[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Cavalcanti et al., 2023 - Google Patents

Use of RGB images from unmanned aerial vehicle to estimate lettuce growth in root-knot nematode infested soil

Cavalcanti et al., 2023

View HTML
Document ID
4923187104109777628
Author
Cavalcanti V
dos Santos A
Rodrigues F
Terra W
Araújo R
Ribeiro C
Campos V
Rigobelo E
Medeiros F
Dória J
Publication year
Publication venue
Smart Agricultural Technology

External Links

Snippet

Lettuce (Lactuca sativa) is an important horticultural commodity all over the world, and its growth can be affected by root-knot nematodes (Meloidogyne spp.). To keep track of plant behaviors, growers are using new technologies. In this paper, aerial images were obtained …
Continue reading at www.sciencedirect.com (HTML) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/0063Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
    • G06K9/00657Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/314Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
    • G01N2021/3155Measuring in two spectral ranges, e.g. UV and visible
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10032Satellite or aerial image; Remote sensing
    • G06T2207/10036Multispectral image; Hyperspectral image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10024Color image

Similar Documents

Publication Publication Date Title
Ali et al. Crop yield prediction using multi sensors remote sensing
Su et al. Spatio-temporal monitoring of wheat yellow rust using UAV multispectral imagery
Zhang et al. High-resolution satellite imagery applications in crop phenotyping: An overview
Chong et al. A review of remote sensing applications for oil palm studies
Wójtowicz et al. Application of remote sensing methods in agriculture
US7715013B2 (en) Optical system for plant characterization
Jiménez-Brenes et al. Automatic UAV-based detection of Cynodon dactylon for site-specific vineyard management
Usha et al. Potential applications of remote sensing in horticulture—A review
EP4150515A1 (en) System and method for crop monitoring
da Rocha Miranda et al. Detection of coffee berry necrosis by digital image processing of landsat 8 oli satellite imagery
Moriya et al. Detection and mapping of trees infected with citrus gummosis using UAV hyperspectral data
US20220392215A1 (en) System and Method for Mapping Land Cover Types with Landsat, Sentinel-1, and Sentinel-2 Images
Lizarazo et al. Identification of symptoms related to potato Verticillium wilt from UAV-based multispectral imagery using an ensemble of gradient boosting machines
CN115136207A (en) Method and system for automatic plant image tagging
Cavalcanti et al. Use of RGB images from unmanned aerial vehicle to estimate lettuce growth in root-knot nematode infested soil
KR20200020209A (en) Applaratus for Monitoring Crop Growth through Multispectral Image Histogram Pattern Analysis of Plot Unit
Poudyal et al. Prediction of morpho-physiological traits in sugarcane using aerial imagery and machine learning
Westbrook et al. Airborne multispectral identification of individual cotton plants using consumer-grade cameras
Sah et al. Discrimination and monitoring of rice cultural types using dense time series of Sentinel-1 SAR data
Brewer et al. Remote sensing of invasive alien wattle using image texture ratios in the low-lying Midlands of KwaZulu-Natal, South Africa
Lass et al. Detecting the locations of Brazilian pepper trees in the Everglades with a hyperspectral sensor
Jiang et al. Automated segmentation of individual leafy potato stems after canopy consolidation using YOLOv8x with spatial and spectral features for UAV-based dense crop identification
Bhatia Hyperspectral remote sensing for early detection of wild carrot in Carrot (Daucus carota) seed production: a feasibility study: a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Horticultural Science at Massey University, Manawatū, New Zealand
Chakraborty et al. Early almond yield forecasting by bloom mapping using aerial imagery and deep learning
Chaiyana et al. Mapping and predicting cassava mosaic disease outbreaks using earth observation and meteorological data-driven approaches