A comprehensive survey on test-time adaptation under distribution shifts
Abstract Machine learning methods strive to acquire a robust model during the training
process that can effectively generalize to test samples, even in the presence of distribution …
process that can effectively generalize to test samples, even in the presence of distribution …
Progressive Contrastive Label Optimization for Source-Free Universal 3D Model Retrieval
Unsupervised Cross-Domain 3D Model Retrieval (UCD3DMR) has emerged as an effective
tool for managing 3D model data recently. However, existing UCD3DMR algorithms typically …
tool for managing 3D model data recently. However, existing UCD3DMR algorithms typically …
Universal domain adaptation for machinery fault diagnosis based on multi‐scale dual attention network and entropy‐based clustering
CY Lee, GL Zhuo - IET Science, Measurement & Technology, 2024 - Wiley Online Library
Recently, data‐driven cross‐domain fault diagnosis methods for rotating machinery have
been successfully developed. However, most existing diagnostic methods assume that the …
been successfully developed. However, most existing diagnostic methods assume that the …
Adaptive Prompt Learning with Negative Textual Semantics and Uncertainty Modeling for Universal Multi-Source Domain Adaptation
Universal Multi-source Domain Adaptation (UniMDA) transfers knowledge from multiple
labeled source domains to an unlabeled target domain under domain shifts (different data …
labeled source domains to an unlabeled target domain under domain shifts (different data …