Spot weed detection and treatment within a field of view in accordance with machine learning training

A method for carrying out spot-based weed spraying based upon a classification value rendered from a sub-field image in accordance with a machine learning-based trained model applied by a processor to the sub-field image, the method comprising:

• acquiring, by a camera, a full field of view image of a crop floor;
• extracting, from the full field of view image, a sub-field image corresponding to a spray nozzle positioned to provide a spray field extending over a part of the crop floor depicted in the sub-field image;
• rendering, by the processor in accordance with the machine learning-based trained model, a classification for the sub-field image;
• and
• selectively activating the spray nozzle in accordance with the classification for the sub-field image,
• wherein the sub-field image is a rectangle rendered from an initial trapezoid image sub-field captured by a forward-looking camera.

A weed spot-spraying system configured to carry out a spot-based weed spraying method based upon a classification value rendered from a sub-field image in accordance with a machine learning-based trained model applied by a processor to the sub-field image, comprising:

• a camera;
• a spray nozzle assembly including a spray nozzle;
• and
• a processor;
• wherein the spot-based weed spraying method comprises:
• acquiring, by the camera, a full field of view image of a crop floor;
• extracting, from the full field of view image, a sub-field image corresponding to the spray nozzle positioned to provide a spray field extending over a part of the crop floor depicted in the sub-field image;
• rendering, by the processor in accordance with the machine learning-based trained model, a classification for the sub-field image;
• and
• selectively activating the spray nozzle in accordance with the classification for the sub-field image,
• wherein the rendering is carried out by a neural network incorporated into the processor, and
• wherein the neural network has an array of inputs arranged in accordance with pixel dimensions of the sub-field image corresponding to a spray nozzle positioned to provide a spray field.

A weed spot-spraying system configured to carry out a spot-based weed spraying method based upon a classification value rendered from a sub-field image in accordance with a machine learning-based trained model applied by a processor to the sub-field image, comprising:

• a camera;
• a spray nozzle assembly including a spray nozzle;
• and
• a processor;
• wherein the spot-based weed spraying method comprises:
• acquiring, by the camera, a full field of view image of a crop floor;
• extracting, from the full field of view image, a sub-field image corresponding to the spray nozzle positioned to provide a spray field extending over a part of the crop floor depicted in the sub-field image;
• rendering, by the processor in accordance with the machine learning-based trained model, a classification for the sub-field image;
• and
• selectively activating the spray nozzle in accordance with the classification for the sub-field image,
• wherein the sub-field image is a rectangle rendered from an initial trapezoid image sub-field captured by a forward-looking camera.