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Recognizing objects from camera images is an important field for researching smart ships and intelligent navigation. In sea transportation, navigation marks indicating the features of navigational environments (e.g. channels, special areas, wrecks, etc.) are focused in this paper. A fine-grained classification model named RMA (ResNet-Multiscale-Attention) based on deep learning is proposed to analyse the subtle and local differences among navigation mark types for the recognition of navigationdoi:10.1109/access.2020.2973856 fatcat:x3kzhbnndzgefha5ixqwv5nkte