Concept Based Classification

Concept-based Classification is a subtask in the field of computer vision that focuses on classifying images using human-interpretable concepts. This task aims to enhance the transparency and interpretability of models by identifying specific concepts such as objects, scenes, and attributes, thereby increasing user trust in model decisions. In practical applications, this classification method can better support precise needs in areas like medical diagnosis, intelligent surveillance, and content moderation.