在工业质检、安全监控等领域， 多类别无监督异常检测（Multi-class Unsupervised Anomaly Detection, MUAD） 一直是个极具挑战的课题。传统的做法通常是训练一个复杂的编码器-解码器模型，试图重建正常样本的特征。但你有没有想过，这种费时费力的“训练”过程，真的是必须的吗？

The funding backs continued innovation in production-grade forecasting, anomaly detection, and artificial intelligence.

Hyperspectral anomaly detection techniques represent a rapidly evolving area in remote sensing, combining advanced machine learning with signal processing to identify outlying elements in ...

Anomaly detection is the process of identifying events or patterns that differ from expected behavior. Anomaly detection can range from simple outlier detection to complex machine learning algorithms ...

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

I am the VP of Engineering at Apriorit, a software development company that provides engineering services globally to tech companies. Social media is an indispensable tool for businesses to engage ...

Using a powerful AI tool, astronomers have combed through vast troves of data from NASA's Hubble and found over 1,300 cosmic anomalies, more than 800 of which are new to science.

Discover how to secure AI orchestration workflows using post-quantum cryptography and AI-driven anomaly detection for Model Context Protocol (MCP) environments.

Unlike pattern-matching, which is about spotting connections and relationships, when we detect anomalies we are seeing disconnections—things that do not fit together. Anomalies get much less attention ...