Self-supervised models generate implicit labels from unstructured data rather than relying on labeled datasets for supervisory signals. Self-supervised learning (SSL), a transformative subset of ...

Semi-supervised learning merges supervised and unsupervised methods, enhancing data analysis. This approach uses less labeled data, making it cost-effective yet precise in pattern recognition.

This article is part of our coverage of the latest in AI research. What is the next step toward bridging the gap between natural and artificial intelligence? Scientists and researchers are divided on ...

In recent articles I have looked at some of the terminology being used to describe high-level Artificial Intelligence concepts – specifically machine learning and deep learning. In this piece, I want ...

We adopted SimSiam to conduct self-supervised pretraining on two large whole-slide image CRC data sets from the United States and Australia. The SSL pretrained encoder is then used in several ...

Supervised machine learning uses labeled data to teach algorithms pattern recognition. It improves prediction accuracy in industries like finance and healthcare. Investors can gauge a company's ...