ReAlnet: Achieving More Human Brain-Like Vision via Human Neural Representational Alignment

Despite the remarkable strides made in artificial intelligence, current object recognition models still lag behind in emulating the mechanism of visual information processing in human brains. Recent studies have highlighted the potential of using neural data to mimic brain processing; however, these often reply on invasive neural recordings from non-human subjects, leaving a critical gap in our understanding of human visual perception and the development of more human brain-like vision models. Addressing this gap, we present, for the first time, …

alignment artificial artificial intelligence brain brains cs.cv cs.lg cs.ne current data human information intelligence processing q-bio.nc recognition studies via vision visual