MX2021006830A - Mapeo de anomalias de campo utilizando imagenes digitales y modelos de aprendizaje por maquina. - Google Patents

Mapeo de anomalias de campo utilizando imagenes digitales y modelos de aprendizaje por maquina.

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Publication number
MX2021006830A
MX2021006830A MX2021006830A MX2021006830A MX2021006830A MX 2021006830 A MX2021006830 A MX 2021006830A MX 2021006830 A MX2021006830 A MX 2021006830A MX 2021006830 A MX2021006830 A MX 2021006830A MX 2021006830 A MX2021006830 A MX 2021006830A
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Mexico
Prior art keywords
parcel
map
machine learning
images
generate
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MX2021006830A
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English (en)
Inventor
Boyan Peshlov
Weilin Wang
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Climate Llc
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Publication of MX2021006830A publication Critical patent/MX2021006830A/es

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    • G06—COMPUTING OR CALCULATING; COUNTING
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    • A01B—SOIL WORKING IN AGRICULTURE OR FORESTRY; PARTS, DETAILS, OR ACCESSORIES OF AGRICULTURAL MACHINES OR IMPLEMENTS, IN GENERAL
    • A01B69/00—Steering of agricultural machines or implements; Guiding agricultural machines or implements on a desired track
    • A01B69/007—Steering or guiding of agricultural vehicles, e.g. steering of the tractor to keep the plough in the furrow
    • A01B69/008—Steering or guiding of agricultural vehicles, e.g. steering of the tractor to keep the plough in the furrow automatic
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64C—AEROPLANES; HELICOPTERS
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    • G—PHYSICS
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    • G06N3/045—Combinations of networks
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    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
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    • G06N3/08—Learning methods
    • G06N3/09—Supervised learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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    • G06—COMPUTING OR CALCULATING; COUNTING
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    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
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    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
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    • A01B79/00—Methods for working soil
    • A01B79/005—Precision agriculture
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G25/00—Watering gardens, fields, sports grounds or the like
    • A01G25/16—Control of watering
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2101/00—UAVs specially adapted for particular uses or applications
    • B64U2101/30—UAVs specially adapted for particular uses or applications for imaging, photography or videography
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2101/00—UAVs specially adapted for particular uses or applications
    • B64U2101/30—UAVs specially adapted for particular uses or applications for imaging, photography or videography
    • B64U2101/32—UAVs specially adapted for particular uses or applications for imaging, photography or videography for cartography or topography
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
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    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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    • G06T2207/10—Image acquisition modality
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    • G—PHYSICS
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    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10032—Satellite or aerial image; Remote sensing
    • G06T2207/10036—Multispectral image; Hyperspectral image
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10048—Infrared image
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20021—Dividing image into blocks, subimages or windows
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • G—PHYSICS
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    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30181—Earth observation
    • G06T2207/30188—Vegetation; Agriculture
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/194—Terrestrial scenes using hyperspectral data, i.e. more or other wavelengths than RGB

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Evolutionary Computation (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Computing Systems (AREA)
  • Artificial Intelligence (AREA)
  • General Engineering & Computer Science (AREA)
  • Molecular Biology (AREA)
  • Mathematical Physics (AREA)
  • Data Mining & Analysis (AREA)
  • Computational Linguistics (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Multimedia (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Quality & Reliability (AREA)
  • Medical Informatics (AREA)
  • Databases & Information Systems (AREA)
  • Mechanical Engineering (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Soil Sciences (AREA)
  • Environmental Sciences (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Image Analysis (AREA)
  • Testing And Monitoring For Control Systems (AREA)
  • Image Processing (AREA)

Abstract

Se divulga un método implementado por computadora para generar un mapa mejorado de anomalías de campo utilizando imágenes digitales y modelos de aprendizaje por máquina; en una modalidad, un método comprende: obtener un Shapefile que define límites de una parcela agrícola y límites del campo que contiene la parcela; obtener una pluralidad de imágenes de parcelas; calibrar y pre-procesar la pluralidad de imágenes de parcelas para crear un mapa de parcelas de la parcela agrícola a un nivel de parcela; con base en el mapa de parcela, generar una rejilla de parcela; con base en la rejilla de gráfico y el mapa de gráfico, generar una pluralidad de mosaicos de parcela; con base en la pluralidad de mosaicos de parcela, generar, utilizando un modelo de aprendizaje por máquina y una pluralidad de clasificadores de imagen correspondientes a una o más anomalías, un conjunto de imágenes de parcela clasificadas que muestra al menos una anomalía; con base en el conjunto de imágenes de parcela clasificadas, generar un mapa de anomalía de parcela para la parcela agrícola.
MX2021006830A 2018-12-10 2019-12-09 Mapeo de anomalias de campo utilizando imagenes digitales y modelos de aprendizaje por maquina. MX2021006830A (es)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201862777748P 2018-12-10 2018-12-10
US16/707,355 US12008744B2 (en) 2018-12-10 2019-12-09 Mapping field anomalies using digital images and machine learning models
PCT/US2019/065270 WO2020123402A1 (en) 2018-12-10 2019-12-09 Mapping field anomalies using digital images and machine learning models

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Publication Number Publication Date
MX2021006830A true MX2021006830A (es) 2021-07-02

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US (2) US12008744B2 (es)
EP (1) EP3894851B8 (es)
JP (1) JP7423631B2 (es)
CN (1) CN113167779B (es)
AR (1) AR117293A1 (es)
AU (1) AU2019398116B2 (es)
BR (1) BR112021009659A2 (es)
CA (1) CA3119812A1 (es)
MX (1) MX2021006830A (es)
WO (1) WO2020123402A1 (es)

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