An ecologically motivated image dataset for deep learning yields better models of human vision
J Mehrer, CJ Spoerer, EC Jones… - Proceedings of the …, 2021 - National Acad Sciences
Deep neural networks provide the current best models of visual information processing in
the primate brain. Drawing on work from computer vision, the most commonly used networks …
the primate brain. Drawing on work from computer vision, the most commonly used networks …
Brain-like object recognition with high-performing shallow recurrent ANNs
Deep convolutional artificial neural networks (ANNs) are the leading class of candidate
models of the mechanisms of visual processing in the primate ventral stream. While initially …
models of the mechanisms of visual processing in the primate ventral stream. While initially …
[HTML][HTML] Individual differences among deep neural network models
Deep neural networks (DNNs) excel at visual recognition tasks and are increasingly used as
a modeling framework for neural computations in the primate brain. Just like individual …
a modeling framework for neural computations in the primate brain. Just like individual …
Cornet: Modeling the neural mechanisms of core object recognition
Deep artificial neural networks with spatially repeated processing (aka, deep convolutional
ANNs) have been established as the best class of candidate models of visual processing in …
ANNs) have been established as the best class of candidate models of visual processing in …
Harmonizing the object recognition strategies of deep neural networks with humans
T Fel, IF Rodriguez Rodriguez… - Advances in neural …, 2022 - proceedings.neurips.cc
The many successes of deep neural networks (DNNs) over the past decade have largely
been driven by computational scale rather than insights from biological intelligence. Here …
been driven by computational scale rather than insights from biological intelligence. Here …
Brain-score: Which artificial neural network for object recognition is most brain-like?
The internal representations of early deep artificial neural networks (ANNs) were found to be
remarkably similar to the internal neural representations measured experimentally in the …
remarkably similar to the internal neural representations measured experimentally in the …
Large-scale, high-resolution comparison of the core visual object recognition behavior of humans, monkeys, and state-of-the-art deep artificial neural networks
Primates, including humans, can typically recognize objects in visual images at a glance
despite naturally occurring identity-preserving image transformations (eg, changes in …
despite naturally occurring identity-preserving image transformations (eg, changes in …
Texture-like representation of objects in human visual cortex
AV Jagadeesh, JL Gardner - Proceedings of the National …, 2022 - National Acad Sciences
The human visual ability to recognize objects and scenes is widely thought to rely on
representations in category-selective regions of the visual cortex. These representations …
representations in category-selective regions of the visual cortex. These representations …
Task-driven convolutional recurrent models of the visual system
Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object
classification tasks such as ImageNet. Further, they are quantitatively accurate models of …
classification tasks such as ImageNet. Further, they are quantitatively accurate models of …
Visual object recognition: Do we (finally) know more now than we did?
I Gauthier, MJ Tarr - Annual review of vision science, 2016 - annualreviews.org
How do we recognize objects despite changes in their appearance? The past three decades
have been witness to intense debates regarding both whether objects are encoded …
have been witness to intense debates regarding both whether objects are encoded …