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:

1. Undamaged residential building
2. Damaged residential building
3. Undamaged commercial building
4. Damaged commercial building

• We are among the Top 10 Global Semi-Finalist of EY Open Science Data Challenge 2024 🎉🥳
  
• We ranked 11 out of 222 teams worldwide on the leaderboard (Top 5%) 🌍🏆
  
• In terms of evaluation score, we rank 4th, tying with other impressive competing teams! 🤩
• Meanwhile, we ranked 1st out of 22 teams in Malaysia! 🏅