Flukebook applies computer vision algorithms and deep learning to identify and track individual whales and dolphins across hundreds of thousands of photos. We help researchers collaborate with each other and citizen scientists contribute to the effort. A.I. scales and speeds research and conservation.
We train computer vision to find individual whales and dolphins in photos and identify the species.
When we know where each animal is, we can identify them individually using algorithms that make digital "fingerprints" for each animal, such as identifying them by their unique body coloration or fin edges. We replace hours of human labor with just a few minutes of computer vision, scanning for matches across tens of thousands of photos.
If we can quickly track individuals in a population, we can model size and migration to generate new insights and support rapid, data-driven conservation action.
We can identify individuals of these species using fully automated computer vision:
Megaptera novaengliae (humpback whales) can be identified by the contrasting color and the trailing edge of their flukes using three algorithms: PIE, Kaggle 7, HotSpotter, CurvRank, and OC/WDTW. Learn more.
Physeter macrocephalus (sperm whales) can be identified by the trailing edge of their flukes using two algorithms: CurvRank and OC/WDTW. Learn more.
Eubalaena spp.(right whales) can be identified by the their heads, peduncles, flukes, and more using the PIE, HotSpotter and DeepSense.ai algorithms. Learn more.
Learn more about our machine learning research and engineering.
2M+ photos
282846 reported sightings
58322 identified whales and dolphins
"Sperm whales roam so vastly that no one research group can study them across their range. PhotoID as a tool for conservation and research finds power in numbers and international, inter-institutional collaboration. Flukebook enables us to do this easily."
- Shane Gero, The Dominica Sperm Whale Project