Buchumschlag

Computer vision‐based recognition and distinction of Arabidopsis thaliana ecotypes using supervised deep learning models

Fuente: Wiley Open Access

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Rijad Sarić, Edhem Čustović, Amila Akagić, Martin Trtílek, Mathew G. Lewsey, James Whelan
Format:	Artículo Open Access
Veröffentlicht:	Wiley 2025
Schlagworte:	The Plant Phenome Journal
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Sorghum segmentation and leaf counting using in silico trained deep neural model
von: Ian Ostermann, et al.
Veröffentlicht: (2024)

Estimating Fusarium head blight severity in winter wheat using deep learning and a spectral index
von: Riley McConachie, et al.
Veröffentlicht: (2024)

SMART: Speedy Measurement of Arabidopsis Rosette Traits
von: Suxing Liu, et al.
Veröffentlicht: (2026)

Deep learning and computer vision for image‐based high‐throughput phenotyping of canning quality traits in dry beans
von: Lovepreet Singh, et al.
Veröffentlicht: (2026)

UAV‐based deep transfer learning to improve grain yield prediction in winter wheat across temporal and spatial variability
von: Swas Kaushal, et al.
Veröffentlicht: (2026)

Zero‐shot insect detection via weak language supervision
von: Benjamin Feuer, et al.
Veröffentlicht: (2024)

Phenotypic scoring of canola blackleg severity using machine learning image analysis
von: Qiao Hu, et al.
Veröffentlicht: (2026)

Improving estimation of days to maturity in field pea using RGB aerial imagery and machine learning
von: Harry Navasca, et al.
Veröffentlicht: (2025)

Rapid estimation of DON content in wheat flour using close‐range hyperspectral imaging and machine learning
von: Dinesh Kumar Saini, et al.
Veröffentlicht: (2024)

Temporal field phenomics of transgenic maize events subjected to drought stress: Cross‐validation scenarios and machine learning models
von: Helcio Duarte Pereira, et al.
Veröffentlicht: (2025)

High‐throughput phenotyping of stay‐green in a sorghum breeding program using unmanned aerial vehicles and machine learning
von: N. Ace Pugh, et al.
Veröffentlicht: (2025)

Pixel‐level supervision resolves overlap: Benchmarking YOLOv12 segmentation for accurate multi‐cluster dry bean stand counting from time series unoccupied aerial systems imagery
von: Aliasghar Bazrafkan, et al.
Veröffentlicht: (2026)

Phenotype imputation using high‐throughput phenotyping produces a new secondary trait for further selection modeling
von: Raysa Gevartosky, et al.
Veröffentlicht: (2026)

Forward prediction of grain yield across early and advanced generations in winter wheat ( Triticum aestivum L.) using NIRS‐based models
von: Pranvera Berisha, et al.
Veröffentlicht: (2025)

Hyperspectral imaging combined with machine learning for high‐throughput phenotyping in winter wheat
von: Sehijpreet Kaur, et al.
Veröffentlicht: (2024)

GWAS analysis for plant height and stem diameter in sorghum using multiple phenotyping approaches
von: Lucas Boatwright, et al.
Veröffentlicht: (2024)

Deep learning‐based high‐throughput detection of flowered maize ( Zea mays L.) plots from UAS imagery across environments
von: Nicholas R. Shepard, et al.
Veröffentlicht: (2025)

Assessing robustness and transferability of image‐based semantic segmentation models for major field crops
von: Gustavo N. Santiago, et al.
Veröffentlicht: (2026)

Unmanned aerial vehicle–based spatiotemporal phenotyping and growth modeling for forecasting potato yield
von: Yuto Imachi, et al.
Veröffentlicht: (2026)

Leveraging high‐dimensional seed colorspace in phenomic selection models for herbaceous perennial crops
von: William Keaggy, et al.
Veröffentlicht: (2025)

Hyperspectral reflectance‐based partial least squares regression models for predicting cotton leaf physiological traits
von: Ved Parkash, et al.
Veröffentlicht: (2025)

Three‐dimensional phenotyping of soybean roots under different water treatment conditions using fringe projection
von: Victoria MacDans, et al.
Veröffentlicht: (2025)

Robustness of high‐throughput prediction of leaf ecophysiological traits using near infrared spectroscopy and poro‐fluorometry
von: Eva Coindre, et al.
Veröffentlicht: (2026)

Soybean maturity prediction using two‐dimensional contour plots from drone‐based time series imagery
von: Bitgoeul Kim, et al.
Veröffentlicht: (2025)

Prediction of symbiotic nitrogen fixation in common bean ( Phaseolus vulgaris L.) using unmanned aerial system remote sensing
von: Madison Whyte, et al.
Veröffentlicht: (2025)

Temporal genetic relationships between growth, development, and malting quality in winter barley ( Hordeum vulgare ) using aerial imagery
von: Amelia Loeb, et al.
Veröffentlicht: (2025)

Optimizing wheat crop performance: Genomic and phenomic insights into yield and days to maturity prediction using multi‐temporal UAV imagery
von: Sahameh Shafiee, et al.
Veröffentlicht: (2024)

Comparison of PhenoCams and drones for lean phenotyping of phenology and senescence of wheat genotypes in variety testing
von: Simon Treier, et al.
Veröffentlicht: (2025)

Class‐specific data augmentation for plant stress classification
von: Nasla Saleem, et al.
Veröffentlicht: (2024)

Predicting soybean aboveground biomass in the short‐season region of Canada: Integrating vegetative cover and canopy height
von: Malcolm J. Morrison, et al.
Veröffentlicht: (2026)

Utilizing QGIS for open‐source UAS imagery plant classification and plot segmentation
von: Erik Z. Killian, et al.
Veröffentlicht: (2025)

Drone‐based imaging sensors, techniques, and applications in plant phenotyping for crop breeding: A comprehensive review
von: Boubacar Gano, et al.
Veröffentlicht: (2024)

Selection of appropriate multispectral camera exposure settings and radiometric calibration methods for applications in phenotyping and precision agriculture
von: Vaishali Swaminathan, et al.
Veröffentlicht: (2024)

Drone‐based polarization imaging system for leaf spot severity determination in peanut plants
von: Joshua Larsen, et al.
Veröffentlicht: (2025)

Issue Information
Veröffentlicht: (2025)

Issue Information
Veröffentlicht: (2025)

Do not benchmark phenomic prediction against genomic prediction accuracy
von: Fangyi Wang, et al.
Veröffentlicht: (2025)

Limitations of phenomic prediction for evaluating wheat stem sawfly resistance in wheat breeding programs
von: Sydney E. Graham, et al.
Veröffentlicht: (2025)

Recipients of 2023 The Plant Phenome Journal Editor's Citation for Excellence Named
Veröffentlicht: (2024)

Developing and deploying an unmanned aerial system–based phenotyping program for maturity to support soybean breeding
von: Nathaniel Burner, et al.
Veröffentlicht: (2026)