Method and system of multi-modality classification using augmented data

摘要

A method and system of multi-modality classification using augmented data is disclosed. The method includes generating a pattern for each of a plurality of augmented data associated with each of a plurality of object classes, based on at least one modality associated with each of the plurality of objects classes using a Long Term Short Memory (LSTM) classifier and a Layer-wise Relevance Propagation (LRP). The method further includes classifying an input image into a first object class of the plurality of object classes based on one or more objects within the input image using a Convolution Neural Network (CNN). The method further includes re-classifying the input image into one of the first object class or a second object class of the plurality of object classes when the accuracy of classification by the CNN into the first object class is below a matching threshold.