Cargando…
Deep Learning in Precision Agriculture: Artificially Generated VNIR Images Segmentation for Early Postharvest Decay Prediction in Apples
Food quality control is an important task in the agricultural domain at the postharvest stage for avoiding food losses. The latest achievements in image processing with deep learning (DL) and computer vision (CV) approaches provide a number of effective tools based on the image colorization and imag...
Autores principales: | Stasenko, Nikita, Shukhratov, Islomjon, Savinov, Maxim, Shadrin, Dmitrii, Somov, Andrey |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378337/ https://www.ncbi.nlm.nih.gov/pubmed/37509935 http://dx.doi.org/10.3390/e25070987 |
Ejemplares similares
-
Evaluation of Endospore-Forming Bacteria for Suppression of Postharvest Decay of Apple Fruit
por: Poleatewich, Anissa, et al.
Publicado: (2022) -
Genome Sequence of Penicillium solitum RS1, Which Causes Postharvest Apple Decay
por: Yu, Jiujiang, et al.
Publicado: (2016) -
Impact of vanillin on postharvest disease control of apple
por: Wang, Xiangyu, et al.
Publicado: (2022) -
Classification Metrics for Improved Atmospheric Correction of Multispectral VNIR Imagery
por: Richter, Rudolf
Publicado: (2008) -
A Hyperspectral Imaging Approach for Classifying Geographical Origins of Rhizoma Atractylodis Macrocephalae Using the Fusion of Spectrum-Image in VNIR and SWIR Ranges (VNIR-SWIR-FuSI)
por: Ru, Chenlei, et al.
Publicado: (2019)