METHOD AND SYSTEM FOR TRAINING A NEURAL NETWORK-IMPLEMENTED SENSOR SYSTEM TO CLASSIFY OBJECTS IN A BULK FLOW

摘要

The present disclosure relates to a method (100) of training a neural network (NN) stored on a computer-readable storage medium (10) to classify objects (A-E) in a bulk flow, the method (100) comprising the steps of: providing (101) input image data (50*) depicting objects (A*-E*) to be classified, which input image data (50*) is captured by means of an input imaging sensor (30, 30a-30e) of a first sensor technology design; providing (102) auxiliary image data (50**), which auxiliary image data (50**) is captured by means of an auxiliary imaging sensor (40, 40a-40e) of a second sensor technology design, and which auxiliary image data (50**) depicts said or similar objects (A**-E**) which are classified in accordance with a predetermined classifying scheme; by means of a processing unit (20), train (103) the neural network (NN) stored on the computer-readable storage medium (10) to classify the depicted objects (A*-E*) in the input image data (50*) based on classifications of depicted objects (A**-E**) in the auxiliary image data (50**), wherein the depicted objects (A*-E*) in the input image data (50*) correspond to objects (A-E) in a bulk flow, and wherein the second sensor technology design is different from the first sensor technology design.