Neural networks learned to tell one bird from another, enabling scientists to study their behavior in greater detail.
What’s new: Researchers from universities in Europe and Africa trained neural networks to recognize individual birds with up to 90 percent accuracy, as detailed in Methods in Ecology and Evolution.
How it works: Researchers collected data by attaching radio-frequency identification tags to 35 of the African songbirds known as sociable weavers. Then they set up cameras to snap pictures, tagged with each creature’s identity, automatically whenever one entered a feeding area.
- The researchers used the Mask R-CNN instance segmentation network trained on the Coco image dataset, which includes pictures of birds, to locate and crop the birds in each picture.
- They pretrained a VGG19 convolutional neural network on ImageNet and fine-tuned it on 900 images of each bird (plus augmentations) to recognize the individuals based on distinctive patterns on their back and wing feathers.
- The researchers used a similar method to train models to spot individuals of two other species as well.
Behind the news: AI is increasingly useful for identifying individuals of various animal species, including chimpanzees, elephants, and pigs.
Why it matters: The researchers aimed to learn how sociable weavers cooperate to build large, communal nests. Catching, tagging, and observing animals in the wild takes a lot of time and effort. AI that automates the process can free up researchers to focus on extracting insights from the behavioral data they gather.
We’re thinking: Now birds are getting the face recognition tweetment!