Abstract: Apparatus having model-based machine learning and inferencing logic for controlling object transfer, comprises: an image input component to receive image data derived from a captured image of an object; a captured image classifier to 5 generate a first classification of the object by activating a trained model to analyse the image data; an input component to receive an object identifier for the object; an object identification classifier to generate a second classification of the object according to the object identifier; matching logic to detect failure to reconcile the first and second classification; heuristic logic responsive to the matching logic to 10 determine a causal factor in the failure; and training logic, operable when the heuristic logic determines that a causal factor in the failure to reconcile is a deficient first classification, to provide model training input comprising the image data and the object identifier to the model-based machine learning logic.

Abstract: Provided is machine learning apparatus comprising: a dataset for input to a training procedure of a machine learning model; data capture logic operable to capture from an object at least one datum for inclusion in the dataset; association logic operable to derive an additional characteristic of the object; annotator logic operable in response to the data capture logic and the association logic to create an annotation linking the additional characteristic with the at least one datum; storage logic operable to store the or each datum with an associated annotation in the dataset; and input logic to supply the dataset as machine learning input.