Imaging Lunch: A Practical Introduction to Machine Learning for Vision Applications
Event details
| Date | 29.04.2026 |
| Hour | 11:00 › 13:00 |
| Speaker | Mallory Witwer |
| Location | |
| Category | Conferences - Seminars |
| Event Language | English |
Registration
Abstract
This workshop is designed for EPFL researchers interested in building effective, automated computer vision systems for scientific applications. During the workshop, we will review and explain the main steps of a machine learning-based computer vision project, from problem definition to image acquisition, annotation, training, validation, and inference. We will illustrate these steps in a practical way, by building a real computer vision application together until we can run it live on a camera. Along the way, we will discuss important concepts (data drift, overfitting, data augmentation) and observe how they manifest themselves in practice. We will also share tips and tricks to help you tackle your own computer vision challenges.
Prerequisites:
Basic familiarity with Python, image analysis, and machine learning concepts is desirable, but not strictly necessary.
Level:
Beginner / Intermediate
Abstract
This workshop is designed for EPFL researchers interested in building effective, automated computer vision systems for scientific applications. During the workshop, we will review and explain the main steps of a machine learning-based computer vision project, from problem definition to image acquisition, annotation, training, validation, and inference. We will illustrate these steps in a practical way, by building a real computer vision application together until we can run it live on a camera. Along the way, we will discuss important concepts (data drift, overfitting, data augmentation) and observe how they manifest themselves in practice. We will also share tips and tricks to help you tackle your own computer vision challenges.
Prerequisites:
Basic familiarity with Python, image analysis, and machine learning concepts is desirable, but not strictly necessary.
Level:
Beginner / Intermediate
Links
Practical information
- General public
- Registration required