A new machine-learning algorithm is able to teach itself to smell within a few minutes of training. As it learns, the system builds an artificial network that mimics the brain's olfactory system.
Findings could advance the development of deep learning networks based on real neurons that will enable them to perform more complex and more efficient learning processes.
A new AI algorithm can predict the onset of Alzheimer's disease with an accuracy of over 99% by analyzing fMRI brain scans.
Researchers discuss different current neural network models and consider the steps that need to be taken to make them more realistic, and thus more useful, as possible.
Artificial neural networks modeled on human brain connectivity can effectively perform complex cognitive tasks.
Artificial IntelligenceAutismDeep LearningFeaturedMachine LearningNeuroscienceOpen Neuroscience Articles
··3 min readArtificial neural networks help researchers uncover new clues as to why people on the autism spectrum have trouble interpreting facial expressions.
Researchers propose a novel computational framework that uses artificial intelligence technology to disentangle the relationship between perception and memory in the human brain.
Researchers created a new human brain model using machine learning-based optimization of required user profile information.
A new deep learning algorithm is superior to human experts in distinguishing between retinal ganglion cells in healthy patients and in those with glaucoma. The AI system could potentially help improve the diagnosis of both eye and brain diseases.
A new algorithm is allowing researchers to develop soft robots that are better able to collect useful information about their surroundings.
··5 min read
A new artificial neural network based on the human brain sheds light on how we process moving images.
When convolutional neural networks are trained under experimental conditions, they are deceived by the brightness and color of a visual image in similar ways to the human visual system.
