Tag: Few-shot learning

Researchers have combined prototypical few-shot learning with adversarial training to build an IoT intrusion detection system that learns attacks from ...

Researchers in China built a prototypical network-based few-shot learning framework that reproduces expert consensus severity stratification in newly diagnosed Crohn's ...

Researchers have introduced HGA-Net, a hypergraph-based adapter that connects related examples within each mini-batch and achieves near-perfect fine-grained recognition with ...

A new federated learning framework called FedCAMP-IDS detects known and zero-day cyberattacks across heterogeneous IoT networks with up to 99.16 ...

Researchers at Yonsei University have developed a prompt-tuning method that lets the vision-language model CLIP detect and localize industrial defects ...

Researchers have developed DiffProNet, a framework that applies diffusion-inspired feature-space denoising to prototypical networks, achieving competitive few-shot fine-grained image classification ...

Researchers have unveiled a meta-learning model that recognizes ship types from underwater sound using only a few examples while retaining ...

Researchers in China have developed NERA-Net, a framework that prevents the early loss of spatial details in few-shot semantic segmentation ...

Researchers have reformulated knowledge tracing so large language models can assess a student's understanding from only a few answers while ...

Chinese researchers have unveiled a lightweight hierarchical deep learning framework that matches or beats state-of-the-art cross-domain few-shot learning methods while ...