eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...

Predictive Modeling: Techniques, Uses, and Key Takeaways

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an ...
IEEE

Spatial-Spectral Contrastive Graph Neural Network for Few-Shot Hyperspectral Image Classification

Abstract: Graph Neural Networks (GNNs) have emerged as a promising solution for few-shot hyperspectral image (HSI) classification. However, existing GNN-based approaches face critical limitations in ...
IEEE

Evolutionary Neural Architecture Search for Remote Sensing Image Classification

Abstract: Remote sensing scene classification is a vital task in remote sensing image analysis with significant application potential. In recent years, convolutional neural network (CNN)-based methods ...
CNN

Data centers powering the AI boom are pitting states against each other

Just before her victory this fall, New Jersey Gov.-elect Mikie Sherrill jabbed at nearby Virginia, which also had a governor’s race, over its booming data center market. “Right now, we need to produce ...
Frontiers

Hyperspectral inversion model of ginkgo leaf yield prediction based on machine learning

Introduction: The yield of ginkgo biloba leaves serves as a critical indicator for assessing their growth and health status. However, current assessment methods primarily rely on manual harvesting and ...