A computer-implemented method for training a software infrastructure, wherein the software infrastructure is based on machine-learning techniques and intended to analyse data obtained from a non-tomographic instrumental examination of objects of a pre-determined type in order to determine information on characteristics of interest of those objects, wherein, moreover, each of the objects has been obtained by splitting a product into pieces; wherein the data obtained from the instrumental examination are in electronic format; wherein, once a training set comprising a plurality of training objects of a predetermined type has been chosen, training input data and the corresponding training output data are fed into the software infrastructure for each training object; wherein the training input data for each training object comprise the data obtained from the instrumental examination on that trained object; wherein the training output data for each trained object comprise information on the characteristics of interest of the training object; wherein the information on the characteristics of interest is, at least in part, information that has been obtained from the results of a tomographic examination of the product from which the training object was obtained; wherein the software infrastructure processes, through its own training unit, the training input data and the training output data for each training object in order to set internal processing parameters of the software infrastructure which correlate the training input data to the training output data; and wherein said objects are wooden boards and said products are wooden logs. wherein the software infrastructure is based on machine-learning techniques and intended to analyse data obtained from a non-tomographic instrumental examination of objects of a pre-determined type in order to determine information on characteristics of interest of those objects, wherein, moreover, each of the objects has been obtained by splitting a product into pieces; wherein the data obtained from the instrumental examination are in electronic format; wherein, once a training set comprising a plurality of training objects of a predetermined type has been chosen, training input data and the corresponding training output data are fed into the software infrastructure for each training object; wherein the training input data for each training object comprise the data obtained from the instrumental examination on that trained object; wherein the training output data for each trained object comprise information on the characteristics of interest of the training object; wherein the information on the characteristics of interest is, at least in part, information that has been obtained from the results of a tomographic examination of the product from which the training object was obtained; wherein the software infrastructure processes, through its own training unit, the training input data and the training output data for each training object in order to set internal processing parameters of the software infrastructure which correlate the training input data to the training output data; and wherein said objects are wooden boards and said products are wooden logs. <EOS>