As annotations from human graders are available, supervised learning techniques can be used to estimate the magnitude of appropriate thresholds.

(These semi-supervised learning techniques reduced the amount of labeled data needed to achieve the same accuracy improvement by 40 times!) ...

Supervised learning algorithms extract general principles from observed examples guided by a specific prediction objective.

Cardiovascular diseases are a leading health concern in Hong Kong, prompting many to undergo regular heart check-ups for their early detection and management. Echocardiography, a key diagnostic ...

Semi-supervised learning combines supervised and unsupervised learning for efficient data analysis. This hybrid approach enhances pattern recognition from large, mixed data sets, saving time and ...

Outside of medical settings, Googlehas developed several self-supervised learning techniques to train neural networks for computer vision tasks.

Semi-supervised learning solutions are deployed here, able to access reference data when it’s available, and use unsupervised learning techniques to make “best guesses” when it comes to ...

In the 2000s, advancements in self-supervised learning techniques like autoencoders and sparse coding aimed to acquire valuable representations without explicit labels.

The key to a better Alexa is self-learning and semi-supervised learning techniques. Here's how Amazon is working to implement them.

In a new paper, artificial intelligence researchers at Google suggest a new technique that uses self-supervised learning to train deep learning models for medical imaging.