Tag: CNN-Transformer

Researchers at the University of Regina and collaborators have developed a computer vision framework that estimates the width of fertilizer ...

A hybrid CNN-Transformer model identified tectonically deformed coal from well logs in the Huainan coalfield with 87.52 percent cross-validation accuracy, ...

A hybrid CNN-Transformer framework called LHCT-Net reached 98.55% accuracy for melanoma-versus-non-melanoma classification on the 25,331-image ISIC 2019 dataset.

A new AI framework first localizes individual disease regions in real-field leaf photographs and then applies similarity-aware contrastive learning, reaching ...

A computational study of GTZAN and ASAP audio datasets reports that the CCTAF-MSR CNN–Transformer model reached 86.40% precision, 88.99% recall ...

A new CNN-Transformer model detects depression from Chinese speech with over 95% precision by fusing wavelet-based spectral features with hybrid ...