AIMC Topic: Neural Networks, Computer

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Bidirectional consistency with temporal-aware for semi-supervised time series classification.

Neural networks : the official journal of the International Neural Network Society
Semi-supervised learning (SSL) has achieved significant success due to its capacity to alleviate annotation dependencies. Most existing SSL methods utilize pseudo-labeling to propagate useful supervised information for training unlabeled data. Howeve...

A Comprehensive Review of Hardware Acceleration Techniques and Convolutional Neural Networks for EEG Signals.

Sensors (Basel, Switzerland)
This paper comprehensively reviews hardware acceleration techniques and the deployment of convolutional neural networks (CNNs) for analyzing electroencephalogram (EEG) signals across various application areas, including emotion classification, motor ...

DeepPhoPred: Accurate Deep Learning Model to Predict Microbial Phosphorylation.

Proteins
Phosphorylation is a substantial posttranslational modification of proteins that refers to adding a phosphate group to the amino acid side chain after translation process in the ribosome. It is vital to coordinate cellular functions, such as regulati...

Machine learning supported single-stranded DNA sensor array for multiple foodborne pathogenic and spoilage bacteria identification in milk.

Food chemistry
Ensuring food safety through rapid and accurate detection of pathogenic bacteria in food products is a critical challenge in the food supply chain. In this study, a non-specific optical sensor array was proposed for the identification of multiple pat...

MMGCN: Multi-modal multi-view graph convolutional networks for cancer prognosis prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Accurate prognosis prediction for cancer patients plays a significant role in the formulation of treatment strategies, considerably impacting personalized medicine. Recent advancements in this field indicate that integrating...

Sampled-data synchronization for fuzzy inertial cellular neural networks and its application in secure communication.

Neural networks : the official journal of the International Neural Network Society
This paper designs the sampled-data control (SDC) scheme to delve into the synchronization problem of fuzzy inertial cellular neural networks (FICNNs). Technically, the rate at which the information or activation of cellular neuronal transmission mad...

Near-optimal deep neural network approximation for Korobov functions with respect to L and H norms.

Neural networks : the official journal of the International Neural Network Society
This paper derives the optimal rate of approximation for Korobov functions with deep neural networks in the high dimensional hypercube with respect to L-norms and H-norm. Our approximation bounds are non-asymptotic in both the width and depth of the ...

IVIM parameters mapping with artificial neural network based on mean deviation prior.

Medical physics
BACKGROUND: The diffusion and perfusion parameters derived from intravoxel incoherent motion (IVIM) imaging provide promising biomarkers for noninvasively quantifying and managing various diseases. Nevertheless, due to the distribution gap between si...

Molecular designing of potential environmentally friendly PFAS based on deep learning and generative models.

The Science of the total environment
Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are widely used across a spectrum of industrial and consumer goods. Nonetheless, their persistent nature and tendency to accumulate in biological systems pose substantial environmental and health t...

Application and innovation of artificial intelligence models in wastewater treatment.

Journal of contaminant hydrology
At present, as the problem of water shortage and pollution is growing serious, it is particularly important to understand the recycling and treatment of wastewater. Artificial intelligence (AI) technology is characterized by reliable mapping of nonli...