In 3D computer graphics, hidden-surface determination (also known as shown-surface determination, hidden-surface removal (HSR), occlusion culling (OC) or visible-surface determination (VSD)) is the process of identifying what surfaces and parts of surfaces can be seen from a particular viewing angle. A hidden-surface determination algorithm is a solution to the visibility problem, which was one of the first major problems in the field of 3D computer graphics. The process of hidden-surface determination is sometimes called hiding, and such an algorithm is sometimes called a hider. When referring to line rendering it is known as hidden-line removal. Hidden-surface determination is necessary to render a scene correctly, so that one may not view features hidden behind the model itself, allowing only the naturally viewable portion of the graphic to be visible. (Wikipedia).
Surface Area of Prisms and Pyramids
This video is about finding the Surface Area of Prisms and Pyramids
From playlist Surface Area and Volume
Area of a Parameterized Surface
This video explains how to determine the area of parameterized surface and introduced a surface integral. http://mathispower4u.wordpress.com/
From playlist Surface Integrals
Ex: Evaluate a Surface Integral (Basic Explicit Surface - Plane Over Rectangle)
This video explains how to evaluate a surface integral. The surface is given as a an explicit equation. http://mathispower4u.com
From playlist Surface Integrals
This video defines a cylindrical surface and explains how to graph a cylindrical surface. http://mathispower4u.yolasite.com/
From playlist Quadric, Surfaces, Cylindrical Coordinates and Spherical Coordinates
The Divergence Theorem - Part 2
This video explains how to apply the divergence theorem to determine the flux of a vector field. http://mathispower4u.wordpress.com/
From playlist Surface Integrals
(New Version Available) Parameterized Surfaces
New Version: https://youtu.be/0kKBPbmzwm8 This video explains how to parameterized a equation of a surface. http://mathispower4u.wordpress.com/
From playlist Surface Integrals
Use Traces of a Surface to Select the Equation of the Surface (Ex 2)
This video explains how to determine the traces of function of two variables and then match given traces to the correct function. http://mathispower4u.com
From playlist Functions of Several Variables
Lecture 8/16 : More recurrent neural networks
Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] 8A A brief overview of "Hessian-Free" optimization 8B Modeling character strings with multiplicative connections 8C Learning to predict the next character using HF 8D Echo state networks
From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]
Neural Networks Pt. 4: Multiple Inputs and Outputs
So far, this series has explained how very simple Neural Networks, with only 1 input and 1 output, function. This video shows how these exact same concepts generalize to multiple inputs and outputs and provides a context within we can discuss SoftMax and ArgMax for modifying the output dat
From playlist StatQuest
Why are neural networks so effective?
Visuals to demonstrate how a neural network classifies a set of data. Thanks for watching! Support me on Patreon! https://patreon.com/vcubingx Source Code: https://github.com/vivek3141/dl-visualization Here's the course I referred to in the video. I am not affiliated with NYU. https://www
From playlist Visualizing Deep Learning
Does Consciousness Have Meaning? | Episode 703 | Closer To Truth
How has "inner experience" radically emerged from cosmic dust? Is consciousness only an accident of biology? Or does consciousness have deeper meaning? Featuring interviews with Ned Block, Marvin Minsky, Alva Noë, Jaron Lanier, and Colin McGinn. Season 7, Episode 3 - #CloserToTruth ▶Reg
From playlist Closer To Truth | Season 7
On cyclic Higgs bundles (Remote Talk) by Qiongling Li
Surface Group Representations and Geometric Structures DATE: 27 November 2017 to 30 November 2017 VENUE:Ramanujan Lecture Hall, ICTS Bangalore The focus of this discussion meeting will be geometric aspects of the representation spaces of surface groups into semi-simple Lie groups. Classi
From playlist Surface Group Representations and Geometric Structures
From playlist Surface integrals
Important Unmanned Missions To The Moon Before Artemis I [4K] | The New Frontier | Spark
It may not be as spectacular as the Apollo landings but the robotic exploration of the moon has surged in recent years. The achievements of these unmanned probes are recounted. And permanent manned moon bases are back in future plans of several national and private space programs. --- Sub
From playlist The New Frontier | Spark
Hidden Order: Hyperuniformity and Rigidity by Joel Lebowitz
DISCUSSION MEETING : STATISTICAL PHYSICS OF COMPLEX SYSTEMS ORGANIZERS : Sumedha (NISER, India), Abhishek Dhar (ICTS-TIFR, India), Satya Majumdar (University of Paris-Saclay, France), R Rajesh (IMSc, India), Sanjib Sabhapandit (RRI, India) and Tridib Sadhu (TIFR, India) DATE : 19 December
From playlist Statistical Physics of Complex Systems - 2022
The Hubble Telescope found more evidence of vast plumes of water bursting through the icy surface of Jupiter’s moon Europa. What does this tell us about the potential for life on Europa? Get your own Space Time tshirt at http://bit.ly/1QlzoBi Tweet at us! @pbsspacetime Facebook: facebook
From playlist Ocean Worlds Playlist
Lecture 6/16 : Optimization: How to make the learning go faster
Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] 6A Overview of mini-batch gradient descent 6B A bag of tricks for mini-batch gradient descent 6C The momentum method 6D A separate, adaptive learning rate for each connection 6E rmsprop: Divide the gradient by a runni
From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]
Sandra van Aert - 3D atomic resolution through dose-efficient fusion of image & analytical technique
Recorded 26 October 2022. Sandra van Aert of the University of Antwerp presents "3D atomic resolution reconstructions through dose-efficient fusion of imaging techniques and analytical techniques in quantitative STEM" at IPAM's Mathematical Advances for Multi-Dimensional Microscopy Worksho
From playlist 2022 Mathematical Advances for Multi-Dimensional Microscopy
The Divergence Theorem - Part 1
This video explains how to apply the divergence theorem to determine the flux of a vector field. http://mathispower4u.wordpress.com/
From playlist Surface Integrals