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[HTML][HTML] Using artificial neural networks to ask 'why'questions of minds and brains
Neuroscientists have long characterized the properties and functions of the nervous system,
and are increasingly succeeding in answering how brains perform the tasks they do. But the …
and are increasingly succeeding in answering how brains perform the tasks they do. But the …
Digital twin studies for reverse engineering the origins of visual intelligence
What are the core learning algorithms in brains? Nativists propose that intelligence emerges
from innate domain-specific knowledge systems, whereas empiricists propose that …
from innate domain-specific knowledge systems, whereas empiricists propose that …
Visual anagrams: Generating multi-view optical illusions with diffusion models
We address the problem of synthesizing multi-view optical illusions: images that change
appearance upon a transformation such as a flip or rotation. We propose a simple zero-shot …
appearance upon a transformation such as a flip or rotation. We propose a simple zero-shot …
Impact of colour on robustness of deep neural networks
Convolutional neural networks have become the most widely used tool for computer vision
applications like image classification, segmentation, object localization etc. Recent studies …
applications like image classification, segmentation, object localization etc. Recent studies …
IllusionVQA: A challenging optical illusion dataset for vision language models
HS Shahgir, KS Sayeed, A Bhattacharjee… - ar** biological and artificial intelligences
Making inferences from behaviour to cognition is problematic due to a many-to-one map**
problem, in which any one behaviour can be generated by multiple possible cognitive …
problem, in which any one behaviour can be generated by multiple possible cognitive …