All Videos Tagged networks (Grasshopper) - Grasshopper

Crow Tutorial1: Neural Sensing and Control in Grasshopper

2017-10-10T13:43:45.819Z

Supervised learning is a branch of machine learning in which a mapping function is programmed into a neural network by exposing examples to the network (training).
This tutorial shows how to use the plug in Crow to classify certain environmental states (based on sensor data) and relate them to a parametric model, hence a neural network classifies sensor states and maps them to respective parametric outputs.

All the files can be found here:
https://github.com/HeinzBenjamin/Crow/tree/master/Study%20Material/Supervised%20Learning/Sensor_classification

...and here:
http://www.food4rhino.com/app/crow-artificial-neural-networks

Rainbow Dog | 2-Dimensional Self-Organizing Maps using Crow in Grasshopper

2016-06-20T23:46:30.846Z

This videos shows the use of the plug-in Crow for Grasshopper in Rhino5. It employs artificial neural networks - specifically a 2-dimensional Kohonen layer, known as self-organizing maps - to fit data vectors of three, four or five dimensions through a set of given training data.
Crow is an extension of NeuronDotNet.dll developed by the NeuronDotNetTeam

Get Crow here: http://www.felbrich.com/projects/Crow/Crow.html

Learning curves

2016-06-01T12:52:03.941Z

ANN learning some properties of various curves.

Slime-mold Networking

2015-07-03T09:06:08.116Z

this is a 3D representation of 2D bottom up system, which can connect points(food) by approximating steiner graphs. This system has been used in infrastructural research on multiple occasions. Have you seen:

https://www.youtube.com/watch?v=GwKuFREOgmo
http://www.economist.com/node/15328524

I have developed it based on references shared by David Reeves:

https://vimeo.com/123547307

Crow - Artificial neural network component for Grasshopper

2014-07-21T14:32:52.017Z

This clip shows a short demo of the plugin "Crow" for Grasshopper in Rhino. It employs artificial neural nets such as Kohonen networks and classic backpropagation networks to remap given topologies into odd point clouds (TSP and Seolf Organizing maps). Furthermore it can be used for petterns recongition.

For more infos about Crow visit: www.felbrich.com/projects/Crow/Crow.html