Bringing AI into the Wild
summary
SAS combines deep learning and computer vision to turn a digital archive of footprint images into an automated system that identifies species and gender, cutting expert processing from about 20 minutes to seconds. The team integrates tribal trackers’ morphometric techniques with noninvasive camera data to map density and distribution, tackling object-detection challenges where footprints and background soil are the same. Project targets real-world conservation gaps—cheetah counts fell from ~100,000 historically to ~7,100 today.
AI-written summary · about
related talks
06mTransitioning AI from the lab to real-life applications
48mSetting the stage for AI for biodiversity
12mWill AI help save the snow leopard?
01h 20mSAS an open ecosystem for Artifical Intelligence
19mHow to Connect Data & AI with Dog Intelligence
27mSmart Forestry: AI in the Service of Nature
27mAI for social good
44mWildbook: Software and Machine Learning Engineers Join the Fight...