Prediction of beef marbling using Hyperspectral Imaging (HSI) and Partial Least Squares Regression (PLSR)

Least Squares Initialisation (LSI) has the aim of improving the initial conditions of partially initialised systems by utilizing the information from observations of limited

In any case, when a new object x should be assessed, the c binary learners are evaluated at x, and a vector with the outputs y¼(y 1 , y 2 , …, y c ) or predicted codeword is

To assess the potential impact of dry-ageing of beef and wet-ageing on beef, pork and lamb under selected current practices, on the load of public health-relevant

In addition, the results can help to raise awareness among policymakers of the need to make appropriate investments in the healthcare system, re- sulting in more available resources

The goal of this study was to demonstrate the capability of airborne hyperspectral imaging for wetland mapping using the Yukon Flats as a test case by means of (a) commissioning

Least-Squares Support Vector Machines (LS-SVMs) have been successfully applied in many classification and regression tasks. Their main drawback is the lack of sparseness of the

Mean absolute error (MAE) of the different forecasts: (i) initial competing forecasts (M1, M2, M3, M4, M5, M6 and M7 models) represented in grey color; NR has not been included in

The focus of this paper was to investigate the contribution of different physicochemical parameters to bulking episodes, and to develop logistic regression models to predict