industrial-anomaly-detection

[NeurIPS 2025] Pytorch Implementation for NeurIPS 2025 paper: ADPretrain: Advancing Industrial Anomaly Detection via Anomaly Representation Pretraining

EMIT: Enhancing MLLMs for Industrial Anomaly Detection via Difficulty-Aware GRPO

This repo contains state-of-the-art deep learning models for industrial anomaly detection, defect segmentation, detection, and classification, with other industrial machine vision applications.

This is an official Pytorch implementation of the paper "Lightweight Masked Reconstruction for Real-Time Sensor-Driven Anomaly Detection in Industrial IoT".

Official ISP-AD Dataset repository, providing PyTorch & Anomalib evaluation pipelines for industrial visual anomaly detection.

Core repository for Cortex Intelligence Nexus Intel Solution—building autonomous AI architectures, industrial control matrices, and high-performance enterprise automation.

Operational Health Scoring for industrial process monitoring, anomaly detection and contextual analytics.

ECHO-CAVER: evidence-tangent residual readers for FREB-CAVER and JUDO

A focused fork of an anomaly detection library, dedicated to enhancing and extending the PatchCore model.

FREB-CAVER: model-native query-reference evidence binding for JUDO industrial anomaly reasoning