Results 161 to 170 of about 82,326 (277)

Enhanced 3D Pose Estimation in Multi-Person, Multi-View Scenarios through Unsupervised Domain Adaptation with Dropout Discriminator. [PDF]

Sensors (Basel), 2023
Deng J, Yao H, Shi P.
europepmc   +1 more source

PIK3CA Mutations Downregulate PPT1 to Promote Adipogenesis by Suppressing P300 Depalmitoylation and Phase Separation

Advanced Science, EarlyView.
This study demonstrates that somatic PIK3CA mutations suppress PPT1 expression via activation of the PI3K–AKT–c‐JUN axis. This reduction in PPT1 weakens its interaction with P300, thereby increasing palmitoylation at C1176 of P300 and protecting P300 from lysosomal degradation.
Hongrui Chen, Zening Huang, Rui Chang, Wei Gao, Yajing Qiu, Bin Sun, Chen Hua, Xiaoxi Lin   +7 more
wiley   +1 more source

Unsupervised Domain Adaptation with Raman Spectroscopy for Rapid Autoimmune Disease Diagnosis. [PDF]

Sensors (Basel)
Zhang Z, Liu Y, Chen C, Lv X, Chen C.
europepmc   +1 more source

Unsupervised domain adaptation for the detection of cardiomegaly in cross-domain chest X-ray images. [PDF]

Front Artif Intell, 2023
Thiam P, Lausser L, Kloth C, Blaich D, Liebold A, Beer M, Kestler HA.   +6 more
europepmc   +1 more source

Triboelectric Tactile Transducers for Neuromorphic Sensing and Synaptic Emulation: Materials, Architectures, and Interfaces

Advanced Energy and Sustainability Research, EarlyView.
Triboelectric nanogenerators are vital for sustainable energy in future technologies such as wearables, implants, AI, ML, sensors and medical systems. This review highlights improved TENG neuromorphic devices with higher energy output, better stability, reduced power demands, scalable designs and lower costs.
Ruthran Rameshkumar, Arunkumar Chandrasekhar, Poongundran Selvaprabhu   +2 more
wiley   +1 more source

Correction: 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

Unsupervised Domain Adaptation for Image Classification and Object Detection Using Guided Transfer Learning Approach and JS Divergence. [PDF]

Sensors (Basel), 2023
Goel P, Ganatra A.
europepmc   +1 more source

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

Advanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren, Qian Jiang, Xin Jin, Puming Wang, Xing Chu, Shaowen Yao, Shengfa Miao   +6 more
wiley   +1 more source

Learning Domain-Invariant Representations for Event-Based Motion Segmentation: An Unsupervised Domain Adaptation Approach. [PDF]

J Imaging
Jeryo M, Harati A.
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source