Machine learning

One of the biggest challenges for pollinator ecology and conservation is identifying the subjects of our research. Bees, for example are highly diverse and often so similar even experts have trouble differentiating them. We are using leading edge techniques computer vision such as convolutional neural networks to detect and classify bees captured in images and video. We are working on developing models for automated species-level identification and deploying sensors for automated sampling and observation of plant-pollinator interactions.

An object detection algorithm tracks Bombus impatiens in the garden outside of my office.