AIMC Topic: Neural Networks, Computer

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Applications of artificial intelligence in dementia.

Geriatrics & gerontology international
The recent evolution of artificial intelligence (AI) can be considered life-changing. In particular, there is great interest in emerging hot topics in AI such as image classification and natural language processing. Our world has been revolutionized ...

Learning a robust foundation model against clean-label data poisoning attacks at downstream tasks.

Neural networks : the official journal of the International Neural Network Society
In the transfer learning paradigm, models that are pre-trained on large datasets are used as the foundation models for various downstream tasks. However, this paradigm exposes downstream practitioners to data poisoning threats, as attackers can injec...

ConTraNet: A hybrid network for improving the classification of EEG and EMG signals with limited training data.

Computers in biology and medicine
OBJECTIVE: Bio-Signals such as electroencephalography (EEG) and electromyography (EMG) are widely used for the rehabilitation of physically disabled people and for the characterization of cognitive impairments. Successful decoding of these bio-signal...

A bi-functional three-terminal memristor applicable as an artificial synapse and neuron.

Nanoscale
Due to their significant resemblance to the biological brain, spiking neural networks (SNNs) show promise in handling spatiotemporal information with high time and energy efficiency. Two-terminal memristors have the capability to achieve both synapti...

Towards accelerating model parallelism in distributed deep learning systems.

PloS one
Modern deep neural networks cannot be often trained on a single GPU due to large model size and large data size. Model parallelism splits a model for multiple GPUs, but making it scalable and seamless is challenging due to different information shari...

AdaSAM: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Sharpness aware minimization (SAM) optimizer has been extensively explored as it can generalize better for training deep neural networks via introducing extra perturbation steps to flatten the landscape of deep learning models. Integrating SAM with a...

Artificial Intelligence ECG Analysis in Patients with Short QT Syndrome to Predict Life-Threatening Arrhythmic Events.

Sensors (Basel, Switzerland)
Short QT syndrome (SQTS) is an inherited cardiac ion-channel disease related to an increased risk of sudden cardiac death (SCD) in young and otherwise healthy individuals. SCD is often the first clinical presentation in patients with SQTS. However, a...

Bridging Neuroscience and Robotics: Spiking Neural Networks in Action.

Sensors (Basel, Switzerland)
Robots are becoming increasingly sophisticated in the execution of complex tasks. However, an area that requires development is the ability to act in dynamically changing environments. To advance this, developments have turned towards understanding t...

Deep-Learning-Based Mixture Identification for Nuclear Magnetic Resonance Spectroscopy Applied to Plant Flavors.

Molecules (Basel, Switzerland)
Nuclear magnetic resonance (NMR) is a crucial technique for analyzing mixtures consisting of small molecules, providing non-destructive, fast, reproducible, and unbiased benefits. However, it is challenging to perform mixture identification because o...

Event-triggered impulsive quasi-synchronization for BAM neural networks with reliable redundant channel.

Neural networks : the official journal of the International Neural Network Society
This work addresses the quasi-synchronization of delay master-slave BAM neural networks. To improve the utilization of channel bandwidth, a dynamic event-triggered impulsive mechanism is employed, in which data is transmitted only when a preset event...