Tag: deep learning

A unified taxonomy of long-term forecasting models shows that channel-independent designs excel on simple benchmarks while channel-dependent designs gain an ...

A compact deep-learning model called minisplice learns splice signals across vertebrates and insects and, when integrated into minimap2 and miniprot, ...

VISTA-Edge weights seven rotating polarizer views pixel by pixel to outperform existing baselines on petrographic thin-section edge segmentation.

A fine-tuned VGG16 network achieved 84.0 percent subset accuracy and an 85.2 percent micro-averaged F1-score on a held-out test set ...

Taxonova, a deep learning classifier, achieved high species-level accuracy across short- and long-read ribosomal amplicons in benchmark tests.

Researchers report a deep learning framework called ShearFocusNet that denoises low-dose CT images by combining Shearlet-based directional perception with spatial ...

A new hybrid CNN-Transformer model called AGDE-Net accurately segments tumor cores and peritumoral edema in adult glioma MRI while keeping ...

A class-adaptive ensemble of three neural networks classifies brain tumors in MRI scans with 99.39 percent benchmark accuracy, validated by ...

A multimodal deep learning framework combining CT radiomics, clinical variables, and EGFR status predicted growth trends of pulmonary ground-glass nodules ...

A new few-shot learning framework called scCAPReSE detects large-scale genomic rearrangements in single-cell Hi-C data using pre-trained image model representations, ...