Perceptual Concept

Perceptual concept research focuses on understanding how machines can represent and reason about concepts grounded in sensory experience, mirroring human perception. Current efforts concentrate on improving the interpretability of learned representations by analyzing contributions of perceptual components like color, shape, and texture, and on developing more efficient methods for training models to understand these concepts, particularly in low-data scenarios. This work is crucial for advancing artificial intelligence in areas such as automated driving, where reliable perception is paramount for safety, and for creating more robust and human-understandable AI systems across various applications.