Fine-Grained Image Classification

Fine-grained image classification becomes important when visual differences between classes are extremely subtle. Examples include bird species, vehicle model variants, product sub-lines, or medical lesion subtypes. The task requires sensitivity to fine detail and sometimes part-based attention mechanisms beyond general object recognition. It carries high commercial and scientific value, especially in expert systems.