AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Pattern Recognition, Visual

Showing 41 to 50 of 145 articles

Clear Filters

On the robustness of skeleton detection against adversarial attacks.

Neural networks : the official journal of the International Neural Network Society
Human perception of an object's skeletal structure is particularly robust to diverse perturbations of shape. This skeleton representation possesses substantial advantages for parts-based and invariant shape encoding, which is essential for object rec...

Capturing human categorization of natural images by combining deep networks and cognitive models.

Nature communications
Human categorization is one of the most important and successful targets of cognitive modeling, with decades of model development and assessment using simple, low-dimensional artificial stimuli. However, it remains unclear how these findings relate t...

Unsupervised neural network models of the ventral visual stream.

Proceedings of the National Academy of Sciences of the United States of America
Deep neural networks currently provide the best quantitative models of the response patterns of neurons throughout the primate ventral visual stream. However, such networks have remained implausible as a model of the development of the ventral stream...

Within-category representational stability through the lens of manipulable objects.

Cortex; a journal devoted to the study of the nervous system and behavior
Our ability to recognize an object amongst many exemplars is one of our most important features, and one that putatively distinguishes humans from non-human animals and potentially from (current) computational and artificial intelligence models. We c...

The human visual system and CNNs can both support robust online translation tolerance following extreme displacements.

Journal of vision
Visual translation tolerance refers to our capacity to recognize objects over a wide range of different retinal locations. Although translation is perhaps the simplest spatial transform that the visual system needs to cope with, the extent to which t...

An ecologically motivated image dataset for deep learning yields better models of human vision.

Proceedings of the National Academy of Sciences of the United States of America
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 are pretrained on data from the ImageNet Large Scale Visual Recognition ...

Examining the Coding Strength of Object Identity and Nonidentity Features in Human Occipito-Temporal Cortex and Convolutional Neural Networks.

The Journal of neuroscience : the official journal of the Society for Neuroscience
A visual object is characterized by multiple visual features, including its identity, position and size. Despite the usefulness of identity and nonidentity features in vision and their joint coding throughout the primate ventral visual processing pat...

Qualitative similarities and differences in visual object representations between brains and deep networks.

Nature communications
Deep neural networks have revolutionized computer vision, and their object representations across layers match coarsely with visual cortical areas in the brain. However, whether these representations exhibit qualitative patterns seen in human percept...

Representational Content of Oscillatory Brain Activity during Object Recognition: Contrasting Cortical and Deep Neural Network Hierarchies.

eNeuro
Numerous theories propose a key role for brain oscillations in visual perception. Most of these theories postulate that sensory information is encoded in specific oscillatory components (e.g., power or phase) of specific frequency bands. These theori...

Temporal Encoding and Multispike Learning Framework for Efficient Recognition of Visual Patterns.

IEEE transactions on neural networks and learning systems
Biological systems under a parallel and spike-based computation endow individuals with abilities to have prompt and reliable responses to different stimuli. Spiking neural networks (SNNs) have thus been developed to emulate their efficiency and to ex...