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公开(公告)号：US10311302B2
公开(公告)日：2019-06-04
申请号：US15253488
申请日：2016-08-31
Applicant: Cape Analytics, Inc.
Inventor： Ryan Kottenstette , Peter Lorenzen , Suat Gedikli
Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
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Patent Agency Ranking
公开(公告)号：US10366288B1
公开(公告)日：2019-07-30
申请号：US16353361
申请日：2019-03-14
Applicant: Cape Analytics, Inc.
Inventor： Ryan Kottenstette , Peter Lorenzen , Suat Gedikli
Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
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公开(公告)号：US20220004762A1
公开(公告)日：2022-01-06
申请号：US17475523
申请日：2021-09-15
Applicant: Cape Analytics, Inc.
Inventor： Ryan Kottenstette , Peter Lorenzen , Suat Gedikli
Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
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公开(公告)号：US11568639B2
公开(公告)日：2023-01-31
申请号：US17475523
申请日：2021-09-15
Applicant: Cape Analytics, Inc.
Inventor： Ryan Kottenstette , Peter Lorenzen , Suat Gedikli
Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
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公开(公告)号：US11151378B2
公开(公告)日：2021-10-19
申请号：US16833313
申请日：2020-03-27
Applicant: Cape Analytics, Inc.
Inventor： Ryan Kottenstette , Peter Lorenzen , Suat Gedikli
Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
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公开(公告)号：US20200226373A1
公开(公告)日：2020-07-16
申请号：US16833313
申请日：2020-03-27
Applicant: Cape Analytics, Inc.
Inventor： Ryan Kottenstette , Peter Lorenzen , Suat Gedikli
Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
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