Self-supervised learning (SSL) has emerged as a powerful method for extracting meaningful representations from vast, unlabelled datasets, transforming computer vision and natural language processing.

The limited availability of labeled ECG data restricts the application of supervised deep learning methods in ECG detection. Although existing self-supervised learning approaches have been applied to ...

The accurate measurement of the green fraction (GF), a critical photosynthetic trait in crops, typically relies on RGB image analysis employing segmentation algorithms to identify green pixels within ...

Overall, the Self-Net deep learning framework is an effective and reliable approach to achieving resolution isotropy of volumetric microscopy. It can be anticipated that Self-Net will be useful in a ...

Deep learning high-content imaging is rapidly reshaping image-based screening in the modern laboratory environment. As high-content screening (HCS) generates increasingly large and complex datasets, ...