Eos

Comparing Machine Learning Models of Raindrop Formation

Better simulations of raindrop formation could help improve climate and weather models. This newsletter rocks. Get the most ...
Technology Networks

Deep Learning for Variant Calling: How DeepVariant and Neural Networks Are Improving Genomic Accuracy

Deep learning variant calling has transformed genomic accuracy. Discover how DeepVariant works, outperforms classical tools, ...

Measuring for gas: computer vision will "see" impending storms and turbulence

A neural network image analysis method will help track the movement of microparticles in the Earth's atmosphere and space.
IEEE

Hybrid ResNet-ViT Transfer Learning Approach for Brain Stroke Classification on Computed Tomography Images

Abstract: This study investigates the utilization of a hybrid Convolutional Neural Network (CNN) and Vision Transformer (ViT) model, employing transfer learning methods, to enhance brain stroke ...
Scientific Research Publishing

Deep Learning-Based Multi-Class Classification of Retinal Diseases from OCT Images Using Transfer Learning ()

1 Amazon Web Services, Seattle, USA. 2 Rajiv Gandhi University of Knowledge Technologies, Nuzvid, India. Optical Coherence Tomography (OCT) is a non-invasive imaging modality widely employed for ...
inforum

Besides Koi Perich, who’s leaving Gophers via the transfer portal?

The Minnesota Gophers football team has had 21 total players from its 2025 roster announce their intent to enter the transfer portal, which opened on Friday. There is one clear headliner — All-Big Ten ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...
Frontiers

Automated classification of MESSENGER plasma observations via unsupervised transfer learning

Our methodology demonstrates a proof of concept of the applicability of transfer learning for heliophysics, a machine learning technique where knowledge learned from one task is reused to perform a ...
IEEE

Bio-Inspired Fine-Tuning for Selective Transfer Learning in Image Classification

Abstract: Deep learning has significantly advanced image analysis across diverse domains but often depends on large, annotated datasets for success. Transfer learning addresses this challenge by ...