AR116766A1 - Técnicas de aprendizaje automático para identificar nubes y sombras de nubes en imágenes satelitales - Google Patents
Técnicas de aprendizaje automático para identificar nubes y sombras de nubes en imágenes satelitalesInfo
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- 230000009418 agronomic effect Effects 0.000 abstract 2
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- G06T5/00—Image enhancement or restoration
- G06T5/77—Retouching; Inpainting; Scratch removal
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
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- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
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- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
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- G—PHYSICS
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- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
- G06V20/188—Vegetation
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- G06N3/02—Neural networks
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- G—PHYSICS
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
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- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
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- G—PHYSICS
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- G06T2207/30—Subject of image; Context of image processing
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- G06T2207/30188—Vegetation; Agriculture
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Abstract
En esta divulgación se describen sistemas y métodos para identificar nubes y sombras de nubes en imágenes satelitales. En una materialización, un sistema recibe una gran cantidad de imágenes de campos agronómicos producidas mediante el uso de una o más bandas de frecuencia. El sistema también recibe datos correspondientes que identifican la ubicación de nubes y sombras de nubes en las imágenes. El sistema entrena a un sistema de aprendizaje automático para identificar por lo menos la ubicación de nubes utilizando las imágenes como información y por lo menos datos que identifican píxeles como píxeles de nubes o píxeles que no son nubes como resultados. Cuando el sistema recibe una o más imágenes particulares de un campo agronómico en particular producidas usando las bandas de frecuencia, el sistema usa una o todas las imágenes particulares como información para el sistema de aprendizaje automático para identificar una gran cantidad de píxeles en una o todas las imágenes particulares como ubicaciones de nubes particulares.
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201862748293P | 2018-10-19 | 2018-10-19 |
Publications (1)
Publication Number | Publication Date |
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AR116766A1 true AR116766A1 (es) | 2021-06-09 |
Family
ID=70279659
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
ARP190102982A AR116766A1 (es) | 2018-10-19 | 2019-10-18 | Técnicas de aprendizaje automático para identificar nubes y sombras de nubes en imágenes satelitales |
Country Status (9)
Country | Link |
---|---|
US (3) | US11256916B2 (es) |
EP (1) | EP3867872A4 (es) |
CN (1) | CN112889089B (es) |
AR (1) | AR116766A1 (es) |
AU (1) | AU2019362019A1 (es) |
BR (1) | BR112021006133A2 (es) |
CA (1) | CA3114956A1 (es) |
MX (1) | MX2021004475A (es) |
WO (1) | WO2020081909A1 (es) |
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2019
- 2019-10-18 CN CN201980068622.9A patent/CN112889089B/zh active Active
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2022
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2023
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CN112889089A (zh) | 2021-06-01 |
US20240013352A1 (en) | 2024-01-11 |
MX2021004475A (es) | 2021-06-04 |
US11769232B2 (en) | 2023-09-26 |
US20220237911A1 (en) | 2022-07-28 |
AU2019362019A1 (en) | 2021-05-20 |
EP3867872A1 (en) | 2021-08-25 |
US11256916B2 (en) | 2022-02-22 |
EP3867872A4 (en) | 2022-08-03 |
CA3114956A1 (en) | 2020-04-23 |
US20200125844A1 (en) | 2020-04-23 |
BR112021006133A2 (pt) | 2021-06-29 |
CN112889089B (zh) | 2024-03-05 |
WO2020081909A1 (en) | 2020-04-23 |
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