This article explains how to use a PyTorch neural autoencoder to find anomalies in a dataset. A good way to see where this article is headed is to take a look at the screenshot of a demo program in ...

Kaizen rethinks cell segmentation by mimicking brain predictions. Using an iterative machine-learning approach to refine boundaries in crowded microscopy images, it enhances accuracy in tissue studies ...

In a recent study published in Nature, researchers present retinal image foundation model (RETFound), a self-supervised learning (SSL) masked autoencoder-based foundation model for retinal images.

The main disadvantage of using a neural autoencoder is that you must fine-tune the training parameters (max epochs, learning rate, batch size) and the number of nodes in the hidden layer. [Click on ...