Nature

Dimensionality reduction for images of IoT using machine learning

Sensors, wearables, mobile devices, and other Internet of Things (IoT) devices are becoming increasingly integrated into all aspects of our lives. They are capable of gathering enormous amounts of ...
Pusula

Building a Modern Masked Autoencoder (MAE) from Scratch in PyTorch

Deep learning has a data problem. While supervised learning has given us incredible breakthroughs in computer vision, annotating millions of images by hand is expensive, slow, and non-scalable. Enter ...
Nature

Deep learning assisted XRF spectra classification

EDXRF spectrometry is a well-established and often-used analytical technique in examining materials from which cultural heritage objects are made. The analytical results are traditionally subjected to ...
Visual Studio Magazine

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 of a dataset that has fewer columns. Imagine that you have a dataset that has many ...
Medical Device and Diagnostic Industry (MD+DI)

The AI Era: How Deep Learning is Overcoming Data Scarcity in Medical Imaging

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...