Predicting horticultural yield for a field location using multi-band aerial imagery

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; ou...

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Bibliographic Details
Main Authors ROTH, Keely, AUNE, Taylor
Format Patent
LanguageEnglish
Published 09.02.2023
Subjects
AGRICULTURE
ANIMAL HUSBANDRY
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
FISHING
FORESTRY
GYROSCOPIC INSTRUMENTS
HUMAN NECESSITIES
HUNTING
MEASURING
MEASURING DISTANCES, LEVELS OR BEARINGS
NAVIGATION
PARTS, DETAILS, OR ACCESSORIES OF AGRICULTURAL MACHINES ORIMPLEMENTS, IN GENERAL
PHOTOGRAMMETRY OR VIDEOGRAMMETRY
PHYSICS
SOIL WORKING IN AGRICULTURE OR FORESTRY
SURVEYING
TESTING
TRAPPING
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Summary: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.
Bibliography:Application Number: AU20210307942