Work

Enhanced industrial anomaly detection via CutMask data augmentation: a self-supervised approach

Year: 2026

Type: article

Source: The Visual Computer

DOI: 10.1007/s00371-026-04601-z

Authors: Le Yang, Dingjian Yao, Wenhan Yang, Zhengsong Wang

Institution: Northeastern University

Language: English

Topic: Industrial Vision Systems and Defect Detection

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funders: National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities

Awards: G2026022350, G6643579984

OpenAlex ID: W7165674522

FWCI: 4.199

Cites: 55

Cited by: 1

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