Degrees of algorithmic equivalence between the brain and its DNN models
Deep neural networks (DNNs) have become powerful and increasingly ubiquitous tools to
model human cognition, and often produce similar behaviors. For example, with their …
model human cognition, and often produce similar behaviors. For example, with their …
Advancing naturalistic affective science with deep learning
People express their own emotions and perceive others' emotions via a variety of channels,
including facial movements, body gestures, vocal prosody, and language. Studying these …
including facial movements, body gestures, vocal prosody, and language. Studying these …
Pre-frontal cortex guides dimension-reducing transformations in the occipito-ventral pathway for categorization behaviors
To interpret our surroundings, the brain uses a visual categorization process. Current
theories and models suggest that this process comprises a hierarchy of different …
theories and models suggest that this process comprises a hierarchy of different …
Utilization of random forest and deep learning neural network for predicting factors affecting perceived usability of a COVID-19 contact tracing mobile application in …
The continuous rise of the COVID-19 Omicron cases despite the vaccination program
available has been progressing worldwide. To mitigate the COVID-19 contraction, different …
available has been progressing worldwide. To mitigate the COVID-19 contraction, different …
Utilization of random forest classifier and artificial neural network for predicting factors influencing the perceived usability of COVID-19 contact tracing “Morchana” in …
With the constant mutation of COVID-19 variants, the need to reduce the spread should be
explored. MorChana is a mobile application utilized in Thailand to help mitigate the spread …
explored. MorChana is a mobile application utilized in Thailand to help mitigate the spread …
Face dissimilarity judgments are predicted by representational distance in morphable and image-computable models
Human vision is attuned to the subtle differences between individual faces. Yet we lack a
quantitative way of predicting how similar two face images look and whether they appear to …
quantitative way of predicting how similar two face images look and whether they appear to …
[HTML][HTML] A narrow band of image dimensions is critical for face recognition
A key challenge in human and computer face recognition is to differentiate information that is
diagnostic for identity from other sources of image variation. Here, we used a combined …
diagnostic for identity from other sources of image variation. Here, we used a combined …
Behavioral signatures of face perception emerge in deep neural networks optimized for face recognition
K Dobs, J Yuan, J Martinez… - Proceedings of the …, 2023 - National Acad Sciences
Human face recognition is highly accurate and exhibits a number of distinctive and well-
documented behavioral “signatures” such as the use of a characteristic representational …
documented behavioral “signatures” such as the use of a characteristic representational …
Modeling naturalistic face processing in humans with deep convolutional neural networks
Deep convolutional neural networks (DCNNs) trained for face identification can rival and
even exceed human-level performance. The ways in which the internal face representations …
even exceed human-level performance. The ways in which the internal face representations …
Understanding the evolution of a de novo molecule generator via characteristic functional group monitoring
ABSTRACT Recently, artificial intelligence (AI)-enabled de novo molecular generators
(DNMGs) have automated molecular design based on data-driven or simulation-based …
(DNMGs) have automated molecular design based on data-driven or simulation-based …