Cargando…
Active learning with point supervision for cost-effective panicle detection in cereal crops
BACKGROUND: Panicle density of cereal crops such as wheat and sorghum is one of the main components for plant breeders and agronomists in understanding the yield of their crops. To phenotype the panicle density effectively, researchers agree there is a significant need for computer vision-based obje...
Autores principales: | Chandra, Akshay L., Desai, Sai Vikas, Balasubramanian, Vineeth N., Ninomiya, Seishi, Guo, Wei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7060654/ https://www.ncbi.nlm.nih.gov/pubmed/32161624 http://dx.doi.org/10.1186/s13007-020-00575-8 |
Ejemplares similares
-
Automatic estimation of heading date of paddy rice using deep learning
por: Desai, Sai Vikas, et al.
Publicado: (2019) -
How Useful Is Image-Based Active Learning for Plant Organ Segmentation?
por: Rawat, Shivangana, et al.
Publicado: (2022) -
Analyzing Nitrogen Effects on Rice Panicle Development by Panicle Detection and Time-Series Tracking
por: Zhou, Qinyang, et al.
Publicado: (2023) -
Quantifying cereal crop movement through hemispherical video analysis of agricultural plots
por: Susko, Alexander Q., et al.
Publicado: (2019) -
An in situ approach to characterizing photosynthetic gas exchange of rice panicle
por: Chang, Tian-Gen, et al.
Publicado: (2020)