Perceptual Understanding
Perceptual understanding research aims to model how humans and machines interpret sensory information, focusing on bridging the gap between objective stimuli and subjective experience. Current efforts leverage deep learning, particularly neural networks and diffusion models, to predict perceptual attributes (e.g., gloss, sound quality, cognitive complexity of language) from various inputs (images, audio, text). This work is significant for improving applications like image and audio processing, human-computer interaction, and even medical diagnosis by enabling more accurate and efficient analysis of sensory data and its impact on human perception and cognition.
Papers
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