Abstract: Implementations are described herein for analyzing vision data depicting undesirable plants such as weeds to detect various attribute(s). The detected attribute(s) of a particular undesirable plant may then be used to select, from a plurality of available candidate remediation techniques, the most suitable remediation technique to eradicate or otherwise eliminate the undesirable plants.

Abstract: Implementations are described herein for utilizing various image processing techniques to facilitate tracking and/or counting of plant-parts-of-interest among crops. In various implementations, a sequence of digital images of a plant captured by a vision sensor while the vision sensor is moved relative to the plant may be obtained. A first digital image and a second digital image of the sequence may be analyzed to determine one or more constituent similarity scores between plant-parts-of-interest across the first and second digital images. The constituent similarity scores may be used, e.g., collectively as a composite similarity score, to determine whether a depiction of a plant-part-of-interest in the first digital images matches a depiction of a plant-part-of-interest in the second digital image.

Abstract: Implementations are described herein for analyzing vision data depicting undesirable plants such as weeds to detect various attribute(s). The detected attribute(s) of a particular undesirable plant may then be used to select, from a plurality of available candidate remediation techniques, the most suitable remediation technique to eradicate or otherwise eliminate the undesirable plants.

Abstract: Implementations are described herein for utilizing various image processing techniques to facilitate tracking and/or counting of plant-parts-of-interest among crops. In various implementations, a sequence of digital images of a plant captured by a vision sensor while the vision sensor is moved relative to the plant may be obtained. A first digital image and a second digital image of the sequence may be analyzed to determine one or more constituent similarity scores between plant-parts-of-interest across the first and second digital images. The constituent similarity scores may be used, e.g., collectively as a composite similarity score, to determine whether a depiction of a plant-part-of-interest in the first digital images matches a depiction of a plant-part-of-interest in the second digital image.