| CPC G06T 11/001 (2013.01) [G06T 7/60 (2013.01); G06T 7/90 (2017.01); G06T 2207/10024 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30188 (2013.01)] | 12 Claims |
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1. A method implemented using one or more processors, the method comprising:
obtaining a monochrome X-ray image that depicts a plant, wherein a canopy of the plant at least partially occludes one or more plant-parts-of-interest from a vantage point at which an X-ray sensor captured the monochrome X-ray image, and wherein the one or more plant-parts-of-interest are visible through the canopy in the monochrome X-ray image;
obtaining environmental data of an agricultural area where the plant is grown, wherein the environmental data is obtained using one or more of a moisture sensor, a laser, a barometer, a photodiode, or a thermometer;
obtaining time-series data corresponding to the environmental data of the agricultural area where the plant is grown;
executing a machine learning model to generate a Red Green Blue (RGB) version of the X-ray image, wherein the monochrome X-ray image, the environmental data of the agricultural area where the plant is grown, and the time-series data are inputs to the machine learning model; and
predicting one or more phenotypic traits of the one or more plant-parts-of-interest based on one or more visual features of the RGB version of the X-ray image.
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