Tag: convolutional neural networks

Physicists have developed lightweight, compound-scaled convolutional neural networks that combine jet images with global substructure observables to achieve high-accuracy top-quark ...

Researchers developed EARS-Net, a hybrid deep learning model combining generative oversampling, dual attention, and transformers that achieves superior facial expression ...

A comprehensive systematic review of literature from 2018 to 2025 reveals that while deep learning achieves high benchmark accuracy for ...

A systematic review of 62 studies reveals that deep learning models effectively monitor marine biodiversity across distinct aquatic mediums despite ...

A systematic audit of a widely used ultrasound archive reveals that top-performing federated deep learning models classify polycystic ovary syndrome ...

Researchers developed AirMixer, a channel-independent neural network that improves long-term air quality forecasting across eleven benchmark datasets.

A comparative study demonstrates that hybrid machine learning classifiers match end-to-end deep learning on saturated steel defect benchmarks but diverge ...

Researchers developed a glowworm swarm-optimized variational autoencoder that combines visual features and structured spatial data to distinguish authentic interior scenes ...

Researchers have developed FTNB-Net, a frequency-aware neural network combining Taylor Neighbor Baikal loss with transformer and convolutional features to detect ...

A comprehensive review of a decade of road scene parsing reveals that while drivable surface detection is well-solved, detecting road ...