Computational Microscopy: Utilizing Image Processing and Neural Networks
www.wolfram.com/wolfram-u/ This event features demos and tutorials using Wolfram technologies for 2D and 3D image analysis and computer vision. Wolfram's integrated workflow combines high level image processing and machine learning in one system, allowing to solve a variety of problems fr
From playlist Computational Microscopy
Live from the ATLAS Experiment
Find out more about the ATLAS Experiment and recent upgrades of the detector.
From playlist 360° videos
Peng Wang - Electron Ptychography: Emerging Computational Microscopy for Physical/Biological Science
Recorded 28 October 2022. Peng Wang of the University of Warwick presents "Electron Ptychography: An Emerging Computational Microscopy for Physical and Biological Sciences" at IPAM's Mathematical Advances for Multi-Dimensional Microscopy Workshop. Abstract: Ptychography is an emerging comp
From playlist 2022 Mathematical Advances for Multi-Dimensional Microscopy
Computational Linear Algebra 7: Compressed Sensing for CT Scans
Course materials available here: https://github.com/fastai/numerical-linear-algebra Compressed sensing is critical to allowing CT scans with lower radiation-- the image can be reconstructed with less data. Here we will learn the technique and apply it to CT images. Numpy Broadcasting Spars
From playlist Computational Linear Algebra
Mahdi Soltanolkotabi - Machine Learning and Computational Imaging - IPAM at UCLA
Recorded 13 September 2022. Mahdi Soltanolkotabi of the University of Southern California (USC) ECE presents "Machine Learning and Computational Imaging" at IPAM's Computational Microscopy Tutorials. Abstract: In this tutorial I will discuss the challenges and opportunities of using AI for
From playlist Tutorials: Computational Microscopy 2022
Optimization meets machine learning for neuroimaging - Gramfort - Workshop 3 - CEB T1 2019
Alexandre Gramfort (INRIA) / 01.04.2019 Optimization meets machine learning for neuroimaging. Electroencephalography (EEG), Magnetoencephalography (MEG) and functional MRI (fMRI) are noninvasive techniques that allow to image the active brain. Yet to do so, challenging computational and
From playlist 2019 - T1 - The Mathematics of Imaging
DIY Scanning Electron Microscope - Overview
Today, I finally produced an image with my DIY scanning electron microscope. I've spent the last few months working on this project, and am encouraged by today's success. There is still a lot of work left to do in making the image higher resolution, and eliminating sources of noise, howe
From playlist Scanning Electron Microscope
Telescope projects now routinely obtain massive digital movies of the dynamic night's sky. But given the growing data volumes, coupled with the need to respond to transient events quickly with appropriate followup resources, it is no longer possible for people to be involved in the real-ti
From playlist What is math used for?
How To Create Image Processing App Using Microsoft Computer Vision API | Session 01 | #programming
Don’t forget to subscribe! In this project series, you will learn to create an image processing app, we will use Microsoft Computer Vision API to create an image processing app. In this project, we are going to walk through the Microsoft computer vision API, its use-cases, and applica
From playlist Create Image Processing App Using Microsoft Computer Vision API
Applications in Computer Vision Using Mathematica 10
For the latest information, please visit: http://www.wolfram.com Speaker: Matthias Odisio Wolfram developers and colleagues discussed the latest in innovative technologies for cloud computing, interactive deployment, mobile devices, and more.
From playlist Wolfram Technology Conference 2015
Jerome Darbon - Algorithms for Non-Local Filtering; application CryoElectron & biological microscopy
Recorded 15 September 2022. Jerome Darbon of Brown University presents "Efficient algorithms for Non-Local Filtering and applications to Cryo-Electron microscopy and biological microscopy" at IPAM's Computational Microscopy Tutorials. Abstract: We present fast and scalable algorithms for n
From playlist Tutorials: Computational Microscopy 2022
Lecture 12 | Visualizing and Understanding
In Lecture 12 we discuss methods for visualizing and understanding the internal mechanisms of convolutional networks. We also discuss the use of convolutional networks for generating new images, including DeepDream and artistic style transfer. Keywords: Visualization, t-SNE, saliency maps
From playlist Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)
MIT 6.S191: Convolutional Neural Networks
MIT Introduction to Deep Learning 6.S191: Lecture 3 Convolutional Neural Networks for Computer Vision Lecturer: Alexander Amini January 2022 For all lectures, slides, and lab materials: http://introtodeeplearning.com Lecture Outline - coming soon! Subscribe to stay up to date with new d
From playlist Introduction to Machine Learning
The Computer Chronicles - Computer Graphics (1984)
Special thanks to archive.org for hosting these episodes. Downloads of all these episodes and more can be found at: http://archive.org/details/computerchronicles
From playlist The Computer Chronicles 1984 Episodes
A friendly introduction to Convolutional Neural Networks and Image Recognition
Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML 40% discount code: serranoyt A friendly explanation of how computer recognize images, based on Convolutional Neural Networks. All the math required is knowing how to add and subtract 1's. (Bonus if you kn
From playlist Neural Networks
DeepMind x UCL | Deep Learning Lectures | 3/12 | Convolutional Neural Networks for Image Recognition
In the past decade, convolutional neural networks have revolutionised computer vision. In this lecture, DeepMind Research Scientist Sander Dieleman takes a closer look at convolutional network architectures through several case studies, ranging from the early 90's to the current state of t
From playlist Learning resources
Making Machines Creative. | Ali Eslami | TEDxWarwick
Through his experience as a research scientist at Google’s DeepMind, Ali Eslami guides us to a concrete understanding of what AI is, and how it relates to us. Contrary to popular belief, it’s not a new phenomenon — the term Al was actually coined back in 1956. What is more, fantastical Hol
From playlist Talks
Day 1: Learning to Tackle Real-World Computer Vision Applications
For more training resources, visit: http://www.wolfram.com/training/ Walk through the development of deep learning applications for the processing and analysis of images in the Wolfram Language. Real-world examples provide practical insights on how to effectively leverage neural networks
From playlist Wolfram Virtual Conference Series
John Miao - Coherent Diffractive Imaging: A Unification of Microscopy, Diffraction and Computation
Recorded 13 September 2022. Jianwei Miao of the University of California, Los Angeles, presents "Coherent Diffractive Imaging: A Unification of Microscopy, Diffraction and Computation" at IPAM's Computational Microscopy Tutorials. Learn more online at: http://www.ipam.ucla.edu/programs/wor
From playlist Tutorials: Computational Microscopy 2022