The goal of the team’s study was to demonstrate the potential for deep-learning architecture to support ... class activation heat maps - which visualize pixels in images - were also generated ...

Neural architecture search is an aspect of AutoML, along with feature engineering, transfer learning, and hyperparameter optimization. It’s probably the hardest machine learning problem ...

semantic segmentation (credit: codebasics). The complexity of convolutional neural networks (CNN), the deep learning architecture commonly used in computer vision tasks, is usually measured in ...

To address this issue, researchers at ETH Zurich have unveiled a revised version of the transformer, the deep learning architecture underlying language models. The new design reduces the size of ...