Results 111 to 120 of about 3,036,262 (193)

A hybrid framework for unsupervised domain adaptation: Integrating feature alignment, parameter adaptation, and instance selection

Journal of King Saud University: Computer and Information Sciences
Unsupervised Domain Adaptation (UDA), a key subfield of Transfer Learning (TL), addresses the performance degradation caused by domain shift that occurs when a model trained on a labeled source domain is applied to an unlabeled target domain.
Shaofei Zang, Huimin Li, Guosen Xie, Xinghai Li, Nannan Lu, Jiwei Gao, Jianwei Ma   +6 more
doaj   +1 more source

Two-pass decision tree construction for unsupervised adaptation of HMM-based synthesis models [PDF]

, 2010
Hidden Markov model (HMM) -based speech synthesis systems possess several advantages over concatenative synthesis systems. One such advantage is the relative ease with which HMM-based systems are adapted to speakers not present in the training dataset ...

core   +1 more source

Category Prior-Guided Unsupervised Domain Adaptation

, 2020
Unsupervised domain adaptation (UDA) aims to adapt the generalization of a model from the source domain with fundamental annotations to the target domain without any labels.
Zhang, Qiming
core  

A curriculum-guided unified framework for robust unsupervised domain adaptation on multi-cohort Parkinson's disease diagnosis. [PDF]

Quant Imaging Med Surg
Shen Y, Hai J, Qiao K, Chen J, Li Y, Yan B.   +5 more
europepmc   +1 more source

Improving Generalization of Deep Learning for Glaucoma Classification Under Real-World Domain Shift via Unsupervised Domain Adaptation. [PDF]

Transl Vis Sci Technol
Rashidisabet H, Chan RVP, Vajaranant TS, Yi D.   +3 more
europepmc   +1 more source

Variance Extrapolated Class-Imbalance-Aware Domain Adaptive Myocardial Segmentation in Multi-Sequence Cardiac MRI. [PDF]

IEEE J Biomed Health Inform
Xing F, Liu X, Aganj I, Fakhri GE, Kim P, Choi BW, Woo J.   +6 more
europepmc   +1 more source

Reliable Pseudo-Labeling and Confusion Calibration for Foggy-Scene Semantic Segmentation. [PDF]

J Imaging
Yan S, Feng S, Wei Z.
europepmc   +1 more source

FD-MSP: feature decoupling network with multi-scale prototypes for domain-adaptive polyp segmentation. [PDF]

BMC Med Imaging
Zhong W, Yang X, Liu S, Wang Y, Im SK.
europepmc   +1 more source

MAIG-Net: Unsupervised Remote Sensing Road Extraction Combining Multi-Layer Adversarial Learning and Intermediate Domain Guidance. [PDF]

Sensors (Basel)
Bao C, Chen G, Jin W, Yang J, Li S.
europepmc   +1 more source

Monocular absolute depth estimation from endoscopy via domain-invariant feature learning and latent consistency. [PDF]

Proc SPIE Int Soc Opt Eng
Li H, Lu D, d'Almeida J, Isik D, Aghdam EK, DiSanto N, Acar A, Sharma S, Wu JY, Webster RJ, Oguz I.   +10 more
europepmc   +1 more source