The goal of the challenge is to develop a machine learning model to identify and detect “damaged” and “un-damaged” coastal infrastructure (residential and commercial buildings), which have been impacted by natural calamities such as hurricanes, cyclones, etc. Participants will be given pre- and post-cyclone satellite images of a site impacted by Hurricane Maria in 2017 and build a machine learning model, designed to detect four different objects in a satellite image of a cyclone impacted area:
- Undamaged residential building
- Damaged residential building
- Undamaged commercial building
- Damaged commercial building
- We are among the Top 10 Global Semi-Finalist of EY Open Science Data Challenge 2024 🎉🥳
- We ranked 8th globally out of a total of 11,000 registrants 🌍🏆
- Meanwhile, we ranked 1st out of 22 teams in Malaysia! 🏅