pv magazine International

PV inverter output and anomalies predicted without environmental sensors

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...
Security Boulevard

AI-Driven Anomaly Detection in Post-Quantum Context Streams

Discover how AI-driven anomaly detection safeguards post-quantum context streams in Model Context Protocol (MCP) environments, ensuring robust security for AI infrastructure against future threats.
pv magazine International

US researchers use machine learning to detect hidden solar array defects

US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...
Devdiscourse

Fast and Accurate Water Leak Detection in Distribution Networks Using Deep Anomaly Models

Researchers from Politecnico di Milano propose a data-driven water leak detection method that treats leaks as anomalies in ...
Security Boulevard

Behavioral Analysis of AI Models Under Post-Quantum Threat Scenarios.

Explore behavioral analysis techniques for securing AI models against post-quantum threats. Learn how to identify anomalies and protect your AI infrastructure with quantum-resistant cryptography.
GitHub

autoencoder-anomaly-detection

This repo contains all my Deep Learning semester work, including implementations of FNNs, CNNs, autoencoders, CBOW, and transfer learning. I explored TensorFlow, Keras, PyTorch, and Theano while ...
The Conversation

How do ‘AI detection’ tools actually work? And are they effective?

T.J. Thomson receives funding from the Australian Research Council. He is an affiliate with the ARC Centre of Excellence for Automated Decision Making & Society. Aaron J. Snoswell receives research ...
Scientific Research Publishing

Sonani, R. and Govindarajan, V. (2022) A Hybrid Cloud-Integrated Autoencoder-GNN Architecture for Adaptive, High-Dimensional Anomaly Detection in US Financial Services ...

ABSTRACT: Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex ...
IEEE

Self-Supervised Masked Graph Autoencoder for Hyperspectral Anomaly Detection

Abstract: Hyperspectral image anomaly detection faces the challenge of difficulty in annotating anomalous targets. Autoencoder(AE)-based methods are widely used due to their excellent image ...
SpaceNews

True Anomaly hires former York Space executive as chief operating officer

WASHINGTON — True Anomaly, a defense-focused space technology startup based in Colorado, hired satellite industry executive Sarah Walter as chief operating officer, the company announced Sept. 2. The ...
IEEE

Patch-Shuffled Superpixel Synthetic Anomaly Insertion in Autoencoder Foreground Extracted Regions for Improved Visual Anomaly Detection

Abstract: We propose a self-supervised framework that combines an autoencoder and segmentation model to enhance anomaly detection and segmentation by inserting synthetic anomalies into the foreground ...