Turning tabular data into ‘pseudo-notes’ that mirror clinical documentation allows AI models to analyze patient information ...

In this TechRepublic exclusive, a COO states that successful AI initiatives must have the right unstructured data at the ...

Explore how Sparc3D transforms 2D images into detailed 3D models with AI-powered efficiency and precision. Discover more.

Google retires seven structured data features including Book Actions, Course Info, and Claim Review to streamline search results. Rankings unaffected.

Keywords: multi-source data fusion, deep convolutional autoencoder, slope displacement, rainfall, health monitoring Citation: Han N, Miao W, Li M, Mohamad Ismail MA, Hu Q, Duan L and Tang J (2025) ...

3.1 2D convolutional autoencoder An autoencoder (AE) is a neural network model primarily used for unsupervised learning. It achieves dimensionality reduction and feature extraction by learning to ...

Many search engines rely on structured data to enhance user experiences – and this trend will likely intensify in 2025. For this reason, structured data is no longer a “nice-to-have” but an ...

The Data Science Lab Data Dimensionality Reduction Using a Neural Autoencoder with C# Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on creating an approximation ...

Data-driven soft sensors play an important role in practical processes and have been widely applied. They provide real-time prediction of quality variables and then guide production and improve ...