Predicting horticultural yield for a field location using multi-band aerial imagery
AssigneeClimate LLC
InventorsTaylor Aune, Keely Roth
Life of this patent
Estimating the term…
Abstract
Embodiments of the disclosed technologies are capable of inputting, to a machine-learned classifier that has been created using a set of neural network-based models, multi-band digital image data that represents an aerial view of an agricultural field location containing an horticultural product; outputting, by the classifier, annotated image data, the annotated image data comprising annotation data indicative of individual instances of the horticultural product in the agricultural field location; using the annotated image data, computing a first predicted yield for the agricultural field location; adjusting the first predicted yield by a scaling factor to produce a second predicted yield for the agricultural field location.
Claims20
A computer-implemented method comprising:
- inputting, to a machine-learned classifier that has been created using a set of neural network-based models, multi-band digital image data that represents an aerial view of an agricultural field location containing a horticultural product, each neural network-based model of the set of neural network-based models comprising a plurality of layers, each layer of the plurality of layers comprising a plurality of nodes and a plurality of weights associated with the plurality of nodes;
- outputting, by the classifier, annotated image data, the annotated image data comprising annotation data identifying individual instances of the horticultural product in the agricultural field location;
- using the annotated image data, computing a first predicted yield for the agricultural field location.
A system comprising:
- one or more processors;
- a memory storing instructions which, when executed by the one or more processors, cause performance of:
- inputting, to a machine-learned classifier that has been created using a set of neural network-based models, multi-band digital image data that represents an aerial view of an agricultural field location containing a horticultural product, each neural network-based model of the set of neural network-based models comprising a plurality of layers, each layer of the plurality of layers comprising a plurality of nodes and a plurality of weights associated with the plurality of nodes;
- outputting, by the classifier, annotated image data, the annotated image data comprising annotation data identifying individual instances of the horticultural product in the agricultural field location;
- using the annotated image data, computing a first predicted yield for the agricultural field location.
One or more non-transitory computer-readable media storing instructions which, when executed, cause performance of:
- inputting, to a machine-learned classifier that has been created using a set of neural network-based models, multi-band digital image data that represents an aerial view of an agricultural field location containing a horticultural product, each neural network-based model of the set of neural network-based models comprising a plurality of layers, each layer of the plurality of layers comprising a plurality of nodes and a plurality of weights associated with the plurality of nodes;
- outputting, by the classifier, annotated image data, the annotated image data comprising annotation data identifying individual instances of the horticultural product in the agricultural field location;
- using the annotated image data, computing a first predicted yield for the agricultural field location.
Dependencies are inferred from the claim text.