Results 161 to 170 of about 12,484 (262)

A simple preprocessing approach for improving semantic segmentation in unsupervised domain adaptation. [PDF]

Sci Rep
Ettedgui S, Abu-Hussein S, Giryes R.
europepmc   +1 more source

Unsupervised Domain Adaptation for Segmentation with Black-box Source Model. [PDF]

Proc SPIE Int Soc Opt Eng, 2022
Liu X, Yoo C, Xing F, Kuo CJ, El Fakhri G, Kang JW, Woo J.   +6 more
europepmc   +1 more source

Integrating Artificial Intelligence With Droplet‐Based Microfluidics: Advances, Challenges, and Emerging Opportunities

Advanced Intelligent Systems, EarlyView.
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai, Sukrit Gaira, Rongfeng Wang, Qingtian Zhang, Ming Li, Liao Wu, Diangeng Li, Yi Li, Chengchen Zhang, Jinhong Guo, Shi‐Yang Tang   +10 more
wiley   +1 more source

Privacy-preserving federated unsupervised domain adaptation with application to age prediction from DNA methylation data. [PDF]

Bioinformatics
Baykara CA, Ünal AB, Pfeifer N, Akgün M.   +3 more
europepmc   +1 more source

Unsupervised Domain Adaptation with Shape Constraint and Triple Attention for Joint Optic Disc and Cup Segmentation. [PDF]

Sensors (Basel), 2022
Zhang F, Li S, Deng J.
europepmc   +1 more source

Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs

Advanced Intelligent Systems, EarlyView.
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza, Bruno José Olivieri de Souza, Markus Endler   +2 more
wiley   +1 more source

Contrastive learning enhanced pseudo-labeling for unsupervised domain adaptation in person re-identification. [PDF]

PLoS One
Bai X, Zhang Y, Zhang C, Wang Z.
europepmc   +1 more source

TSTELM: Two-Stage Transfer Extreme Learning Machine for Unsupervised Domain Adaptation. [PDF]

Comput Intell Neurosci, 2022
Zang S, Li X, Ma J, Yan Y, Gao J, Wei Y.
europepmc   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Threshold-based exploitation of noisy label in black-box unsupervised domain adaptation. [PDF]

PLoS One
Xu H, Lee J, Kang U.
europepmc   +1 more source