AIMC Topic: Neural Networks, Computer

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Empowering entity synonym set generation using flexible perceptual field and multi-layer contextual information.

PloS one
Automatic generation of entity synonyms plays a pivotal role in various natural language processing applications, such as search engines, question-answering systems, and taxonomy construction. Previous research on generating entity synonym sets has t...

Enhanced convolutional neural network accelerators with memory optimization for routing applications.

PloS one
Currently, Convolutional Neural Networks (CNN) accelerators find application in various digital domains, each highlighting memory utilization as a significant concern leading to system degradation. In response, our present work focuses on optimizing ...

Confidence interval forecasting model of small watershed flood based on compound recurrent neural networks and Bayesian.

PloS one
Flood forecasting exhibits rapid fluctuations, water level forecasting shows great uncertainty and inaccuracy in small watersheds, and the reliability and accuracy performance of traditional probability forecasting is often unbalanced. This study com...

Uncertainty mapping and probabilistic tractography using Simulation-based Inference in diffusion MRI: A comparison with classical Bayes.

Medical image analysis
Simulation-Based Inference (SBI) has recently emerged as a powerful framework for Bayesian inference: Neural networks are trained on simulations from a forward model, and learn to rapidly estimate posterior distributions. We here present an SBI frame...

Machine-learning guided differentiation between photoplethysmography waveforms of supraventricular and ventricular origin.

Computer methods and programs in biomedicine
BACKGROUND: It is unclear, whether photoplethysmography (PPG) waveforms from wearable devices can differentiate between supraventricular and ventricular arrhythmias. We assessed, whether a neural network-based classifier can distinguish the origin of...

Computational modelling for risk assessment of neurological disorder in diabetes using Hodgkin-Huxley model.

Computer methods and programs in biomedicine
BACKGROUND: Diabetes mellitus, characterized by chronic glucose dysregulation, significantly increases the risk of neurological disorders such as cognitive decline, seizures, and Alzheimer's disease. As neurons depend on glucose for energy, fluctuati...

Deep-learning-enabled spatial frequency domain imaging of the spatiotemporal dynamics of skin physiology.

Journal of biomedical optics
SIGNIFICANCE: Spatial frequency domain imaging (SFDI) is an emerging optical imaging modality for visualizing tissue absorption and scattering properties. This approach is promising for noninvasive wide field-of-view (FOV) monitoring of biophysiologi...

SPR-based refractive index sensor design with grated Au-ZnS for dengue detection using machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this paper, we propose a Surface Plasmon Resonance (SPR) fiber optic refractive index (RI) sensor. It consists of a multi-mode fiber (MMF) sensor with a bi-metallic nanostructure with Gold (Au) and Zinc Sulphide (ZnS) as the plasmonic sensing laye...

Differentiation of black tea according to country of origin using the μ-CTE/TD/GC-MS method combined with decision tree-optimizable neural network analysis.

Journal of the science of food and agriculture
BACKGROUND: Accurate discrimination of the country of origin of teas is critical to determine their actual commercial value, to meet consumer preferences, and to ensure compliance with labeling regulations. Therefore, in this study, we developed a ne...

SpikeCLIP: A contrastive language-image pretrained spiking neural network.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNNs) have emerged as a promising alternative to conventional Artificial Neural Networks (ANNs), demonstrating comparable performance in both visual and linguistic tasks while offering the advantage of improved energy efficie...