Scientific Research Publishing

Covariant-Scale: Riemannian Manifold Learning for Scale-Invariant Video Anomaly Detection ()

Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs ...
IEEE

Numerical Investigation of Bending Tolerance of Multimode Optical Fiber Imaging with Variational Autoencoder

We propose a Variational Autoencoder-based image reconstruction through a multimode optical fiber. Simulations under bending conditions achieved 96% accuracy, demonstrating the feasibility even with ...
IEEE

Detection of Unknown Attacks Through Encrypted Traffic: A Gaussian Prototype-Aided Variational Autoencoder Framework

Abstract: The identification of encrypted network traffic presents a pivotal challenge in detecting unknown malicious traffic. Unlike closed-set identification, which primarily classifies known ...
GitHub

HiSTaR : identifying spatial domains in spatial transcriptomics data with Hierarchical Decoupled Variational Autoencoder

we propose a Hierarchical ST variational autoencoder (HiSTaR) to extract multi-level latent features of spots. HiSTaR tends to perform well in identifying spatial domains across multiple datasets from ...
GitHub

SVG: Latent Diffusion Model without Variational Autoencoder

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.