Non-destructively sensing pork’s freshness indicator using near infrared multispectral imaging technique
By Qiping Huang, Quansheng Chen, Huanhuan Li, Gengping Huang, Ouyang Qin, Jiewen Zhao. 2015
62 citations recorded by the source corpus.
Subfields: Analytical Chemistry, Animal Science and Zoology, Biomedical Engineering
View Paper: https://www.semanticscholar.org/paper/baff9f082cbbc0322264051e899b737e0f449f54
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In Analytical Chemistry
In Animal Science and Zoology
In Biomedical Engineering
Citations in the corpus
- Enhancing Visible and Near-Infrared Hyperspectral Imaging Prediction of TVB-N Level for Fish Fillet Freshness Evaluation by Filtering Optimal Variables (2017, methodology): “Although these studies (Chen et al. 2013; Huang et al. 2015; Cheng et al. 2014a, b, c) have confirmed the potential and success of using hyperspectral imagingwith chemometric analysis for prediction of TVB-N level, the accuracies and reliabilities of these reported models are still low and it is…”
- Quantifying Total Viable Count in Pork Meat Using Combined Hyperspectral Imaging and Artificial Olfaction Techniques (2016, background): “…as the most classical feed-forward multi-layer network consisting of neurons arranged in layers (an input layer, one or more hidden layers, and an output layer) being the connected (weights) unidirectional from input to output (Chen et al. 2010a, c; Huang et al. 2015a, b; Urmila et al. 2015).”