AI Medical Compendium Topic

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

Models, Neurological

Showing 111 to 120 of 1111 articles

Clear Filters

Memristive Circuit Implementation of Caenorhabditis Elegans Mechanism for Neuromorphic Computing.

IEEE transactions on neural networks and learning systems Sep 3, 2024
To overcome the energy efficiency bottleneck of the von Neumann architecture and scaling limit of silicon transistors, an emerging but promising solution is neuromorphic computing, a new computing paradigm inspired by how biological neural networks h...
Interneurons Models, Neurological Motor Neurons Robotics Neurons Neural Networks, Computer Locomotion Animals Nerve Net Caenorhabditis elegans
View on PubMed DOI

Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey.

IEEE transactions on neural networks and learning systems Sep 3, 2024
With the adoption of smart systems, artificial neural networks (ANNs) have become ubiquitous. Conventional ANN implementations have high energy consumption, limiting their use in embedded and mobile applications. Spiking neural networks (SNNs) mimic ...
Neural Networks, Computer Machine Learning Algorithms Humans Models, Neurological Action Potentials Neurons Animals Deep Learning Image Processing, Computer-Assisted
View on PubMed DOI

Delay learning based on temporal coding in Spiking Neural Networks.

Neural networks : the official journal of the International Neural Network Society Aug 31, 2024
Spiking Neural Networks (SNNs) hold great potential for mimicking the brain's efficient processing of information. Although biological evidence suggests that precise spike timing is crucial for effective information encoding, contemporary SNN researc...
Algorithms Humans Learning Neural Networks, Computer Models, Neurological Time Factors Action Potentials Neurons
View on PubMed DOI

A Federated Learning Protocol for Spiking Neural Membrane Systems.

International journal of neural systems Aug 30, 2024
Although deep learning models have shown promising results in solving problems related to image recognition or natural language processing, they do not match how the biological brain works. Some of the differences include the amount of energy consume...
Humans Neural Networks, Computer Machine Learning Algorithms Deep Learning Models, Neurological Action Potentials Neurons
View on PubMed DOI

Asynchronous Numerical Spiking Neural Membrane Systems with Local Synchronization.

International journal of neural systems Aug 23, 2024
Since the spiking neural P system (SN P system) was proposed in 2006, it has become a research hotspot in the field of membrane computing. The SN P system performs computations through the encoding, processing, and transmission of spiking information...
Models, Neurological Action Potentials Neurons Computer Simulation Animals Humans Neural Networks, Computer
View on PubMed DOI

A new hybrid learning control system for robots based on spiking neural networks.

Neural networks : the official journal of the International Neural Network Society Aug 22, 2024
This paper presents a new hybrid learning and control method that can tune their parameters based on reinforcement learning. In the new proposed method, nonlinear controllers are considered multi-input multi-output functions and then the functions ar...
Robotics Neurons Nonlinear Dynamics Reinforcement, Psychology Neuronal Plasticity Models, Neurological Action Potentials Algorithms Feedback Neural Networks, Computer Machine Learning
View on PubMed DOI

SNN-BERT: Training-efficient Spiking Neural Networks for energy-efficient BERT.

Neural networks : the official journal of the International Neural Network Society Aug 20, 2024
Spiking Neural Networks (SNNs) are naturally suited to process sequence tasks such as NLP with low power, due to its brain-inspired spatio-temporal dynamics and spike-driven nature. Current SNNs employ "repeat coding" that re-enter all input tokens a...
Deep Learning Models, Neurological Action Potentials Humans Neurons Neural Networks, Computer Algorithms
View on PubMed DOI

Subject-independent auditory spatial attention detection based on brain topology modeling and feature distribution alignment.

Hearing research Aug 14, 2024
Auditory spatial attention detection (ASAD) seeks to determine which speaker in a surround sound field a listener is focusing on based on the one's brain biosignals. Although existing studies have achieved ASAD from a single-trial electroencephalogra...
Signal Processing, Computer-Assisted Humans Attention Auditory Perception Neural Networks, Computer Acoustic Stimulation Models, Neurological Auditory Pathways Brain Brain Waves Electroencephalography Sound Localization
View on PubMed DOI

Multi-focus image fusion with parameter adaptive dual channel dynamic threshold neural P systems.

Neural networks : the official journal of the International Neural Network Society Aug 8, 2024
Multi-focus image fusion (MFIF) is an important technique that aims to combine the focused regions of multiple source images into a fully clear image. Decision-map methods are widely used in MFIF to maximize the preservation of information from the s...
Image Processing, Computer-Assisted Models, Neurological Action Potentials Algorithms Animals Neurons Humans Neural Networks, Computer
View on PubMed DOI

Signatures of Bayesian inference emerge from energy-efficient synapses.

eLife Aug 6, 2024
Biological synaptic transmission is unreliable, and this unreliability likely degrades neural circuit performance. While there are biophysical mechanisms that can increase reliability, for instance by increasing vesicle release probability, these mec...
Models, Neurological Bayes Theorem Neurons Neural Networks, Computer Animals Synaptic Transmission Energy Metabolism Synapses
View on PubMed DOI
Popular Topics
Recent Journals