Threshold-based exploitation of noisy label in black-box unsupervised domain adaptation. [PDF]
Xu H, Lee J, Kang U.
europepmc +1 more source
This study demonstrates how optimizing laser power, scanning speed, and hatching distance in laser powder bed fusion can boost the productivity of Inconel 718 manufacturing by up to 29% while maintaining mechanical integrity. The work delivers a validated process window and cost–time analysis, offering industry‐ready guidelines for efficient additive ...
Amir Behjat +7 more
wiley +1 more source
Towards bridging the synthetic-to-real gap in quantitative photoacoustic tomography via unsupervised domain adaptation. [PDF]
Wang Z, Tao W, Zhang Z, Zhao H.
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A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
Histogram matching-enhanced adversarial learning for unsupervised domain adaptation in medical image segmentation. [PDF]
Qian X, Shao HC, Li Y, Lu W, Zhang Y.
europepmc +1 more source
Unsupervised Domain Adaptation Method Based on Relative Entropy Regularization and Measure Propagation. [PDF]
Tan L +7 more
europepmc +1 more source
Enhancing AI microscopy for foodborne bacterial classification using adversarial domain adaptation to address optical and biological variability. [PDF]
Bhattacharya S +4 more
europepmc +1 more source
A Lightweight Network with Domain Adaptation for Motor Imagery Recognition. [PDF]
Ding X, Zhang Z, Wang K, Xiao X, Xu M.
europepmc +1 more source
Domain adaptation in small-scale and heterogeneous biological datasets. [PDF]
Orouji S, Liu MC, Korem T, Peters MAK.
europepmc +1 more source

