https://www.eventbrite.com/e/frugal-ai-unsupervised-domain-adaptation-for-semantic-segmentation-tickets-690339051687?aff=oddtdtcreator

Machine Learning prerequisites
** : Good skills

Python prerequisites
** : Good skills

Technical prerequisites
Bring your own laptop

📅 Agenda:

08:30 AM – 09:00 AM: Delicious free breakfast & connection with Paris to discuss with french participants 🇫🇷

09:00 AM – 12:00 PM: Dive into datasets discovery and code exploration

12:00 PM – 01:00 PM: Enjoy a well-deserved lunch break

01:00 PM – 04:30 PM: Get your hands dirty with hands-on dataset work and code adaptation

04:30 PM – 05:30 PM: Engage in a group discussion and exchange on key takeaway messages

Algorithmic methods to be covered:                                                                                                                                                                                                       

Unsupervised Domain Adaptation for Semantic Segmentation using Few-shot Image-to-Image Translation via Latent Representation Mixing – San Francisco 🇺🇸

Dataset description:                                                                                                                                                                                                                                   

Participants will receive extracts from publicly available image segmentation datasets. These datasets are focused on satellite imagery of urban and suburban regions, although the techniques covered can be applied to various domains (medical imagery, self-driving car imagery).