Deere & Company

Shuhao Fu

Yueqi Li

Alexander Ngai

Implementations are described herein for learning mappings between a domain specific language (DSL) and images, and leveraging those mappings for various purposes. In various implementations, a method for using a DSL to generate training data may include processing data indicative of ground truth image(s) depicting a real plant using a trained image-to-DSL machine learning (ML) model to generate a first expression in the DSL that describes structure of the real plant. The first expression may include a plurality of parameters, and may be processed to programmatically generate a plurality of synthetic DSL expressions. Each respective synthetic DSL expression may describe structure of a respective synthetic plant for which parameter(s) have been altered from the first expression. The synthetic DSL expressions may be processed using a renderer to create three-dimensional (3D) synthetic plant models. Two-dimensional (2D) synthetic images may be generated that depict the 3D synthetic plant models in an area.

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San Jose, CA, United States of America

Shuhao Fu