Machine Learning for Automated Strawberry Sorting

December 30, 2009

PITTSBURGH—Researchers at Carnegie Mellon University’s National Robotics Engineering Center (NREC) have developed a plant-sorting machine that uses computer vision and machine learning to inspect and grade harvested strawberry plants and then mechanically sort them by quality – tasks that until now could only be done manually.

In a successful field test this fall, the machine classified and sorted harvested plants more consistently and faster than workers could, with a comparable error rate.

Automated Strawberry Sorting by Machine Learning

David Larose and David Stager did the yeoman’s work developing the learning system with contributions from the lairlab team. The machine learning is based on the sub-gradient approach in:
(Online) Subgradient Methods for Structured Prediction

More details in the press here:

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