REGINNA 4.0 First Summer School: Deep Tech training with impact on entrepreneurship and innovation

Computer Vision and Machine Learning in Industry 4.0: Use case

4 Jul 2023, 10:45

1h 30m

MIC, Medpodjetniški izobraževalni center

Industry 4.0

Speakers

Fidalgo Fernández (University of Leon) Laura Fernández Robles (Universidad de León)

Description

In this course we will cover the basic concepts of Neural Networks and Convolutional Neural Networks with an application to the classification of inserts of a milling machine according to their wear level.

Objectives

1. Know the concept of convolution and its applications in image processing.
2. Identify the building blocks of a Neural Network and a Convolutional Neural Network.
3. Learn to use pretrained CNNs to get descriptors to classify the level of wear of milling inserts
   3.1. Get started with non-handcrafted descriptors
   3.2. Application to Industry 4.0 problem

Outcomes

1. To know the basics about image convolution
2. To learn what a -neural Network is and its main concepts (neuron, layer, etc.).
3. To define the working of a Convolutional Neural Network and its basic building blocks
4. To classify inserts as having high or low wear using features extracted using pre-trained CNNs

Presentation Materials

Automatic_classification_of_inserts_using_image_classification_with_CNN_SOLUTION.ipynb

REGINNA-4.0_Computer_Vision_Machine_Learning_Industry_4.0_With_Videos.pdf

Video