Semi‐ and unsupervised learning constitute two pivotal paradigms for extracting structure and meaning from data when explicit labels are sparse or entirely absent. In semi‐supervised learning, a small ...

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.

What Is Semi-Supervised Learning? Semi-supervised learning is a powerful machine learning technique that combines the strengths of supervised and unsupervised learning. It leverages a small amount of ...

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 ...

Tomographic Particle Image Velocimetry (Tomo-PIV) is a 3D particle image velocimetry technology combined with computed tomography (CT), which can realize full-field quantitative measurement of spatial ...

In a pineapple exporting factory, manual lines are usually built to screen fruits of non-ripen hitting sounds from millions of undecided fruits for long-haul transportation. However, human workers ...

A dataset for anomaly detection and localization in the 5-GHz ISM band was developed. The normal signals consisted of real-world Wi-Fi signals, whereas the anomalous signals were artificially added to ...