Tag: Few-shot learning

A target-domain augmentation and class-wise alignment framework enhances few-shot cross-condition bearing fault diagnosis, achieving up to 97.58 percent accuracy in ...

Researchers developed a lightweight convolutional network combined with modified Reptile meta-learning to accurately recognize sports actions from scarce video samples.

A new meta-learning framework improves concrete strength prediction accuracy and interpretability using limited data.

A decoupled few-shot segmentation model improves edge detail recovery and achieves higher Dice scores across three medical imaging benchmarks.

Researchers have developed a dual-pathway computational framework that combines molecular graphs, biological knowledge networks, and semantic descriptions to predict rare ...

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, ...

Researchers classified 1440 company webpages into five business-relevant categories and found that a few-shot large language model outperformed conventional machine ...

An improved Siamese neural network trained with metric learning identified coarse aggregate clustering in fresh high arch dam concrete with ...

A new framework called TinyRoute combines TinyML, reinforcement learning, and few-shot learning to achieve adaptive routing and zero-day attack detection ...

A new framework called TRRN re-indexes and filters web-retrieved images against few-shot class anchors, lifting accuracy across six benchmark settings ...