Training school programme
The programme is organised by topics and dataset types. Each topic builds on the previous one, guiding participants from foundational skills to advanced applications of computer vision in archaeology.
Programme
Monday
Kick-off & Python for CV
Morning
- Kick-off, practicalities, and motivations
- Introduction to the workshop structure
- Introduction co computer vision and questions computer vision can answer
- Setting up the technical environment (Google Colab and tools)
Afternoon
- Coding with agents
- Python fundamentals for computer vision
Evening
- Ice-breaker
Tuesday
Artefacts Dataset
Morning
- Image datasets and annotation – theory
- Datasets, licensing, controlled vocabularies, and annotation challenges
Afternoon
- Practical part: annotating a dataset
Wednesday
Microscopy Dataset
Morning
- Data standardization (brightness, contrast, size, RGB/grayscale) and image pre-processing
- Data pre-processing and augmentation
- OpenCV: detection masks and data augmentation
Afternoon
- Practical part: data standardization and augmentation
Thursday
Satellite Imagery
Morning
- Satellite imagery and remote sensing in theory
- Object detection on satellite images
Afternoon
- Practical part: satellite imagery analysis
Friday
Coins Dataset & Closing
Morning
- Advanced topics illustrated on coins dataset and combining methods
- LLMs and vision-language models
- Bias, reproducibility, black-box models, attention maps, and causation–correlation problems
Afternoon
- Closing and discussion
Case Studies
Throughout the school, participants will work with four real-world archaeological datasets:
- Artefact types: classification and detection of archaeological artefacts from photographs
- Microscopic use-wear analysis: identifying and classifying wear traces from microscopic images
- Satellite imagery: remote sensing and object detection on satellite data
- Coins: combining techniques on photographs and drawings of coins and exploring model interpretability
Keynote
Will be specified…
Social Events