Rapid identification of tea quality by E-nose and computer vision combining with a synergetic data fusion strategy
Year: 2018
Type: article
Source: Journal of Food Engineering
Institution: Zhejiang University
Language: English
Subfield: Analytical Chemistry
Field: Chemistry
Domain: Physical Sciences
Open Access status: closed
Awards: G309980374, G8363145814
OpenAlex ID: W2884444414
