Cargando…
DeepCount: In-Field Automatic Quantification of Wheat Spikes Using Simple Linear Iterative Clustering and Deep Convolutional Neural Networks
Crop yield is an essential measure for breeders, researchers, and farmers and is composed of and may be calculated by the number of ears per square meter, grains per ear, and thousand grain weight. Manual wheat ear counting, required in breeding programs to evaluate crop yield potential, is labor-in...
Autores principales: | Sadeghi-Tehran, Pouria, Virlet, Nicolas, Ampe, Eva M., Reyns, Piet, Hawkesford, Malcolm J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6775245/ https://www.ncbi.nlm.nih.gov/pubmed/31616456 http://dx.doi.org/10.3389/fpls.2019.01176 |
Ejemplares similares
-
Scalable Database Indexing and Fast Image Retrieval Based on Deep Learning and Hierarchically Nested Structure Applied to Remote Sensing and Plant Biology
por: Sadeghi-Tehran, Pouria, et al.
Publicado: (2019) -
Automated Method to Determine Two Critical Growth Stages of Wheat: Heading and Flowering
por: Sadeghi-Tehran, Pouria, et al.
Publicado: (2017) -
Multi-feature machine learning model for automatic segmentation of green fractional vegetation cover for high-throughput field phenotyping
por: Sadeghi-Tehran, Pouria, et al.
Publicado: (2017) -
Modeling the spatial-spectral characteristics of plants for nutrient status identification using hyperspectral data and deep learning methods
por: Okyere, Frank Gyan, et al.
Publicado: (2023) -
Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform
por: Lyra, Danilo H, et al.
Publicado: (2020)