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Classification can be highly challenging when the dataset is extremely large, or when the training data in the underlying domain are difficult to obtain. One feasible solution to this challenge is transfer learning, which extracts the knowledge from source tasks and applies the knowledge to target tasks. Extant transfer learning schemes typically assume that similarities between the source task and...
To precisely determine heme and non-heme iron contents in meat product, the feasibility of combining spectral with texture features extracted from multispectral imaging data (405–970nm) was assessed. In our study, spectra and textures of 120 pork sausages (PSs) treated by different temperatures (30–80°C) were analyzed using different calibration models including partial least squares regression (PLSR)...
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