TronixLab/Neurona-rgbClassifier
An easy guide for Color classification (RGB) using Multilayer Perceptron (MLP) Neural Networks with Arduino
This project helps hobbyists and makers add color recognition capabilities to their Arduino projects. By connecting an RGB color sensor, it takes in raw color readings and classifies them into predefined color categories, making it easy to build devices that respond to different colors. This is ideal for anyone working on small-scale automation or interactive projects with microcontrollers.
Use this if you want to implement simple color classification directly on an Arduino or compatible microcontroller without needing a more powerful computer.
Not ideal if you need to classify very subtle color differences, require real-time video processing, or are working with complex image analysis.
Stars
8
Forks
4
Language
C
License
—
Category
Last pushed
Jan 15, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/TronixLab/Neurona-rgbClassifier"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
Devignitor/Single-neuron-model-Simple-Neural-Network
Single-neuron model trained by gradient descent. It is the most fundamental simple neural network.
sushantPatrikar/XOR-Gate-With-Neural-Network-Using-Numpy
XOR gate which predicts the output using Neural Network :fire:
casparwylie/Perceptron
A flexible artificial neural network builder to analyse performance, and optimise the best model.
pasqal-io/perceptrain
Machine learning training, simplified, at scale
devleo-m/ia-perceptron
Basic implementation of a Perceptron in Python. The Perceptron is trained with input data,...