The problem of reconstructing a multidimensional signal from its projection is uniquely multidimensional, having no 1-D counterpart. It has applications that range from computer-aided tomography to geophysical signal processing. It is a problem which can be explored from several points of view—as a deconvolution problem, a modeling problem, an estimation problem, or an interpolation problem. (Wikipedia).
Recordings of the corresponding course on Coursera. If you are interested in exercises and/or a certificate, have a look here: https://www.coursera.org/learn/pca-machine-learning
From playlist Projections
A solar system, a simulation made with Excel
An Excel simulation of the solar system. You can see how things are recursively computed: the mutual gravity force from the locations, the accelerations, the velocities, and finally the updated locations. The solar eclipse is also shown. This is clip is intended to illustrate Chapter 24 Ap
From playlist Physics simulations
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist 3D Printing
Projections (video 2): Projection onto 1D Subspaces
Recordings of the corresponding course on Coursera. If you are interested in exercises and/or a certificate, have a look here: https://www.coursera.org/learn/pca-machine-learning
From playlist Projections
Projections (video 4): N-dimensional projections
Recordings of the corresponding course on Coursera. If you are interested in exercises and/or a certificate, have a look here: https://www.coursera.org/learn/pca-machine-learning
From playlist Projections
NuFormer 3D Video Mapping Projection on Buildings
NuFormer 3D Video Mapping Projection on Buildings Impressive and stylish projections on buildings, a renewing way of communicating. For those who want to carry out a message in a striking and visually attractive way with guaranteed exposure: 3D Projection on buildings is the communication
From playlist Projection Mapping inspirations
In this video, I define the concept of orthogonal projection of a vector on a line (and on more general subspaces), derive a very nice formula for it, and show why orthogonal projections are so useful. You might even see the hugging formula again. Enjoy! This is the second part of the ort
From playlist Orthogonality
What to do with all those old PCBs from stuff you've taken apart...
From playlist Projects & Installations
What is the projection of one vector on another one and how is it useful? Free ebook https://bookboon.com/en/introduction-to-vectors-ebook (updated link) Test your understanding via a short quiz http://goo.gl/forms/CpZUX1mFLS
From playlist Introduction to Vectors
Measurements vs. Bits: Compressed Sensors and Info Theory
October 18, 2006 lecture by Dror Baron for the Stanford University Computer Systems Colloquium (EE 380). Dror Baron discusses the numerous rich insights information theory has to offer Compressed Sensing (CS), an emerging field based on the revelation that optimization routines can reco
From playlist Course | Computer Systems Laboratory Colloquium (2006-2007)
Holographic Tomography | MIT 2.71 Optics, Spring 2009
Holographic Tomography Instructor: Aditya Bhakta, Danny Codd View the complete course: http://ocw.mit.edu/2-71S09 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 2.71 Optics, Spring 2009
Seminar on Applied Geometry and Algebra (SIAM SAGA): Rekha Thomas
Date: Tuesday, November 10 at 11:00am EST (5:00pm CET) Speaker: Rekha Thomas, University of Washington Title: When Two Cameras Meet a Cubic Surface Abstract: The set of images captured by an arrangement of pinhole cameras is usually modeled by the multiview variety. The true set is in f
From playlist Seminar on Applied Geometry and Algebra (SIAM SAGA)
Yongsoo Yang - Neural network-assisted atomic electron tomography - IPAM at UCLA
Recorded 26 October 2022. Yongsoo Yang of the Korea Advanced Institute of Science and Technology presents "Neural network-assisted atomic electron tomography" at IPAM's Mathematical Advances for Multi-Dimensional Microscopy Workshop. Abstract: Functional properties of nanomaterials strongl
From playlist 2022 Mathematical Advances for Multi-Dimensional Microscopy
Manuel Guizar-Sicairos - Resonant ptychography, 3D magnetization and chemical characterization
Recorded 10 October 2022. Manuel Guizar-Sicairos of the Paul Scherrer Institute presents "Resonant ptychography, applications to 3D magnetization and chemical characterization" at IPAM's Diffractive Imaging with Phase Retrieval Workshop. Abstract: Ptychography is an imaging technique that
From playlist 2022 Diffractive Imaging with Phase Retrieval - - Computational Microscopy
Tim Salditt - Phase Retrieval & Tomographic Reconstruction in X-ray Near-field Diffractive Imaging
Recorded 11 October 2022. Tim Salditt of the Georg-August-Universität zu Göttingen presents "Phase Retrieval and Tomographic Reconstruction in X-ray Near-field Diffractive Imaging: Inverse Problems at Work - An Experimentalist’s View" at IPAM's Diffractive Imaging with Phase Retrieval Work
From playlist 2022 Diffractive Imaging with Phase Retrieval - - Computational Microscopy
Ayelet Heimowitz - Center of Mass Alignment for Noisy Tomographic Projections - IPAM at UCLA
Recorded 17 November 2022. Ayelet Heimowitz of Ariel University presents "Center of Mass Alignment for Noisy Tomographic Projections" at IPAM's Cryo-Electron Microscopy and Beyond Workshop. Abstract: Under the weak-phase object approximation, the center of mass of a 3-D macromolecule is pr
From playlist 2022 Cryo-Electron Microscopy and Beyond
DEMONSTRATIONS with REMOVED FIGURE MODELS #9
More demonstrations on foreshortening.
From playlist DEMONSTRATIONS with REMOVED FIGURE MODELS
From shallow to deep learning for inverse imaging problems - Carola-Bibiane Schönlieb, Cambridge
This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data science” — brings together leading researchers in the general fields of mathematics, statistics, computer science and engineering. About the event The workshop ai
From playlist Mathematics of data: Structured representations for sensing, approximation and learning
