Domain generalization for cross-domain fault diagnosis: An application-oriented perspective and a benchmark study
Most data-driven methods for fault diagnostics rely on the assumption of independently and
identically distributed data of training and testing. However, domain shift between the …
identically distributed data of training and testing. However, domain shift between the …
Generalizing to Unseen Domains in Diabetic Retinopathy with Disentangled Representations
Diabetic Retinopathy (DR), induced by diabetes, poses a significant risk of visual
impairment. Accurate and effective grading of DR aids in the treatment of this condition. Yet …
impairment. Accurate and effective grading of DR aids in the treatment of this condition. Yet …
An Application-oriented Perspective of Domain Generalization for Cross-Domain Fault Diagnosis
Traditional data-driven fault diagnosis methods generally assume that the training and
testing distributions are the same, which does not hold in real-world industrial applications …
testing distributions are the same, which does not hold in real-world industrial applications …