公开(公告)号：US20210150207A1

公开(公告)日：2021-05-20

申请号：US17138737

申请日：2020-12-30

Applicant: X Development LLC

Inventor： Cheng-en Guo ,  Jie Yang ,  Elliott Grant

IPC: G06K9/00 ,  G06N3/08 ,  G06T7/11 ,  G06Q50/02 ,  A01B79/00

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.

公开(公告)号：US10909368B2

公开(公告)日：2021-02-02

申请号：US16218305

申请日：2018-12-12

Applicant: X Development LLC

Inventor： Cheng-en Guo ,  Jie Yang ,  Elliott Grant

IPC: G06K9/00 ,  G06N7/00 ,  G06N3/08 ,  G06N20/20 ,  G06T7/174 ,  G06K9/46 ,  G06K9/40 ,  G06K9/62 ,  G06Q50/02

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.

公开(公告)号：US20190392596A1

公开(公告)日：2019-12-26

申请号：US16016495

申请日：2018-06-22

Applicant: X Development LLC

Inventor： Jie Yang ,  Cheng-en Guo ,  Elliott Grant

IPC: G06T7/33 ,  G06K9/00 ,  G06K9/62

Abstract: Implementations relate to detecting/replacing transient obstructions from high-elevation digital images. A digital image of a geographic area includes pixels that align spatially with respective geographic units of the geographic area. Analysis of the digital image may uncover obscured pixel(s) that align spatially with geographic unit(s) of the geographic area that are obscured by transient obstruction(s). Domain fingerprint(s) of the obscured geographic unit(s) may be determined across pixels of a corpus of digital images that align spatially with the one or more obscured geographic units. Unobscured pixel(s) of the same/different digital image may be identified that align spatially with unobscured geographic unit(s) of the geographic area. The unobscured geographic unit(s) also may have domain fingerprint(s) that match the domain fingerprint(s) of the obscured geographic unit(s). Replacement pixel data may be calculated based on the unobscured pixels and used to generate a transient-obstruction-free version of the digital image.

公开(公告)号：US20230028706A1

公开(公告)日：2023-01-26

申请号：US17960432

申请日：2022-10-05

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.

公开(公告)号：US20220217894A1

公开(公告)日：2022-07-14

申请号：US17147048

申请日：2021-01-12

Applicant: X Development LLC

Inventor： Cheng-en Guo ,  Jie Yang ,  Zhiqiang Yuan ,  Elliott Grant

IPC: A01B79/00 ,  G01N33/24 ,  G06K9/00 ,  G06T7/00

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.

公开(公告)号：US10949972B2

公开(公告)日：2021-03-16

申请号：US16236743

申请日：2018-12-31

Applicant: X Development LLC

Inventor： Cheng-en Guo ,  Wilson Zhao ,  Jie Yang ,  Zhiqiang Yuan ,  Elliott Grant

IPC: G06T7/00 ,  G06T5/50 ,  G06T7/143 ,  A01D41/127 ,  G06K9/00 ,  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.