Life Sciences Commons^™

Identification And Classification Of Poultry Eggs: A Case Study Utilizing Computer Vision And Machine Learning, Jeremy Lubich, Kyle Thomas, Daniel W. Engels

SMU Data Science Review

We developed a method to identify, count, and classify chickens and eggs inside nesting boxes of a chicken coop. Utilizing an IoT AWS Deep Lens Camera for data capture and inferences, we trained and deployed a custom single-shot multibox (SSD) object detection and classification model. This allows us to monitor a complex environment with multiple chickens and eggs moving and appearing simultaneously within the video frames. The models can label video frames with classifications for 8 breeds of chickens and/or 4 colors of eggs, with 98% accuracy on chickens or eggs alone and 82.5% accuracy while detecting both types of …