Learn to implement computer vision in smart factories using deep learning in this hands-on course. Gain skills to gather and label datasets, train and deploy models, and create interactive dashboards using Node-Red with MQTT for real-world applications in manufacturing.
The Computer Vision with Deep Learning for Smart Factory program is an intensive, hands-on training course designed for professionals aiming to integrate computer vision technology into industrial settings. This program covers all stages of computer vision project development, equipping participants with essential technical competencies:
Introduction to Deep Learning and Computer Vision: Understand the basics of deep learning, neural networks, and computer vision, including key concepts like image classification, object detection, and image segmentation.
Dataset Preparation: Learn to gather, label, and annotate datasets, critical steps for any successful computer vision project.
Model Training and Deployment: Gain hands-on experience in training deep learning models and deploying them for computer vision tasks using relevant software platforms.
Interactive Dashboard Development: Utilize Node-Red with MQTT to create custom dashboards, allowing real-time monitoring and control of computer vision applications for industrial use cases.
Engineers
Technicians
Technical Managers
Production Managers
Academia with relevant background.
None
5 Days
Participants are exposed to theoretical fundamentals and demonstrations of information technology related to smart factory competencies and processes, followed by hands-on activities to support application of competencies acquired.
Provide detailed definition of deep learning and describe the basic structure of neural network.
Provide detailed definition of computer vision and describe the differences between image classification, object detection and image segmentation tasks.
Perform the necessary methodologies for Computer Vision projects using Deep Learning
Utilize data labelling and annotation software to perform data annotation on various computer vision tasks.
Utilize the relevant software platform to train and deploy deep learning
model(s) for computer vision application(s).
Utilize Node-RED to develop interactive user interfaces to control and monitor the computer vision task and application(s).
