Work

Diff-Fastener: A Few-Shot Rail Fastener Anomaly Detection Framework Based on Diffusion Model

Year: 2025

Type: article

Abstract: Supervised learning-based rail fastener anomaly detection models are limited by the scarcity of anomaly samples and perform poorly under data imbalance conditions. However, unsupervised anomaly detection methods based on diff... | Find, read and cite all the research you need on Tech Science Press

Source: Structural durability & health monitoring

DOI: 10.32604/sdhm.2025.066098

Authors: Peng Sun, Dechen Yao, Jianwei Yang, Quanyu Long

Institution: Beijing University of Civil Engineering and Architecture

Language: English

Topic: Infrastructure Maintenance and Monitoring

Subfield: Civil and Structural Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funder: National Natural Science Foundation of China