Abstract: Accurate fault classification and location are critical to ensure the reliability and resilience of large-scale power distribution systems (PDSs). The existing data-driven works in this area ...

What if technology could bridge the gap between spoken language and sign language, empowering millions of people to communicate more seamlessly? With advancements in deep learning, this vision is no ...

Hi @bilalsal @NarineK @sarahtranfb @vivekmig @aobo-y, First of all, thank you for the amazing work on Captum! I'm currently exploring the capabilities of Captum for analyzing a convolutional neural ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Senyo Simpson discusses how Rust's core ...

Abstract: Spectral unmixing is an important technique in remote sensing for analyzing hyperspectral images to identify endmembers and estimate fractional abundance maps. Over the past few decades, ...

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...

A comprehensive PyTorch-based system for predicting cryptocurrency prices using a state-of-the-art Spatial-Temporal Graph Neural Network (ST-GNN) model. This advanced implementation integrates ...

The precise segmentation of the optic cup (OC) and the optic disc (OD) is important for glaucoma screening. In recent years, medical image segmentation based on convolutional neural networks (CNN) has ...