公开(公告)号：US11176623B2

公开(公告)日：2021-11-16

申请号：US16595420

申请日：2019-10-07

Applicant: THE CLIMATE CORPORATION

Inventor： Juan Pablo Bedoya ,  Victor Stuber ,  Gerard Guillemette ,  Joost Kemink ,  Yaqi Chen ,  Daniel Williams ,  Ying She ,  Marian Farah ,  Julian Boshard ,  Wei Guan

IPC: G06K9/00 ,  G06Q50/02 ,  G06K9/46 ,  G06K9/68 ,  A01D41/127 ,  G01D21/02 ,  A01B79/00 ,  A01G7/06 ,  A01D91/00 ,  A01G22/00

Abstract: In an embodiment, a computer-implemented method is disclosed. The method comprises causing a camera to continuously capture surroundings to generate multiple images and causing a display device to continuously display the multiple images as the multiple images are generated. In addition, the method comprises processing each of one or more of the multiple images. The processing comprises identifying at least one of a plurality of diseases and calculating at least one disease score associated with the at least one disease for a particular image; causing the display device to display information regarding the at least one disease and the at least one disease score in association with a currently displayed image; receiving input specifying one or more of the at least one disease; and causing the display device to show additional data regarding the one or more diseases, including a remedial measure for the one or more diseases.

公开(公告)号：US10956780B2

公开(公告)日：2021-03-23

申请号：US16662023

申请日：2019-10-24

Applicant: The Climate Corporation

Inventor： Ying She ,  Wei Guan

IPC: G06K9/62 ,  G06N3/04 ,  G06N3/08 ,  G06N5/00

Abstract: A system and processing methods for refining a convolutional neural network (CNN) to capture characterizing features of different classes are disclosed. In some embodiments, the system is programmed to start with the filters in one of the last few convolutional layers of the initial CNN, which often correspond to more class-specific features, rank them to hone in on more relevant filters, and update the initial CNN by turning off the less relevant filters in that one convolutional layer. The result is often a more generalized CNN that is rid of certain filters that do not help characterize the classes.

公开(公告)号：US10438302B2

公开(公告)日：2019-10-08

申请号：US15688567

申请日：2017-08-28

Applicant: THE CLIMATE CORPORATION

Inventor： Juan Pablo Bedoya ,  Victor Stuber ,  Gerard Guillemette ,  Joost Kemink ,  Yaqi Chen ,  Daniel Williams ,  Ying She ,  Marian Farah ,  Julian Boshard ,  Wei Guan

IPC: G06K9/00 ,  G06Q50/02 ,  G06K9/46 ,  G06K9/68 ,  A01D41/127 ,  G01D21/02 ,  A01G7/06 ,  A01B79/00 ,  A01D91/00 ,  A01G22/00

Abstract: In an embodiment, a computer-implemented method is disclosed. The method comprises causing a camera to continuously capture surroundings to generate multiple images and causing a display device to continuously display the multiple images as the multiple images are generated. In addition, the method comprises processing each of one or more of the multiple images. The processing comprises identifying at least one of a plurality of diseases and calculating at least one disease score associated with the at least one disease for a particular image; causing the display device to display information regarding the at least one disease and the at least one disease score in association with a currently displayed image; receiving input specifying one or more of the at least one disease; and causing the display device to show additional data regarding the one or more diseases, including a remedial measure for the one or more diseases.

公开(公告)号：US11256916B2

公开(公告)日：2022-02-22

申请号：US16657957

申请日：2019-10-18

Applicant: The Climate Corporation

Inventor： Ying She ,  Pramithus Khadka ,  Wei Guan ,  Xiaoyuan Yang ,  Demir Devecigil

IPC: G06K9/00 ,  G06F17/16 ,  G06N3/04 ,  G06N20/00

Abstract: Systems and methods for identifying clouds and cloud shadows in satellite imagery are described herein. In an embodiment, a system receives a plurality of images of agronomic fields produced using one or more frequency bands. The system also receives corresponding data identifying cloud and cloud shadow locations in the images. The system trains a machine learning system to identify at least cloud locations using the images as inputs and at least data identifying pixels as cloud pixels or non-cloud pixels as outputs. When the system receives one or more particular images of a particular agronomic field produced using the one or more frequency bands, the system uses the one or more particular images as inputs into the machine learning system to identify a plurality of pixels in the one or more particular images as particular cloud locations.