ARDUINO BOARD

Artist research using Arduino boards to generate work, I split the research into three areas the physical computing tool covers, considering digital simulations, user communities and open-source hardware.
3D model of my Arduino board on sketchfab
I used the platform Trnio and Sketchfab to create 3D models of the separate components of the Arduino board.
Experimenting with the AR headset function to present the model with a net Arduino board model.
I collected all UV mapping examples of the Arduino board and compiled together to create several ‘digital skins’.

CLASSIFICATION, BEAUTIFIED – MACHINE LEARNING

Classification through machine learning

‘CLASSIFICATION, BEAUTIFIED TEXTURE, MACHINE LEARNING, NET’ : This experiment explores the commercial use of AI Generator technology, using the ‘Beautified’ filter to create UV edits on blender, to expand and manipulate the AI models. Through this process, I began building a classification image system, using the AI faces as inputs to build a classification system through machine learning. Coding a classifier, enabled the use of ‘AI BEAUTIFIED FACES’ as inputs using model predictions, list index sort predictions and range classification to create a visual outcome; combining the audio (listing the unique numerical values of each 15 model) with the ‘classified’ outcome of the initial input.

Skin Classification – Building a skin texture algorithm

Classification models selected to create a classification image algorithm through machine learning.
Classification— skin texture outcome: Exploring the use of AI generated images in machine learning, building an algorithm to use skin textures as input to train a classifying model.
Training model:
https://colab.research.google.com/drive/1PS_juuZrqlumZPciFfuXet4KCP6_UlS6#scrollTo=6WEvc3vEWqS4&uniqifier=2