Image noise

Photoshop: Sharpening and Noise Reduction

In this video, you’ll learn more about sharpening and noise reduction in Photoshop. Visit https://www.gcflearnfree.org/photoshopbasics/sharpening-and-noise-reduction/1/ for our text-based lesson. This video includes information on: • Sharpening tips • Noise-reduction tips We hope you enj

From playlist Photoshop

Sound waves interference!

In this video i demonstrate sound waves interference and standing waves from loudspeaker used sound sensor. The frequency on loudspeaker is about 5500Hz. Enjoy!!!

From playlist WAVES

What Is White Noise?

Jonathan defines what white noise actually is and how it's used to mask other annoying sounds. Learn more at HowStuffWorks.com: http://science.howstuffworks.com/question47.htm Share on Facebook: http://goo.gl/n7YNrZ Share on Twitter: http://goo.gl/Fq9InS Subscribe: http://goo.gl/ZYI7Gt V

From playlist Episodes hosted by Jonathan

One of the loudest underwater sounds is made by an animal you wouldn’t expect

Here’s a hint: It has something to do with mating Keep reading: http://scim.ag/2CE1DuQ

From playlist Animals

Sound Effect III

This is a video response to RootBerry Sound Effect Contest. I saw a man who could play music like that. I'm not that good, though. Anyway, forgive me for that. ;~)

From playlist Other...

Sound Effect I

This is a video response to RootBerry Sound Effect Contest. I've been able to do this sound since I was a kid and I've never met anybody else who could do it... Anyway, forgive me for that. ;~)

From playlist Other...

Show Me Some Science! Speed Of Sound

Sound is a wave which travels through the air at about 330 m/s. The Little Shop of Physics Crew dances to the music together. When spread out along the track, it takes about a third of a second for the sound to travel from the first person to the last. The crew is blindfolded, so there are

From playlist Show Me Some Science!

Most Annoying Sound Ever!

Learn to make the most annoying sound ever. And possibly the loudest sound ever using a tiny piece of paper.

From playlist How to videos!

Data Noise | Introduction to Data Mining part 8

In this Data Mining Fundamentals tutorial, we discuss data noise that can overlap valid data and outliers. Noise can appear because of human inconsistency and labeling. We will provide you with several examples of data noise, and how data noise can be measured and recorded. -- Learn more a

From playlist Introduction to Data Mining

Learning Robust Imaging Models without Paired Data

44th Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series Talk Date: Wednesday, May 25, 10:00am Eastern Speaker: Prof. Chenglong Bao, Tsinghua University Abstract : The observations in practical imaging systems always contain complex noise such that classical appro

From playlist Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series

Diffusion Models | Paper Explanation | Math Explained

Diffusion Models are generative models just like GANs. In recent times many state-of-the-art works have been released that build on top of diffusion models such as #dalle or #imagen. In this video I give a detailed explanation of how they work. At first I explain the fundamental idea of th

From playlist Paper Explanations

DDPM - Diffusion Models Beat GANs on Image Synthesis (Machine Learning Research Paper Explained)

#ddpm #diffusionmodels #openai GANs have dominated the image generation space for the majority of the last decade. This paper shows for the first time, how a non-GAN model, a DDPM, can be improved to overtake GANs at standard evaluation metrics for image generation. The produced samples l

From playlist Papers Explained

Deep Decoder: Concise Image Representations from Untrained Networks (Lecture 2) by Paul Hand

DISCUSSION MEETING THE THEORETICAL BASIS OF MACHINE LEARNING (ML) ORGANIZERS: Chiranjib Bhattacharya, Sunita Sarawagi, Ravi Sundaram and SVN Vishwanathan DATE : 27 December 2018 to 29 December 2018 VENUE : Ramanujan Lecture Hall, ICTS, Bangalore ML (Machine Learning) has enjoyed tr

From playlist The Theoretical Basis of Machine Learning 2018 (ML)

Juan Carlos De los Reyes: Bilevel learning approaches in variational image ....

In order to determine the noise model in corrupted images, we consider a bilevel optimization approach in function space with the variational image denoising models as constraints. In the flavour of supervised machine learning, the approach presupposes the existence of a training set of cl

From playlist HIM Lectures: Trimester Program "Multiscale Problems"

GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

#glide #openai #diffusion Diffusion models learn to iteratively reverse a noising process that is applied repeatedly during training. The result can be used for conditional generation as well as various other tasks such as inpainting. OpenAI's GLIDE builds on recent advances in diffusion

From playlist Papers Explained

CERIAS Security: Forensics Characterization of Printers and Image Capture devices 2/5

Clip 2/5 Speaker: Nitin Khanna Forensic techniques can be used to uniquely identify each device using the data it produces. This is different from simply securing the data being sent across the network because we are also authenticating the sensor that is creating the data. Fore

From playlist The CERIAS Security Seminars 2006

Lesson 9A 2022 - Stable Diffusion deep dive

Johno shows us what is happening behind the scenes when we create an image with Stable Diffusion, looking at the different components and processes and how each can be modified for further control over the generation process. The notebook is available in this repository: https://github.com

From playlist Practical Deep Learning 2022 Part 2

Lesson 22: Deep Learning Foundations to Stable Diffusion

Oops I say it's "Lesson 21" at the start of the video -- but actually this is lesson 22! (All lesson resources are available at http://course.fast.ai.) Jeremy begins this lesson with a discussion of improvements to the DDPM/DDIM implementation. He explores the removal of the concept of an

From playlist Practical Deep Learning 2022 Part 2

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 2 - Deep Learning Intuition

Andrew Ng, Adjunct Professor & Kian Katanforoosh, Lecturer - Stanford University https://stanford.io/3eJW8yT Andrew Ng Adjunct Professor, Computer Science Kian Katanforoosh Lecturer, Computer Science To follow along with the course schedule and syllabus, visit: http://cs230.stanford.

From playlist Stanford CS230: Deep Learning | Autumn 2018

Sound vs. Noise: What’s the Actual Difference? (Part 1 of 3)

Noise and sound are not the same thing… really, they aren’t! What exactly is noise? Part 2 of 3 - https://youtu.be/XhFhK97hrdY Part 3 of 3 - https://youtu.be/yTyYZFcxGGQ Read More: Signal-to-Noise Ratio and Why It Matters https://www.lifewire.com/signal-to-noise-ratio-3134701 “You

From playlist Seeker Plus