Tag: multi-task learning

Researchers at the Vellore Institute of Technology developed three hybrid deep learning models combining convolutional networks, transformers, and clinical metadata ...

A multi-task deep learning system reads infant hip ultrasounds, segments seven anatomical structures, localizes six landmarks, and measures Graf angles ...

Researchers have developed and validated an AI-driven adaptive learning system that predicts student engagement, forecasts academic achievement, and generates explainable ...

Researchers built ViTDrone, a Vision Transformer framework that simultaneously steers a drone through corridors and detects collisions while using Grad-CAM ...

A new Genome Biology study introduces Pep2Net, a platform combining a knowledge base built from 52 peptide databases with a ...

Researchers have built a holographic neural network that uses a single spatial light modulator and one beam of light to ...

A new hybrid deep learning architecture combining a fine-tuned U-Net with a time-weighted multi-task bi-directional LSTM significantly improves real-time detection ...

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 ...