Wildfire Intelligence
Jan 1, 2023
·
1 min read
Wildfire intelligence work connects perception models with constrained deployment settings where compute, bandwidth, and response time matter.
- Developed a generative wildfire-spread model using conditional variational autoencoders
- Designed supervised image-compression models that reduced inputs to 4.8 KB while preserving 72.9% wildfire-detection accuracy
- Built an edge-computing framework for distributed wildfire detection using early-exit neural networks
- Integrated wildfire perception work with broader digital twin and disaster-resilience systems
