The neocognitron is a hierarchical, multilayered artificial neural network proposed by Kunihiko Fukushima in 1979. It has been used for Japanese handwritten character recognition and other pattern recognition tasks, and served as the inspiration for convolutional neural networks. The neocognitron was inspired by the model proposed by Hubel & Wiesel in 1959. They found two types of cells in the visual primary cortex called simple cell and complex cell, and also proposed a cascading model of these two types of cells for use in pattern recognition tasks. The neocognitron is a natural extension of these cascading models. The neocognitron consists of multiple types of cells, the most important of which are called S-cells and C-cells. The local features are extracted by S-cells, and these features' deformation, such as local shifts, are tolerated by C-cells. Local features in the input are integrated gradually and classified in the higher layers. The idea of local feature integration is found in several other models, such as the Convolutional Neural Network model, the SIFT method, and the HoG method. There are various kinds of neocognitron. For example, some types of neocognitron can detect multiple patterns in the same input by using backward signals to achieve selective attention. (Wikipedia).
FERROFLUID underwater LIQUID MAGNET to NEODYMIUM Rare earth micro plastic
Ferrofluid is a magnetically active compound attracted to a rare earth or neodymium magnet that is dispersed throughout another substance or organic solvent resulting in micro particles and plastics to attach. It changes shapes and can demonstrate magnetic flux. flhttp://www.greenpowerscie
From playlist neodymium magnets GREENPOWERSCIENCE
AWESOME antigravity electromagnetic levitator (explaining simply)
Physics levitron (science experiments)
From playlist ELECTROMAGNETISM
In quantum mechanics, a boson is a particle that follows Bose–Einstein statistics. Bosons make up one of the two classes of particles, the other being fermions. The name boson was coined by Paul Dirac to commemorate the contribution of the Indian physicist Satyendra Nath Bose in developing
From playlist Science Unplugged: Particle Physics
4 Algorithms We Borrowed from Nature
We use algorithms every day for things like image searches, predictive text, and securing sensitive data. Algorithms show up all over nature, too, in places like your immune system and schools of fish, and computer scientists have learned a lot from studying them. Here are four ways our te
From playlist Biology
Lecture 5 | Convolutional Neural Networks
In Lecture 5 we move from fully-connected neural networks to convolutional neural networks. We discuss some of the key historical milestones in the development of convolutional networks, including the perceptron, the neocognitron, LeNet, and AlexNet. We introduce convolution, pooling, and
From playlist Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)
Unsupervised Brain Models - How does Deep Learning inform Neuroscience? (w/ Patrick Mineault)
#deeplearning #brain #neuroscience Originally, Deep Learning sprang into existence inspired by how the brain processes information, but the two fields have diverged ever since. However, given that deep models can solve many perception tasks with remarkable accuracy, is it possible that we
From playlist Papers Explained
[ML News] Microsoft trains 530B model | ConvMixer model fits into single tweet | DeepMind profitable
#mlnews #turingnlg #convmixer Your latest upates on what's happening in the Machine Learning world. OUTLINE: 0:00 - Intro 0:16 - Weights & Biases raises on 1B valuation (sponsored) 2:30 - Microsoft trains 530 billion parameter model 5:15 - StyleGAN v3 released 6:45 - A few more examples
From playlist All Videos
AMMI Course "Geometric Deep Learning" - Lecture 1 (Introduction) - Michael Bronstein
Video recording of the course "Geometric Deep Learning" taught in the African Master in Machine Intelligence in July-August 2021 by Michael Bronstein (Imperial College/Twitter), Joan Bruna (NYU), Taco Cohen (Qualcomm), and Petar Veličković (DeepMind) Lecture 1: Symmetry through the centur
From playlist AMMI Geometric Deep Learning Course - First Edition (2021)
NOvA: Building a Next Generation Neutrino Experiment
The NOvA neutrino experiment is searching for the answers to some of the most fundamental questions of the universe. This video documents how collaboration between government research institutions like Fermilab, academia and industry can create one of the largest neutrino detectors in the
From playlist Neutrinos
AMMI 2022 Course "Geometric Deep Learning" - Lecture 1 (Introduction) - Michael Bronstein
Video recording of the course "Geometric Deep Learning" taught in the African Master in Machine Intelligence in July 2022 by Michael Bronstein (Oxford), Joan Bruna (NYU), Taco Cohen (Qualcomm), and Petar Veličković (DeepMind) Lecture 1: Symmetry through the centuries • First neural networ
From playlist AMMI Geometric Deep Learning Course - Second Edition (2022)
Deep Learning | Stanford CS221: AI (Autumn 2019)
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3mk0qCV Topics: Deep learning, autoencoders, CNNs, RNNs Reid Pryzant, PhD Candidate & Head Course Assistant http://onlinehub.stanford.edu/ To follow along with th
From playlist Stanford CS221: Artificial Intelligence: Principles and Techniques | Autumn 2019
AMMI 2022 Course "Geometric Deep Learning" - Lecture 7 (Grids) - Joan Bruna
Video recording of the course "Geometric Deep Learning" taught in the African Master in Machine Intelligence in July 2022 by Michael Bronstein (Oxford), Joan Bruna (NYU), Taco Cohen (Qualcomm), and Petar Veličković (DeepMind) Lecture 1: Symmetry through the centuries • First neural networ
From playlist AMMI Geometric Deep Learning Course - Second Edition (2022)
Neodymium - Periodic Table of Videos
Neodymium is element number 60. More links in description below ↓↓↓ Support Periodic Videos on Patreon: https://www.patreon.com/periodicvideos A video on every element: http://bit.ly/118elements More at http://www.periodicvideos.com/ Follow us on Facebook at http://www.facebook.com/peri
From playlist With Portuguese subtitles (Português) - Periodic Videos
Lecture 1: A Brief History of Geometric Deep Learning - Michael Bronstein
Video recording of the First Italian Summer School on Geometric Deep Learning, which took place in July 2022 in Pescara. Slides: https://www.sci.unich.it/geodeep2022/slides/Pescara%202022%20-%20Intro.pdf
From playlist First Italian School on Geometric Deep Learning - Pescara 2022
Subscribe to our YouTube Channel for all the latest from World Science U. Visit our Website: http://www.worldscienceu.com/ Like us on Facebook: https://www.facebook.com/worldscienceu Follow us on Twitter: https://twitter.com/worldscienceu
From playlist Science Unplugged: Particle Physics
Nuclear Physics C1 The Neutrino
The neutrino and antineutrino
From playlist Physics - Nuclear Physics and Radioactivity
The Long Story of How Neural Nets Got to Where They Are: A Conversation with Terry Sejnowski
Stephen Wolfram plays the role of Salonnière in this on-going series of intellectual explorations with special guests. Watch all of the conversations here: https://wolfr.am/youtube-sw-conversations Originally livestreamed at: https://twitch.tv/stephen_wolfram 00:00 Start stream 5:26 SW st
From playlist Conversations with Special Guests
"Milk" was released as the fifth and final single from their 1995 platinum debut album Garbage.
From playlist NeoTango