A fault detection method for power conversion circuits using thermal images and a convolutional autoencoder is presented. The autoencoder is trained on thermal images captured from a commercial power ...

Google has reportedly initiated the TorchTPU project to enhance support for the PyTorch machine learning framework on its tensor processing units (TPUs), aiming to challenge the software dominance of ...

Google's TorchTPU aims to enhance TPU compatibility with PyTorch Google seeks to help AI developers reduce reliance on Nvidia's CUDA ecosystem TorchTPU initiative is part of Google's plan to attract ...

This project implements ResNet-50, a deep convolutional neural network with 50 layers that uses residual connections to enable training of very deep networks. The architecture includes identity ...

Abstract: We introduce a new convolutional autoencoder architecture for user modeling and recommendation tasks with several improvements over the state of the art. First, our model has the flexibility ...

SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.

AI is being rapidly adopted in edge computing. As a result, it is increasingly important to deploy machine learning models on Arm edge devices. Arm-based processors are common in embedded systems ...

When Microsoft launched its Copilot+ PC range almost a year ago, it announced that it would deliver the Copilot Runtime, a set of tools to help developers take advantage of the devices’ built-in AI ...