Visual auto-encoders for flawless reconstruction of visual data for the CloudGripper V1 robot environment - Releases · GiacomoBillo/cloudgripper-visual-autoencoder ...

This paper studies the computational offloading of CNN inference in dynamic multi-access edge computing (MEC) networks. To address the uncertainties in communication time and edge servers’ available ...

Visual Servoing in Autoencoder Latent Space Abstract: Visual servoing (VS) is a common way in robotics to control a robot motion usinginformation acquired by a camera. This approach requires to ...

The demo program presented in this article uses image data, but the autoencoder anomaly detection technique can work with any type of data. The demo begins by creating a Dataset object that stores the ...

This repository contains the official implementation (in PyTorch) of the Contrastive Audio-Visual Masked Autoencoder (CAV-MAE) proposed in the ICLR 2023 paper Contrastive Audio-Visual Masked ...

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

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 ...

The overall structure of the PyTorch autoencoder anomaly detection demo program, with a few minor edits to save space, is shown in Listing 3. I prefer to indent my Python programs using two spaces ...