The precise classification of remote sensing images is crucial for applications such as disaster monitoring, land use planning, and national security. Since effective classification models often rely on large, well-annotated datasets, the remote sensing field faces two persistent challenges: the limited availability of...
Dan Song, Ning Liu, Yu-Ting Ling et al.· IEEE Transactions on Geoscie...· 0 citations
Drug-drug interactions (DDIs) represent a critical challenge in drug development and clinical practice, as they can lead to severe adverse effects, including toxicity and reduced therapeutic efficacy. Deep learning methods have shown promise in large-scale, rapid DDI prediction; however, current approaches suffer from...
A novel cascaded deep learning framework that combines domain expertise with data‐driven refinement for typhoon intensity prediction is proposed, providing comprehensive modelling of typhoon evolution dynamics.
Zhengya Sun, Bojie Fan, Bo Yin et al.· CAAI Transactions on Intelli...· 0 citations
iSCALE serves as an effective in silico tool for large-scale protein-RNA binding ΔΔG prediction, which pushes the border of understanding in mutation-induced pathological outcomes.
