duality-robotics/YOLOv8-Multiclass-Object-Detection-Dataset
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Rebekah Bogdanoff PRO
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🗣️ Introducing the Duality AI + LunateAI Challenge- Geospatial Object Detection: Rural Buildings!
Train a model to detect difficult detection instances, such as a low number of pixels or weak feature responses, in rural aerial imagery, to win 🏆PRIZES🏆 and 🤩RECOGNITION🤩.
Sign up here: https://www.kaggle.com/competitions/duality-ai-lunate-ai-geospatial-object-detection/overview
This is the first competition in the 🌎Geospatial Kaggle Challenge Series🌏, which will explore how geospatial-based digital twins can train an AI model for real-world applications.
Duality is excited to be partnering with LunateAI, a high-end advisory business founded by the award-winning, industry-recognized global leader Dr. Nadine Alameh to usher in a new era of geospatial impact in conjunction with advances in computing and AI.
Lunate helps government and industry leaders 🤔 rethink, 💡redesign, and 📝 execute transformative geospatial strategies using AI, cloud, and Lunate’s unparalleled global expertise. Read more about the company here: https://lunateai.com/
🏠 For this Kaggle competition, competitors will train an object detection model to identify buildings in a rural environment, using aerial imagery. 🏠
The real-world testing data focuses on difficult detection instances, such as:
🔎 Low number of pixels
🏘️ Weak feature responses
🌤️Varied lighting
Competitors must generate varied synthetic data that addresses key difficulties of the real-world dataset using a FalconCloud simulation with controllable parameters.
Competitors can control:
✅ Variety of in-class of objects
✅ Lighting and shadow conditions
✅ Environmental occlusions
✅ and more!
Join the competition and learn how digital simulation using data such as geospatial information can help tackle difficult real-world challenges.
Sign up here: https://www.kaggle.com/competitions/duality-ai-lunate-ai-geospatial-object-detection/overview
reacted
to
their
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15 days ago
🗣️ Introducing the Duality AI + LunateAI Challenge- Geospatial Object Detection: Rural Buildings!
Train a model to detect difficult detection instances, such as a low number of pixels or weak feature responses, in rural aerial imagery, to win 🏆PRIZES🏆 and 🤩RECOGNITION🤩.
Sign up here: https://www.kaggle.com/competitions/duality-ai-lunate-ai-geospatial-object-detection/overview
This is the first competition in the 🌎Geospatial Kaggle Challenge Series🌏, which will explore how geospatial-based digital twins can train an AI model for real-world applications.
Duality is excited to be partnering with LunateAI, a high-end advisory business founded by the award-winning, industry-recognized global leader Dr. Nadine Alameh to usher in a new era of geospatial impact in conjunction with advances in computing and AI.
Lunate helps government and industry leaders 🤔 rethink, 💡redesign, and 📝 execute transformative geospatial strategies using AI, cloud, and Lunate’s unparalleled global expertise. Read more about the company here: https://lunateai.com/
🏠 For this Kaggle competition, competitors will train an object detection model to identify buildings in a rural environment, using aerial imagery. 🏠
The real-world testing data focuses on difficult detection instances, such as:
🔎 Low number of pixels
🏘️ Weak feature responses
🌤️Varied lighting
Competitors must generate varied synthetic data that addresses key difficulties of the real-world dataset using a FalconCloud simulation with controllable parameters.
Competitors can control:
✅ Variety of in-class of objects
✅ Lighting and shadow conditions
✅ Environmental occlusions
✅ and more!
Join the competition and learn how digital simulation using data such as geospatial information can help tackle difficult real-world challenges.
Sign up here: https://www.kaggle.com/competitions/duality-ai-lunate-ai-geospatial-object-detection/overview
reacted
to
their
post
with 👀
15 days ago
🗣️ Introducing the Duality AI + LunateAI Challenge- Geospatial Object Detection: Rural Buildings!
Train a model to detect difficult detection instances, such as a low number of pixels or weak feature responses, in rural aerial imagery, to win 🏆PRIZES🏆 and 🤩RECOGNITION🤩.
Sign up here: https://www.kaggle.com/competitions/duality-ai-lunate-ai-geospatial-object-detection/overview
This is the first competition in the 🌎Geospatial Kaggle Challenge Series🌏, which will explore how geospatial-based digital twins can train an AI model for real-world applications.
Duality is excited to be partnering with LunateAI, a high-end advisory business founded by the award-winning, industry-recognized global leader Dr. Nadine Alameh to usher in a new era of geospatial impact in conjunction with advances in computing and AI.
Lunate helps government and industry leaders 🤔 rethink, 💡redesign, and 📝 execute transformative geospatial strategies using AI, cloud, and Lunate’s unparalleled global expertise. Read more about the company here: https://lunateai.com/
🏠 For this Kaggle competition, competitors will train an object detection model to identify buildings in a rural environment, using aerial imagery. 🏠
The real-world testing data focuses on difficult detection instances, such as:
🔎 Low number of pixels
🏘️ Weak feature responses
🌤️Varied lighting
Competitors must generate varied synthetic data that addresses key difficulties of the real-world dataset using a FalconCloud simulation with controllable parameters.
Competitors can control:
✅ Variety of in-class of objects
✅ Lighting and shadow conditions
✅ Environmental occlusions
✅ and more!
Join the competition and learn how digital simulation using data such as geospatial information can help tackle difficult real-world challenges.
Sign up here: https://www.kaggle.com/competitions/duality-ai-lunate-ai-geospatial-object-detection/overview
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