Fourier Optics Aperture Function Explained
https://www.patreon.com/edmundsj If you want to see more of these videos, or would like to say thanks for this one, the best way you can do that is by becoming a patron - see the link above :). And a huge thank you to all my existing patrons - you make these videos possible. In this video
From playlist Fourier Optics
Mario Figueiredo: ADMM in Imaging Inverse Problems: Some History and Recent Advances
Abstract: The alternating direction method of multipliers (ADMM) is an optimization tool of choice for several imaging inverse problems, namely due its flexibility, modularity, and efficiency. In this talk, I will begin by reviewing our earlier work on using ADMM to deal with classical pro
From playlist Analysis and its Applications
Flat-Interface Refraction Ray Transfer Matrix
https://www.patreon.com/edmundsj If you want to see more of these videos, or would like to say thanks for this one, the best way you can do that is by becoming a patron - see the link above :). And a huge thank you to all my existing patrons - you make these videos possible. Here I derive
From playlist Geometric Optics
Ray Transfer Matrices Explained
https://www.patreon.com/edmundsj If you want to see more of these videos, or would like to say thanks for this one, the best way you can do that is by becoming a patron - see the link above :). And a huge thank you to all my existing patrons - you make these videos possible. Ray transfer
From playlist Geometric Optics
Function Orthogonality Explained
https://www.patreon.com/edmundsj If you want to see more of these videos, or would like to say thanks for this one, the best way you can do that is by becoming a patron - see the link above :). And a huge thank you to all my existing patrons - you make these videos possible. In this video
From playlist Optoelectronic and Photonic Devices
Wavelets: a mathematical microscope
Wavelet transform is an invaluable tool in signal processing, which has applications in a variety of fields - from hydrodynamics to neuroscience. This revolutionary method allows us to uncover structures, which are present in the signal but are hidden behind the noise. The key feature of w
From playlist Fourier
Physics: Optics- Thick Lenses (17 of 56) How Do Refracting and Transfer Equations Work?
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain in detail of how does the refracting and transfer equations work. Next video in this series can be seen at: https://youtu.be/0EJXeVNKYr8
From playlist PHYSICS 55.3 THICK LENSES
Lens Aperture Function Explained
https://www.patreon.com/edmundsj If you want to see more of these videos, or would like to say thanks for this one, the best way you can do that is by becoming a patron - see the link above :). And a huge thank you to all my existing patrons - you make these videos possible. In this video
From playlist Fourier Optics
https://www.patreon.com/edmundsj If you want to see more of these videos, or would like to say thanks for this one, the best way you can do that is by becoming a patron - see the link above :). And a huge thank you to all my existing patrons - you make these videos possible. Here I derive
From playlist Geometric Optics
Part 3: CTF Correction - G. Jensen
From playlist Getting Started in Cryo-EM
Style Transfer Part 2: Real-Time Style Transfer with ml5.js with Yining Shi
In this video, Yining Shi uses this trained model to style a real-time image, in browser, using ml5.js and p5.js. #ThisDotStyle #StyleTransfer #MachineLearning To sign up to Spell: https://spell.run/codingtrain 🎥 Part 1: https://youtu.be/STHRNIJc-vI This video is sponsored by Spell. 🔗
From playlist Machine Learning with TensorFlow, ml5.js, and Spell
Style Transfer using Spell with Yining Shi
In this live stream, Yining Shi demonstrates how to train a "Style Transfer Model" using Spell (Sign up here: https://spell.run/codingtrain). After training the model, Yining writes code to process new images in the browser with ml5.js. #ThisDotStyle #StyleTransfer #MachineLearning This s
From playlist Machine Learning with TensorFlow, ml5.js, and Spell
DSI | Neural Representations for Volume Visualization by Josh Levine
In this talk, I will describe two projects, both joint work with collaborators at Vanderbilt University. The first project studies how generative neural models can be used to model the process of volume rendering scalar fields. We construct a generative adversarial network that learns th
From playlist DSI Virtual Seminar Series
Pratik Chaudhari: "Learning with few labeled data"
High Dimensional Hamilton-Jacobi PDEs 2020 Workshop II: PDE and Inverse Problem Methods in Machine Learning "Learning with few labeled data" Pratik Chaudhari - University of Pennsylvania Abstract: The human visual system is proof that it is possible to learn new categories with extremely
From playlist High Dimensional Hamilton-Jacobi PDEs 2020
Semantic Adversarial Attacks for Privacy Protection
A Google TechTalk, 2020/7/30, presented byAli Shahin Shamsabadi, Ricardo Sanchez-Matilla, Andrea Cavallaro, Queen Mary University of London ABSTRACT: Images shared on social media are routinely analyzed by machine learning models for content annotation and user profiling. These automatic
From playlist 2020 Google Workshop on Federated Learning and Analytics
Notion Link: https://ebony-scissor-725.notion.site/Henry-AI-Labs-Weekly-Update-July-15th-2021-a68f599395e3428c878dc74c5f0e1124 Chapters 0:00 Introduction 2:18 Improvements in Video Modeling 6:08 Vokenization 7:31 HowTo100M Data 9:07 Teacher Learning 13:06 Interesting Distillation Ideas 17
From playlist AI Weekly Update - July 15th, 2021!
Antoine Cornuejols - Transfer Learning, Covariant Learning and Parallel Transport
Transfer learning has become increasingly important in recent years, particularly because learning a new model for each task can be much more costly in terms of training examples than adapting a model learned for another task. The standard approach in neural networks is to reuse the learne
From playlist 8th edition of the Statistics & Computer Science Day for Data Science in Paris-Saclay, 9 March 2023
TensorFlow Tutorial 09 - Transfer Learning
New Tutorial series about TensorFlow 2! Learn all the basics you need to get started with this deep learning framework! Part 09: Transfer Learning In this part we improve our model from last time to classify Lego Star Wars Minifigures. We use Transfer Learning for this. A very simple yet
From playlist TensorFlow 2 Beginner Course
What are the Inverse Trigonometric functions and what do they mean?
👉 Learn how to evaluate inverse trigonometric functions. The inverse trigonometric functions are used to obtain theta, the angle which yielded the trigonometric function value. It is usually helpful to use the calculator to calculate the inverse trigonometric functions, especially for non-
From playlist Evaluate Inverse Trigonometric Functions