Some aspects of an embodiment of the present disclosure relate to the use of a boundary recognition loss function for training a machine learning model so as to calculate a semantic segmentation map from an input image. Some aspects of an embodiment of the present disclosure relate to a deep convolutional neural network (DCNN) for calculating a semantic segmentation map from an input image, wherein the DCNN includes a box filtering layer formed to box-filter a characteristic map calculated from the input image before supplying a box-filtered characteristic map to an atrous spatial pyramidal pooling (ASPP) layer. Some aspects of an embodiment of the present disclosure relate to a selective ASPP layer formed to increase the output of an ASPP layer in accordance with an attention characteristic map.
SYSTEM AND METHOD FOR BOUNDARY AWARE SEMANTIC SEGMENTATION