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公开(公告)号：US11580718B2
公开(公告)日：2023-02-14
申请号：US16995618
申请日：2020-08-17
Applicant: Blue River Technology Inc.
Inventor： Christopher Grant Padwick , William Louis Patzoldt , Benjamin Kahn Cline , Olgert Denas , Sonali Subhash Tanna
Abstract: A farming machine moves through a field and includes an image sensor that captures an image of a plant in the field. A control system accesses the captured image and applies the image to a machine learned plant identification model. The plant identification model identifies pixels representing the plant and categorizes the plant into a plant group (e.g., plant species). The identified pixels are labeled as the plant group and a location of the pixels is determined. The control system actuates a treatment mechanism based on the identified plant group and location. Additionally, the images from the image sensor and the plant identification model may be used to generate a plant identification map. The plant identification map is a map of the field that indicates the locations of the plant groups identified by the plant identification model.
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公开(公告)号：US20250000015A1
公开(公告)日：2025-01-02
申请号：US18217296
申请日：2023-06-30
Applicant: Blue River Technology Inc.
Inventor： Benjamin Kahn Cline , Christopher Grant Padwick , Chia-Chun Fu , Olgert Denas
Abstract: A method for calibrating performance characteristics of a farming machine using a performance report is described. The farming machine accesses images of plants in a field captured during the calibration pass. The images are input into a performance model to generate a performance report by identifying plants in the images using a plurality of identification sensitivities and determining expected performance characteristics of the farming machine for each of the identification sensitivities. As such, the performance report includes expected performance characteristics for each identification sensitives. The farming machine accesses a target performance characteristic (e.g., from an operator) for the farming machine corresponding identification sensitivity. Images are input into a plant identification model during a treatment pass which identify a plant in the field using the identification sensitivity corresponding to the target performance characteristic. The farming machine treats the plant in the field using a treatment array of the farming machine.
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3.发明授权公开(公告)号：US11514671B2
公开(公告)日：2022-11-29
申请号：US16893405
申请日：2020-06-04
Applicant: Blue River Technology Inc.
Inventor： Andrei Polzounov , James Patrick Ostrowski , Lee Kamp Redden , Olgert Denas , Chia-Chun Fu , Chris Padwick
Abstract: A farming machine including a number of treatment mechanisms treats plants according to a treatment plan as the farming machine moves through the field. The control system of the farming machine executes a plant identification model configured to identify plants in the field for treatment. The control system generates a treatment map identifying which treatment mechanisms to actuate to treat the plants in the field. To generate a treatment map, the farming machine captures an image of plants, processes the image to identify plants, and generates a treatment map. The plant identification model can be a convolutional neural network having an input layer, an identification layer, and an output layer. The input layer has the dimensionality of the image, the identification layer has a greatly reduced dimensionality, and the output layer has the dimensionality of the treatment mechanisms.
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公开(公告)号：US20250000010A1
公开(公告)日：2025-01-02
申请号：US18217294
申请日：2023-06-30
Applicant: Blue River Technology Inc.
Inventor： Benjamin Kahn Cline , Christopher Grant Padwick , Chia-Chun Fu , Olgert Denas
Abstract: A method for calibrating characteristics of a farming machine as it travels through a field treating plants is presented. Images captured by the farming machine are input into a performance model which identifies plants in the images using an original identification sensitivity and determines expected performance characteristics of the farming machine. The performance model accesses a target performance characteristic for the farming machine and determines a modified identification sensitivity for the performance model that achieves the target performance characteristic. The farming machine inputs additional images captured by the farming machine into the performance model. The performance model identifies a plant using the modified identification sensitivity, and the farming machine treats the plant in the field.
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公开(公告)号：US11823388B2
公开(公告)日：2023-11-21
申请号：US18094927
申请日：2023-01-09
Applicant: Blue River Technology Inc.
Inventor： Christopher Grant Padwick , William Louis Patzoldt , Benjamin Kahn Cline , Olgert Denas , Sonali Subhash Tanna
IPC: G06T7/11 , G06T7/73 , G06V10/82 , G06V20/10 , G06V20/00 , G06V10/75 , G06V10/44 , G06V10/20 , G06T7/66 , G06V20/68
CPC classification number: G06T7/11 , G06T7/66 , G06T7/73 , G06V10/255 , G06V10/44 , G06V10/751 , G06V10/82 , G06V20/188 , G06V20/38 , G06T2207/20164 , G06T2207/30128 , G06T2207/30188 , G06T2207/30252 , G06V20/68
Abstract: A farming machine moves through a field and includes an image sensor that captures an image of a plant in the field. A control system accesses the captured image and applies the image to a machine learned plant identification model. The plant identification model identifies pixels representing the plant and categorizes the plant into a plant group (e.g., plant species). The identified pixels are labeled as the plant group and a location of the pixels is determined. The control system actuates a treatment mechanism based on the identified plant group and location. Additionally, the images from the image sensor and the plant identification model may be used to generate a plant identification map. The plant identification map is a map of the field that indicates the locations of the plant groups identified by the plant identification model.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20230076562A1
公开(公告)日：2023-03-09
申请号：US17985766
申请日：2022-11-11
Applicant: Blue River Technology Inc.
Inventor： Andrei Polzounov , James Patrick Ostrowski , Lee Kamp Redden , Olgert Denas , Chia-Chun Fu , Chris Padwick
Abstract: A farming machine including a number of treatment mechanisms treats plants according to a treatment plan as the farming machine moves through the field. The control system of the farming machine executes a plant identification model configured to identify plants in the field for treatment. The control system generates a treatment map identifying which treatment mechanisms to actuate to treat the plants in the field. To generate a treatment map, the farming machine captures an image of plants, processes the image to identify plants, and generates a treatment map. The plant identification model can be a convolutional neural network having an input layer, an identification layer, and an output layer. The input layer has the dimensionality of the image, the identification layer has a greatly reduced dimensionality, and the output layer has the dimensionality of the treatment mechanisms.
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公开(公告)号：US20240046479A1
公开(公告)日：2024-02-08
申请号：US18487252
申请日：2023-10-16
Applicant: Blue River Technology Inc.
Inventor： Christopher Grant Padwick , William Louis Patzoldt , Benjamin Kahn Cline , Olgert Denas , Sonali Subhash Tanna
IPC: G06T7/11 , G06T7/66 , G06T7/73 , G06V10/82 , G06V20/10 , G06V20/00 , G06V10/75 , G06V10/44 , G06V10/20
CPC classification number: G06T7/11 , G06T7/66 , G06T7/73 , G06V10/82 , G06V20/188 , G06V20/38 , G06V10/751 , G06V10/44 , G06V10/255 , G06T2207/30252 , G06T2207/20164 , G06T2207/30128 , G06T2207/30188 , G06V20/68
Abstract: A farming machine moves through a field and includes an image sensor that captures an image of a plant in the field. A control system accesses the captured image and applies the image to a machine learned plant identification model. The plant identification model identifies pixels representing the plant and categorizes the plant into a plant group (e.g., plant species). The identified pixels are labeled as the plant group and a location of the pixels is determined. The control system actuates a treatment mechanism based on the identified plant group and location. Additionally, the images from the image sensor and the plant identification model may be used to generate a plant identification map. The plant identification map is a map of the field that indicates the locations of the plant groups identified by the plant identification model.
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公开(公告)号：US20210056338A1
公开(公告)日：2021-02-25
申请号：US16995618
申请日：2020-08-17
Applicant: Blue River Technology Inc.
Inventor： Christopher Grant Padwick , William Louis Patzoldt , Benjamin Kahn Cline , Olgert Denas , Sonali Subhash Tanna
Abstract: A farming machine moves through a field and includes an image sensor that captures an image of a plant in the field. A control system accesses the captured image and applies the image to a machine learned plant identification model. The plant identification model identifies pixels representing the plant and categorizes the plant into a plant group (e.g., plant species). The identified pixels are labeled as the plant group and a location of the pixels is determined. The control system actuates a treatment mechanism based on the identified plant group and location. Additionally, the images from the image sensor and the plant identification model may be used to generate a plant identification map. The plant identification map is a map of the field that indicates the locations of the plant groups identified by the plant identification model.
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9.发明申请公开(公告)号：US20200302170A1
公开(公告)日：2020-09-24
申请号：US16893405
申请日：2020-06-04
Applicant: Blue River Technology Inc.
Inventor： Andrei Polzounov , James Patrick Ostrowski , Lee Kamp Redden , Olgert Denas , Chia-Chun Fu , Chris Padwick
Abstract: A farming machine including a number of treatment mechanisms treats plants according to a treatment plan as the farming machine moves through the field. The control system of the farming machine executes a plant identification model configured to identify plants in the field for treatment. The control system generates a treatment map identifying which treatment mechanisms to actuate to treat the plants in the field. To generate a treatment map, the farming machine captures an image of plants, processes the image to identify plants, and generates a treatment map. The plant identification model can be a convolutional neural network having an input layer, an identification layer, and an output layer. The input layer has the dimensionality of the image, the identification layer has a greatly reduced dimensionality, and the output layer has the dimensionality of the treatment mechanisms.
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公开(公告)号：US20230177697A1
公开(公告)日：2023-06-08
申请号：US18094927
申请日：2023-01-09
Applicant: Blue River Technology Inc.
Inventor： Christopher Grant Padwick , William Louis Patzoldt , Benjamin Kahn Cline , Olgert Denas , Sonali Subhash Tanna
IPC: G06T7/11 , G06T7/66 , G06T7/73 , G06V10/82 , G06V20/10 , G06V20/00 , G06V10/75 , G06V10/44 , G06V10/20
CPC classification number: G06T7/11 , G06T7/66 , G06T7/73 , G06V10/82 , G06V20/188 , G06V20/38 , G06V10/751 , G06V10/44 , G06V10/255 , G06T2207/30252 , G06T2207/20164 , G06T2207/30128 , G06T2207/30188 , G06V20/68
Abstract: A farming machine moves through a field and includes an image sensor that captures an image of a plant in the field. A control system accesses the captured image and applies the image to a machine learned plant identification model. The plant identification model identifies pixels representing the plant and categorizes the plant into a plant group (e.g., plant species). The identified pixels are labeled as the plant group and a location of the pixels is determined. The control system actuates a treatment mechanism based on the identified plant group and location. Additionally, the images from the image sensor and the plant identification model may be used to generate a plant identification map. The plant identification map is a map of the field that indicates the locations of the plant groups identified by the plant identification model.
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