Patents by Inventor Dustin James Webb
Dustin James Webb has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11937524Abstract: A method includes obtaining, by the treatment system configured to implement a machine learning (ML) algorithm, one or more images of a region of an agricultural environment near the treatment system, wherein the one or more images are captured from the region of a real-world where agricultural target objects are expected to be present, determining one or more parameters for use with the ML algorithm, wherein at least one of the one or more parameters is based on one or more ML models related to identification of an agricultural object, determining a real-world target in the one or more images using the ML algorithm, wherein the ML algorithm is at least partly implemented using the one or more processors of the treatment system, and applying a treatment to the target by selectively activating the treatment mechanism based on a result of the determining the target.Type: GrantFiled: September 15, 2022Date of Patent: March 26, 2024Assignee: Verdant Robotics, Inc.Inventors: Gabriel Thurston Sibley, Lorenzo Ibarria, Curtis Dale Garner, Patrick Christopher Leger, Dustin James Webb
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Publication number: 20240057502Abstract: A method implemented by a treatment system disposed on a vehicle, the treatment system having one or more processors, a storage, and a treatment mechanism, includes capturing a first image of a region of an agricultural environment, detecting, by implementing a first machine learning (ML) algorithm on a first portion of the first image, a presence of at least a portion of a first object in the first image, determining whether the first object detected is a treatment candidate, determining, upon determining that the first object is a treatment candidate, a first three dimensional (3D) location of at least a portion of the first object in the agricultural environment, and applying, a treatment to at least the portion of the first object by activating the treatment mechanism to interact with the first object.Type: ApplicationFiled: October 16, 2023Publication date: February 22, 2024Inventors: Gabriel Thurston Sibley, Lorenzo Ibarria, Curtis Dale Garner, Patrick Christopher Leger, Dustin James Webb
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Patent number: 11785873Abstract: A method includes obtaining, by the treatment system configured to implement a machine learning (ML) algorithm, one or more images of a region of an agricultural environment near the treatment system, wherein the one or more images are captured from the region of a real-world where agricultural target objects are expected to be present, determining one or more parameters for use with the ML algorithm, wherein at least one of the one or more parameters is based on one or more ML models related to identification of an agricultural object, determining a real-world target in the one or more images using the ML algorithm, wherein the ML algorithm is at least partly implemented using the one or more processors of the treatment system, and applying a treatment to the target by selectively activating the treatment mechanism based on a result of the determining the target.Type: GrantFiled: August 29, 2022Date of Patent: October 17, 2023Assignee: VERDANT ROBOTICS, INC.Inventors: Gabriel Thurston Sibley, Lorenzo Ibarria, Curtis Dale Garner, Patrick Christopher Leger, Dustin James Webb
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Publication number: 20230252791Abstract: A computer-implemented method of sensor input processing, implemented by an agricultural platform comprising a processor and a sensor, includes capturing, using the sensor, sensor images of a vicinity of a target object of a time interval during which a treatment is applied to the target object; processing the sensor images using one or more machine learning (ML) algorithms wherein at least one ML algorithm uses an ML model trained to detect a presence of a treatment action in the vicinity of the target object; and providing, selectively based on a result of detecting the presence of the treatment action in the vicinity of the target object, an outcome of the processing for further processing.Type: ApplicationFiled: March 31, 2023Publication date: August 10, 2023Inventors: Dustin James Webb, Patrick Christopher Leger, Gabriel Thurston Sibley, Lorenzo Ibarria, Curtis Dale Garner
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Publication number: 20230252789Abstract: A computer-implemented method of sensor input processing, implemented by an agricultural platform comprising a processor and a sensor, includes capturing, using the sensor, sensor images of a vicinity of a target object of a time interval during which a treatment is applied to the target object; processing the sensor images using one or more machine learning (ML) algorithms wherein at least one ML algorithm uses an ML model trained to detect a presence of a treatment action in the vicinity of the target object; and providing, selectively based on a result of detecting the presence of the treatment action in the vicinity of the target object, an outcome of the processing for further processing.Type: ApplicationFiled: February 6, 2023Publication date: August 10, 2023Inventors: Gabriel Thurston Sibley, Lorenzo Ibarria, Curtis Dale Garner, Patrick Christopher Leger, Dustin James Webb
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Publication number: 20230247928Abstract: A computer-implemented method includes performing, using a processor onboard a vehicle, a machine learning (ML) processing on sensor input from sensors onboard an agricultural vehicle, identifying, according to a rule, a subset of data resulting from the ML processing and generating and displaying, in real-time, the subset of data to a user interface, thereby enabling a user interaction with the subset of data.Type: ApplicationFiled: February 6, 2023Publication date: August 10, 2023Inventors: Gabriel Thurston Sibley, Lorenzo Ibarria, Curtis Dale Garner, Patrick Christopher Leger, Dustin James Webb
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Publication number: 20230252773Abstract: A method of processing agricultural images includes comparing object detections performed by multiple image processing schemes to determine a set of ground truth images from which at least one machine learning (ML) models used by at least one ML algorithm included in the multiple image processing schemes is trained, wherein the multiple image processing schemes include two or more of (a) an image processing scheme that includes a cascade of multiple ML algorithms; (b) an image processing scheme that includes image annotation based on user feedback; or (c) an image processing scheme that includes a cascade of an ML algorithm or a computer vision (CV) algorithm and a user feedback.Type: ApplicationFiled: February 6, 2023Publication date: August 10, 2023Inventors: Patrick Christopher Leger, Dustin James Webb
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Publication number: 20230252318Abstract: A computer-implemented method of sensor input processing, implemented by an agricultural platform comprising a processor and a sensor includes receiving sensor input from the sensor; processing the sensor input by multiple machine learning (ML) algorithms, each using a corresponding ML model for generating labels for objects identified in the sensor input; combining labels generated by each ML algorithm to generate a super-imposed labeled sensor input frame; comparing outputs of the ML algorithms to determine similarities or differences; and using results of the comparing for improving an operational characteristic of the sensor input processing.Type: ApplicationFiled: February 6, 2023Publication date: August 10, 2023Inventor: Dustin James Webb
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Publication number: 20230011505Abstract: A method includes obtaining, by the treatment system configured to implement a machine learning (ML) algorithm, one or more images of a region of an agricultural environment near the treatment system, wherein the one or more images are captured from the region of a real-world where agricultural target objects are expected to be present, determining one or more parameters for use with the ML algorithm, wherein at least one of the one or more parameters is based on one or more ML models related to identification of an agricultural object, determining a real-world target in the one or more images using the ML algorithm, wherein the ML algorithm is at least partly implemented using the one or more processors of the treatment system, and applying a treatment to the target by selectively activating the treatment mechanism based on a result of the determining the target.Type: ApplicationFiled: September 15, 2022Publication date: January 12, 2023Inventors: Gabriel Thurston Sibley, Lorenzo Ibarria, Curtis Dale Garner, Patrick Christopher Leger, Dustin James Webb
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Publication number: 20220400596Abstract: A method includes obtaining, by the treatment system configured to implement a machine learning (ML) algorithm, one or more images of a region of an agricultural environment near the treatment system, wherein the one or more images are captured from the region of a real-world where agricultural target objects are expected to be present, determining one or more parameters for use with the ML algorithm, wherein at least one of the one or more parameters is based on one or more ML models related to identification of an agricultural object, determining a real-world target in the one or more images using the ML algorithm, wherein the ML algorithm is at least partly implemented using the one or more processors of the treatment system, and applying a treatment to the target by selectively activating the treatment mechanism based on a result of the determining the target.Type: ApplicationFiled: August 29, 2022Publication date: December 22, 2022Inventors: Gabriel Thurston Sibley, Lorenzo Ibarria, Curtis Dale Garner, Patrick Christopher Leger, Dustin James Webb
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Patent number: 11425852Abstract: A method includes obtaining, by the treatment system configured to implement a machine learning (ML) algorithm, one or more images of a region of an agricultural environment near the treatment system, wherein the one or more images are captured from the region of a real-world where agricultural target objects are expected to be present, determining one or more parameters for use with the ML algorithm, wherein at least one of the one or more parameters is based on one or more ML models related to identification of an agricultural object, determining a real-world target in the one or more images using the ML algorithm, wherein the ML algorithm is at least partly implemented using the one or more processors of the treatment system, and applying a treatment to the target by selectively activating the treatment mechanism based on a result of the determining the target.Type: GrantFiled: October 20, 2021Date of Patent: August 30, 2022Assignee: VERDANT ROBOTICS, INC.Inventors: Gabriel Thurston Sibley, Lorenzo Ibarria, Curtis Dale Garner, Patrick Christopher Leger, Dustin James Webb
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Publication number: 20220183208Abstract: A method includes obtaining, by the treatment system configured to implement a machine learning (ML) algorithm, one or more images of a region of an agricultural environment near the treatment system, wherein the one or more images are captured from the region of a real-world where agricultural target objects are expected to be present, determining one or more parameters for use with the ML algorithm, wherein at least one of the one or more parameters is based on one or more ML models related to identification of an agricultural object, determining a real-world target in the one or more images using the ML algorithm, wherein the ML algorithm is at least partly implemented using the one or more processors of the treatment system, and applying a treatment to the target by selectively activating the treatment mechanism based on a result of the determining the target.Type: ApplicationFiled: October 20, 2021Publication date: June 16, 2022Inventors: Gabriel Thurston Sibley, Lorenzo Ibarria, Curtis Dale Garner, Patrick Christopher Leger, Dustin James Webb