Multi-label learning addresses classification tasks in which each instance may be associated with multiple, non-exclusive labels. Unlike traditional single-label approaches, multi-label methods must ...

Multi-label image classification extends the traditional single-label paradigm by assigning multiple simultaneous labels to each image, reflecting the complexity of real-world scenes. This task poses ...