Tag: multi-task learning

A new knowledge distillation framework compresses three large neural networks into a 6.97 MB model that classifies rice diseases, localizes ...

Researchers have developed a hierarchical temporal graph network that predicts student academic outcomes with high accuracy while using gradient-based attribution ...

Researchers at Ningxia University have developed SPMTNet, a structural-prior-guided multi-task AI framework that recognizes Tangut characters by learning their internal ...

A multi-task deep learning model that fuses pretreatment MRI and whole slide pathology images outperformed standard staging in predicting chemotherapy ...

A new multi-task deep learning framework called ApexTransNet segments apical periodontitis lesions and grades radiographic severity on periapical radiographs with ...

A controlled head-to-head study shows Vision Transformers beat convolutional networks on real X-ray diffraction data once fine-tuned, while CNNs remain ...

Researchers at Keio University have developed H-PLE, a hierarchical multi-task recommendation framework that stabilizes expert routing and improves prediction of ...

A new multi-task AI framework called TAZD-Net segments thyroid nodules and predicts malignancy by explicitly reasoning over the lesion, its ...

A new multi-scale deep learning framework called Rain-PostEFNet substantially improves numerical weather prediction rainfall forecasts, with the largest gains in ...

A deep learning model trained on nearly 30,000 retinal images predicts biological age from eye scans, revealing that smoking, diabetes, ...