TensorFlow Learns Cucumber Selection and Classification

What’s been criticized as Google marketing in threads on Hacker News and celebrated by others as an example of the increasing ubiquity of deep learning, neural networks and machine learning, Makoto Koike detailed how TensorFlow learned his farming-family’s discipline of cucumber selection and classification. The results were a greater success than he expected. Selection and classification is an often time-consuming process and can’t be taught quickly to temporary staff during peak harvest season, and often results in long hours where Koike’s family has to meticulously sort and classify cucumbers based on a number of attributes. Koike used 7,000 images of cucumbers classified by his family as the training data set over the course of three months. When he put the network to the test he used a Raspberry Pi to control imagery data…

Link to Full Article: TensorFlow Learns Cucumber Selection and Classification

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