Interpretable deep learning network significantly improves tropical cyclone intensity forecast accuracy

Predicting tropical cyclones (TCs) accurately is crucial for disaster mitigation and public safety. Although the forecasting accuracy of TC tracks has improved substantially in recent decades, ...
IEEE

Jellyfish Species Identification: A CNN Based Artificial Neural Network Approach

Abstract: Jellyfish are a diverse category of marine gelatinous organisms that are vital to the balance of aquatic ecosystems, yet they present notable difficulties for biodiversity preservation and ...

How hair and skin characteristics affect brain imaging: Making fNIRS research more inclusive

Functional near-infrared spectroscopy (fNIRS) is a promising non-invasive neuroimaging technique that works by detecting ...
IEEE

Open-Set Domain Adaptation for Hyperspectral Image Classification Based on Reconstruction Discrepancy and Feature Alignment

Abstract: For hyperspectral image classification, domain adaptation algorithms often assume that the source domain and target domain share the same label space, and thus, classify all samples in the ...