Cargando…
Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review
Non-destructive testing techniques have gained importance in monitoring food quality over the years. Hyperspectral imaging is one of the important non-destructive quality testing techniques which provides both spatial and spectral information. Advancement in machine learning techniques for rapid ana...
Autores principales: | Saha, Dhritiman, Manickavasagan, Annamalai |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890297/ https://www.ncbi.nlm.nih.gov/pubmed/33659896 http://dx.doi.org/10.1016/j.crfs.2021.01.002 |
Ejemplares similares
-
Imaging with electromagnetic spectrum: applications in food and agriculture
por: Manickavasagan, Annamalai, et al.
Publicado: (2014) -
Advances in Machine Learning and Hyperspectral Imaging in the Food Supply Chain
por: Kang, Zhilong, et al.
Publicado: (2022) -
Application of Visible/Infrared Spectroscopy and Hyperspectral Imaging With Machine Learning Techniques for Identifying Food Varieties and Geographical Origins
por: Feng, Lei, et al.
Publicado: (2021) -
Determining the Spectral Requirements for Cyanobacteria Detection for the CyanoSat Hyperspectral Imager with Machine Learning
por: Matthews, Mark W., et al.
Publicado: (2023) -
Identification of Weeds Based on Hyperspectral Imaging and Machine Learning
por: Li, Yanjie, et al.
Publicado: (2021)