Deep Graph Convolutional Autoencoder with Conditional Normalizing Flow for Power Distribution Systems Fault Classification and Location Abstract: Accurate fault classification and location are ...

Learn to build a real-time sign language detection system with AI, using DETR for accessibility and innovation. Bridging ...

AI is helping scientists crack the code on next-gen batteries that could replace lithium-ion tech. By discovering novel porous materials, researchers may have paved the way for more powerful and ...

Graph Convolutional Networks in PyTorch. Contribute to Tinard/Mypygcn development by creating an account on GitHub.

Muhammad H, Sigel CS, Campanella G, et al: Unsupervised subtyping of cholangiocarcinoma using a deep clustering convolutional autoencoder, in Shen D (ed): Medical Image Computing and Computer Assisted ...

This article explains how AI fails at visual image comparison and offers a solution: a custom CNN that compares segments to tolerate minor pixel shifts and find meaningful differences.

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, significant ...

Sun, Y., Xue, B., Zhang, M. and Yen, G.G. (2019) A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification. IEEE Transactions on ...