AIMC Topic: Neural Networks, Computer

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Lightweight and efficient skeleton-based sports activity recognition with ASTM-Net.

PloS one
Human Activity Recognition (HAR) plays a pivotal role in video understanding, with applications ranging from surveillance to virtual reality. Skeletal data has emerged as a robust modality for HAR, overcoming challenges such as noisy backgrounds and ...

Edges are all you need: Potential of medical time series analysis on complete blood count data with graph neural networks.

PloS one
PURPOSE: Machine learning is a powerful tool to develop algorithms for clinical diagnosis. However, standard machine learning algorithms are not perfectly suited for clinical data since the data are interconnected and may contain time series. As show...

Simulation of emitter discharge along drip laterals under drip fertigation system using artificial neural network.

PloS one
Simulation of emitter discharge under a drip fertigation system is important for capturing the variation in water and nutrient distribution to crops. This is important for an effective design and irrigation management for agricultural crops. Moreover...

Design of an evolutionary model for international trade settlement based on genetic algorithm and fuzzy neural network.

PloS one
Accurate risk assessment in international trade settlement has become increasingly critical as global financial transactions grow in scale and complexity. This study proposes a hybrid model-Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)-to...

Rapid forensic differentiation of human and animal bones using handheld near-infrared spectroscopy and deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The forensic differentiation of human and animal bones is critical in various investigations, mainly when dealing with fragmented skeletal remains. This study explores the practical application of handheld near-infrared spectroscopy combined with art...

Low-cost machine learning-integrated optical spectrophotometer for non-destructive color and shelf-life analysis: A study on sliced bread.

Food chemistry
Monitoring physical color and spectral signatures is essential for the early detection of spoilage in perishable food products. This study introduces a cost-effective, Machine Learning (ML)-enabled spectrophotometer for nondestructive spoilage detect...

Harnessing deep learning for fusion-based heavy metal contamination index prediction in groundwater.

Journal of contaminant hydrology
Groundwater contamination by heavy metals presents a major environmental threat with serious implications for public health and resource sustainability. This study proposes a novel deep learning-based data fusion framework to predict heavy metal cont...

Groundwater health probability risk prediction through oral intake using advanced optimization methods.

Journal of contaminant hydrology
Examining the cancer risk associated with oral groundwater (GW) intake is crucial, particularly in regions heavily reliant on GW for human consumption and agriculture. The study was based on real field investigations and controlled laboratory experim...

Filter-type neural network-based counter-pulsation control in pulsatile ECMO: improving heartbeat-pulse discrimination and synchronization accuracy.

Biomedical engineering online
Implementing counter-pulsation (CP) control in pulsatile extracorporeal membrane oxygenator (p-ECMO) systems offers a refined approach to mitigate risks commonly associated with conventional ECMOs. To attain CP between the p-ECMO and heart, accurate ...

Multi-task genomic prediction using gated residual variable selection neural networks.

BMC bioinformatics
BACKGROUND: The recent development of high-throughput sequencing techniques provide massive data that can be used in genome-wide prediction (GWP). Although GWP is effective on its own, the incorporation of traditional polygenic pedigree information i...