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公开(公告)号：US11562486B2
公开(公告)日：2023-01-24
申请号：US17160928
申请日：2021-01-28
Applicant: X Development LLC
Inventor： Cheng-en Guo , Wilson Zhao , Jie Yang , Zhiqiang Yuan , Elliott Grant
IPC: G06T7/00 , G06V20/13 , A01D41/127 , G06T5/50 , G06T7/143 , G06N3/04 , G06N3/08 , G06Q10/04 , G06Q50/02 , G06V20/10
Abstract: Implementations relate to diagnosis of crop yield predictions and/or crop yields at the field- and pixel-level. In various implementations, a first temporal sequence of high-elevation digital images may be obtained that captures a geographic area over a given time interval through a crop cycle of a first type of crop. Ground truth operational data generated through the given time interval and that influences a final crop yield of the first geographic area after the crop cycle may also be obtained. Based on these data, a ground truth-based crop yield prediction may be generated for the first geographic area at the crop cycle's end. Recommended operational change(s) may be identified based on distinct hypothetical crop yield prediction(s) for the first geographic area. Each distinct hypothetical crop yield prediction may be generated based on hypothetical operational data that includes altered data point(s) of the ground truth operational data.
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公开(公告)号：US20220405962A1
公开(公告)日：2022-12-22
申请号：US17354147
申请日：2021-06-22
Applicant: X Development LLC
Inventor： Zhiqiang Yuan , Jie Yang
Abstract: Implementations are described herein for localizing individual plants using high-elevation images at multiple different resolutions. A first set of high-elevation images that capture the plurality of plants at a first resolution may be analyzed to classify a set of pixels as invariant anchor points. High-elevation images of the first set may be aligned with each other based on the invariant anchor points that are common among at least some of the first set of high-elevation images. A mapping may be generated between pixels of the aligned high-elevation images of the first set and spatially-corresponding pixels of a second set of higher-resolution high-elevation images. Based at least in part on the mapping, individual plant(s) of the plurality of plants may be localized within one or more of the second set of high-elevation images for performance of one or more agricultural tasks.
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公开(公告)号：US11367278B2
公开(公告)日：2022-06-21
申请号：US16817937
申请日：2020-03-13
Applicant: X Development LLC
Inventor： Alex Wilson , Christopher Edward Bacon , Jie Yang , Cheng-en Guo
Abstract: Implementations relate to improved crop field segmentation and crop classification in which boundaries between crop fields are more accurately detected. In various implementations, high-elevation image(s) that capture an area containing multiple demarcated fields may be applied as input across one or more machine learning models to generate a boundary enhancement channel. Each pixel of the boundary enhancement channel may be spatially aligned with a corresponding pixel of the one or more high-elevation images. Moreover, each pixel of the boundary enhancement channel may be classified with a unit angle to a reference location of the field of the multiple demarcated fields that contains the pixel. Based on the boundary enhancement channel, pixel-wise field memberships of pixels of the one or more high-elevation images in the multiple demarcated fields may be determined.
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公开(公告)号：US20210150209A1
公开(公告)日：2021-05-20
申请号：US17162806
申请日：2021-01-29
Applicant: X Development LLC
Inventor： Cheng-en Guo , Jie Yang , Elliott Grant
Abstract: In embodiments, obtaining a plurality of image sets associated with a geographical region and a time period, wherein each image set of the plurality of image sets comprises multi-spectral and time series images that depict a respective particular portion of the geographical region during the time period, and predicting one or more crop types growing in each of particular locations within the particular portion of the geographical region associated with an image set of the plurality of image sets. Determining a crop type classification for each of the particular locations based on the predicted one or more crop types for the respective particular locations, and generating a crop indicative image comprising at least one image of the multi-spectral and time series images of the image set overlaid with indications of the crop type classification determined for the respective particular locations.
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公开(公告)号：US10885331B2
公开(公告)日：2021-01-05
申请号：US16218374
申请日：2018-12-12
Applicant: X Development LLC
Inventor： Cheng-en Guo , Jie Yang , Elliott Grant
Abstract: In embodiments, obtaining a plurality of image sets associated with a geographical region and a time period, wherein each image set of the plurality of image sets comprises multi-spectral and time series images that depict a respective particular portion of the geographical region during the time period, and predicting presence of a crop at particular locations within the particular portion of the geographical region associated with an image set of the plurality of image sets. Determining crop boundary locations within the particular portion of the geographical region based on the predicted presence of the crop at the particular locations, and generating a crop indicative image comprising at least one image of the multi-spectral and time series images of the image set overlaid with indication of crop areas, wherein the crop areas are defined by the determined crop boundary locations.
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Patent Agency Ranking
公开(公告)号：US20190228225A1
公开(公告)日：2019-07-25
申请号：US16218374
申请日：2018-12-12
Applicant: X Development LLC
Inventor： Cheng-en Guo , Jie Yang , Elliott Grant
Abstract: In embodiments, obtaining a plurality of image sets associated with a geographical region and a time period, wherein each image set of the plurality of image sets comprises multi-spectral and time series images that depict a respective particular portion of the geographical region during the time period, and predicting presence of a crop at particular locations within the particular portion of the geographical region associated with an image set of the plurality of image sets. Determining crop boundary locations within the particular portion of the geographical region based on the predicted presence of the crop at the particular locations, and generating a crop indicative image comprising at least one image of the multi-spectral and time series images of the image set overlaid with indication of crop areas, wherein the crop areas are defined by the determined crop boundary locations.
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公开(公告)号：US11606896B2
公开(公告)日：2023-03-21
申请号：US17147048
申请日：2021-01-12
Applicant: X Development LLC
Inventor： Cheng-en Guo , Jie Yang , Zhiqiang Yuan , Elliott Grant
Abstract: Implementations are described herein for predicting soil organic carbon (“SOC”) content for agricultural fields detected in digital imagery. In various implementations, one or more digital images depicting portion(s) of one or more agricultural fields may be processed. The one or more digital images may have been acquired by a vision sensor carried through the field(s) by a ground-based vehicle. Based on the processing, one or more agricultural inferences indicating agricultural practices or conditions predicted to affect SOC content may be determined. Based on the agricultural inferences, one or more predicted SOC measurements for the field(s) may be determined.
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公开(公告)号：US11501443B2
公开(公告)日：2022-11-15
申请号：US17110141
申请日：2020-12-02
Applicant: X Development LLC
Inventor： Jie Yang , Cheng-en Guo , Zhiqiang Yuan , Elliott Grant , Hongxu Ma
IPC: G06T7/00 , A01D41/127 , G06T5/50 , G06T7/143 , G06N3/04 , G06N3/08 , G06Q10/04 , G06Q50/02 , G06V20/13 , G06V20/10
Abstract: Implementations relate to detecting/replacing transient obstructions from high-elevation digital images, and/or to fusing data from high-elevation digital images having different spatial, temporal, and/or spectral resolutions. In various implementations, first and second temporal sequences of high-elevation digital images capturing a geographic area may be obtained. These temporal sequences may have different spatial, temporal, and/or spectral resolutions (or frequencies). A mapping may be generated of the pixels of the high-elevation digital images of the second temporal sequence to respective sub-pixels of the first temporal sequence. A point in time at which a synthetic high-elevation digital image of the geographic area may be selected. The synthetic high-elevation digital image may be generated for the point in time based on the mapping and other data described herein.
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公开(公告)号：US20210183108A1
公开(公告)日：2021-06-17
申请号：US16715285
申请日：2019-12-16
Applicant: X Development LLC
Inventor： Kathleen Watson , Jie Yang , Yueqi Li
IPC: G06T7/00
Abstract: Implementations are described herein for edge-based real time crop yield predictions made using sampled subsets of robotically-acquired vision data. In various implementations, one or more robots may be deployed amongst a plurality of plants in an area such as a field. Using one or more vision sensors of the one or more robots, a superset of high resolution images may be acquired that depict the plurality of plants. A subset of multiple high resolution images may then be sampled from the superset of high resolution images. Data indicative of the subset of high resolution images may be applied as input across a machine learning model, with or without additional data, to generate output indicative of a real time crop yield prediction.
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公开(公告)号：US20210150717A1
公开(公告)日：2021-05-20
申请号：US17160928
申请日：2021-01-28
Applicant: X Development LLC
Inventor： Cheng-en Guo , Wilson Zhao , Jie Yang , Zhiqiang Yuan , Elliott Grant
IPC: G06T7/00 , A01D41/127 , G06K9/00 , G06T5/50 , G06T7/143 , G06N3/04 , G06N3/08 , G06Q10/04 , G06Q50/02
Abstract: Implementations relate to diagnosis of crop yield predictions and/or crop yields at the field- and pixel-level. In various implementations, a first temporal sequence of high-elevation digital images may be obtained that captures a geographic area over a given time interval through a crop cycle of a first type of crop. Ground truth operational data generated through the given time interval and that influences a final crop yield of the first geographic area after the crop cycle may also be obtained. Based on these data, a ground truth-based crop yield prediction may be generated for the first geographic area at the crop cycle's end. Recommended operational change(s) may be identified based on distinct hypothetical crop yield prediction(s) for the first geographic area. Each distinct hypothetical crop yield prediction may be generated based on hypothetical operational data that includes altered data point(s) of the ground truth operational data.
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