When a Large LLM Doesn’t Work: Object Detection on 10-Meter Pixels [ukr]
When you give an LLM satellite imagery, object detection can look impressive on high-quality images — and completely fall apart when you switch to freely available satellite data, where the entire object may be just 20 pixels across. I’ll share our journey of detecting illegal landfills in Sentinel-2 imagery and explain why the path to a working solution wasn’t simply “get more data and throw a bigger model at it.” We started by moving away from LLMs and toward specialized object detectors, and eventually ended up with an architecture where each individual feature of an object is detected by a separate agent, while the final probability is calculated using explicit mathematical rules.
Yehor Litvinov
Senior Software Engineer at DataArt
- Senior software engineer with almost 20 years of experience in IT. Over the years, he has worked on software ranging from space mission control centers to dating and payment platforms
- Yehor has been with DataArt for more than 10 years, working mainly with PHP, JavaScript, and .NET.
- Alongside his work, Yehor is also pursuing a PhD at the Ukrainian State University of Science and Technologies, where he focuses on computer vision. More specifically, he is teaching machines to find all sorts of interesting and useful things in satellite imagery