Pixels per inch (ppi) and pixels per centimetre (ppcm or pixels/cm) are measurements of the pixel density of an electronic image device, such as a computer monitor or television display, or image digitizing device such as a camera or image scanner. Horizontal and vertical density are usually the same, as most devices have square pixels, but differ on devices that have non-square pixels. Note that pixel density is not the same as resolutionโโโwhere the former describes the amount of detail on a physical surface or device, the latter describes the amount of pixel information regardless of its scale. Considered in another way, a pixel has no inherent size or unit (a pixel is actually a sample), but when it is printed, displayed, or scanned, then the pixel has both a physical size (dimension) and a pixel density (ppi). (Wikipedia).
What is an angle and it's parts
๐ Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
CCSS What is the difference between Acute, Obtuse, Right and Straight Angles
๐ Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
๐ Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
What are acute, obtuse, right, and straight angles
๐ Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
What are adjacent angles and linear pairs
๐ Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
๐ Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
Label the angle in three different ways
๐ Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
Determine the relationship between two angles
๐ Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
๐ Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
Lecture 19: Generative Models I
Lecture 19 is the first of two lectures about generative models. We compare supervised and unsupervised learning, and also compare discriminative vs generative models. We discuss autoregressive generative models that explicitly model densities, including PixelRNN and PixelCNN. We discuss a
From playlist Tango
What does density mean for your display device
In this lesson we discuss the concept of density (device pixel ratio) in terms of pixels for your display device.
From playlist Mobile web design
9.23: createGraphics() - p5.js Tutorial
In this video, I discuss the p5.js function createGraphics(). createGraphics() creates a 2D graphics "context" (also sometimes called "buffer") that you can use as an "offscreen canvas." createGraphics() as WebGL Texture: https://youtu.be/3tTZlTq4Cxs Support this channel on Patreon: http
From playlist 9: Additional Topics - p5.js Tutorial
11.3: The Pixel Array - p5.js Tutorial
This video looks at how to access the pixels of an HTML5 canvas in p5.js. ๐ป Code: https://editor.p5js.org/codingtrain/sketches/A92PDk-1z ๐ฅ Next video: https://youtu.be/rNqaw8LT2ZU ๐Website: https://thecodingtrain.com/ ๐กGithub: https://github.com/CodingTrain ๐ฌDiscord: https://discord.gg/h
From playlist 11: Video and Pixels - p5.js Tutorial
This is the first in a sequence of videos about images. It describes the fundamental principles of a bitmap image, namely, that a bitmap is a rectangular grid of picture elements known as pixels. It explains how pixel density, which is known as the image resolution, and the number of bit
From playlist Images
Working with Images and Notebooks on Your Hi-Res Display
This talk features Ian Hojnicki giving a brief overview of resolution independence and our support for it in Wolfram Language 12.1's user interface. Also discussed are some common issues that come up and how to go about fixing them.
From playlist Wolfram Technology Conference 2020
Lecture 13 | Generative Models
In Lecture 13 we move beyond supervised learning, and discuss generative modeling as a form of unsupervised learning. We cover the autoregressive PixelRNN and PixelCNN models, traditional and variational autoencoders (VAEs), and generative adversarial networks (GANs). Keywords: Generative
From playlist Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)
Iain Murray: "Density Estimation"
Graduate Summer School 2012: Deep Learning, Feature Learning "Density Estimation" Iain Murray, University of Edinburgh Institute for Pure and Applied Mathematics, UCLA July 26, 2012 For more information: https://www.ipam.ucla.edu/programs/summer-schools/graduate-summer-school-deep-learn
From playlist GSS2012: Deep Learning, Feature Learning
Fractal Flame, Let's go! (Day 2)
continuing our fractal flame saga! -- Watch live at https://www.twitch.tv/simuleios
From playlist Fractal
I.5: 2D Noise - Perlin Noise and p5.js Tutorial
In the fifth part of my Perlin Noise Tutorial, I demonstrate how to use two-dimensional Perlin noise in a p5.js sketch. ๐ป Code: https://thecodingtrain.com/learning/noise/0.5-2d-noise.html ๐ป Code (web editor): https://editor.p5js.org/codingtrain/sketches/2_hBcOBrF ๐ฅ Next video: https://yo
From playlist 13: What is Perlin Noise?
Find the reference angle of a angle larger than 2pi
๐ Learn how to find the reference angle of a given angle. The reference angle is the acute angle formed by the terminal side of an angle and the x-axis. To find the reference angle, we determine the quadrant on which the given angle lies and use the reference angle formula for the quadrant
From playlist Find the Reference Angle