A hierarchical sampling based triplet network for fine-grained image classification

•Building layered ontology for 3 different databases to guide the layered knowledge of the network.•Hierarchical sampling method for mining more effective hard triplets to get better performance.•Acquisition of more discriminative deep feature by building hierarchical structure with semantic knowledge.•Combination of hierarchical structure and triplet loss to construct a layered Triplet loss function.