practical experience with discretization and solution methods for computational fluid dynamics and heat and mass transfer problems | |||||

Content | - Introduction with application examples, steps to a numerical solution - Classification of PDEs, application examples - Finite differences - Finite volumes - Method of weighted residuals, spectral methods, finite elements - Stability analysis, consistency, convergence - Numerical solution methods, linear solvers The learning materials are illustrated with practical examples. | |||||

Lecture notes | Slides to be completed during the lecture will be handed out. | |||||

Literature | References are provided during the lecture. Notes in close agreement with the lecture material are available (in German). | |||||

Prerequisites / Notice | Basic knowledge in fluid dynamics, thermodynamics and programming (lecture: "Models, Algorithms and Data: Introduction to Computing") | |||||

Systems and Control | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

227-0216-00L | Control Systems II | W | 6 credits | 4G | R. Smith | |

Abstract | Introduction to basic and advanced concepts of modern feedback control. | |||||

Objective | Introduction to basic and advanced concepts of modern feedback control. | |||||

Content | This course is designed as a direct continuation of the course "Regelsysteme" (Control Systems). The primary goal is to further familiarize students with various dynamic phenomena and their implications for the analysis and design of feedback controllers. Simplifying assumptions on the underlying plant that were made in the course "Regelsysteme" are relaxed, and advanced concepts and techniques that allow the treatment of typical industrial control problems are presented. Topics include control of systems with multiple inputs and outputs, control of uncertain systems (robustness issues), limits of achievable performance, and controller implementation issues. | |||||

Lecture notes | The slides of the lecture are available to download. | |||||

Literature | Skogestad, Postlethwaite: Multivariable Feedback Control - Analysis and Design. Second Edition. John Wiley, 2005. | |||||

Prerequisites / Notice | Prerequisites: Control Systems or equivalent | |||||

227-0046-10L | Signals and Systems II | W | 4 credits | 2V + 2U | J. Lygeros | |

Abstract | Continuous and discrete time linear system theory, state space methods, frequency domain methods, controllability, observability, stability. | |||||

Objective | Introduction to basic concepts of system theory. | |||||

Content | Modeling and classification of dynamical systems. Modeling of linear, time invariant systems by state equations. Solution of state equations by time domain and Laplace methods. Stability, controllability and observability analysis. Frequency domain description, Bode and Nyquist plots. Sampled data and discrete time systems. Advanced topics: Nonlinear systems, chaos, discrete event systems, hybrid systems. | |||||

Lecture notes | Copy of transparencies | |||||

Literature | Recommended: K.J. Astrom and R. Murray, "Feedback Systems: An Introduction for Scientists and Engineers", Princeton University Press 2009 Link | |||||

Robotics | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

151-0854-00L | Autonomous Mobile Robots | W | 5 credits | 4G | R. Siegwart, M. Chli, N. Lawrance | |

Abstract | The objective of this course is to provide the basics required to develop autonomous mobile robots and systems. Main emphasis is put on mobile robot locomotion and kinematics, environment perception, and probabilistic environment modeling, localizatoin, mapping and navigation. Theory will be deepened by exercises with small mobile robots and discussed accross application examples. | |||||

Objective | The objective of this course is to provide the basics required to develop autonomous mobile robots and systems. Main emphasis is put on mobile robot locomotion and kinematics, environment perception, and probabilistic environment modeling, localizatoin, mapping and navigation. | |||||

Lecture notes | This lecture is enhanced by around 30 small videos introducing the core topics, and multiple-choice questions for continuous self-evaluation. It is developed along the TORQUE (Tiny, Open-with-Restrictions courses focused on QUality and Effectiveness) concept, which is ETH's response to the popular MOOC (Massive Open Online Course) concept. | |||||

Literature | This lecture is based on the Textbook: Introduction to Autonomous Mobile Robots Roland Siegwart, Illah Nourbakhsh, Davide Scaramuzza, The MIT Press, Second Edition 2011, ISBN: 978-0262015356 | |||||

151-0566-00L | Recursive Estimation | W | 4 credits | 2V + 1U | R. D'Andrea | |

Abstract | Estimation of the state of a dynamic system based on a model and observations in a computationally efficient way. | |||||

Objective | Learn the basic recursive estimation methods and their underlying principles. | |||||

Content | Introduction to state estimation; probability review; Bayes' theorem; Bayesian tracking; extracting estimates from probability distributions; Kalman filter; extended Kalman filter; particle filter; observer-based control and the separation principle. | |||||

Lecture notes | Lecture notes available on course website: Link | |||||

Prerequisites / Notice | Requirements: Introductory probability theory and matrix-vector algebra. | |||||

252-0579-00L | 3D Vision | W | 5 credits | 3G + 1A | M. Pollefeys, V. Larsson | |

Abstract | The course covers camera models and calibration, feature tracking and matching, camera motion estimation via simultaneous localization and mapping (SLAM) and visual odometry (VO), epipolar and mult-view geometry, structure-from-motion, (multi-view) stereo, augmented reality, and image-based (re-)localization. | |||||

Objective | After attending this course, students will: 1. understand the core concepts for recovering 3D shape of objects and scenes from images and video. 2. be able to implement basic systems for vision-based robotics and simple virtual/augmented reality applications. 3. have a good overview over the current state-of-the art in 3D vision. 4. be able to critically analyze and asses current research in this area. | |||||

Content | The goal of this course is to teach the core techniques required for robotic and augmented reality applications: How to determine the motion of a camera and how to estimate the absolute position and orientation of a camera in the real world. This course will introduce the basic concepts of 3D Vision in the form of short lectures, followed by student presentations discussing the current state-of-the-art. The main focus of this course are student projects on 3D Vision topics, with an emphasis on robotic vision and virtual and augmented reality applications. |

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