Reversibility of a Point Mutation Induced Domain Shift: Expanding the Conformational Space of a Sucrose Phosphorylase
Sign Up to like & getrecommendations! Published in 2018 at "Scientific Reports"
DOI: 10.1038/s41598-018-28802-2
Abstract: Despite their popularity as enzyme engineering targets structural information about Sucrose Phosphorylases remains scarce. We recently clarified that the Q345F variant of Bifidobacterium adolescentis Sucrose Phosphorylase is able to accept large polyphenolic substrates like resveratrol… read more here.
Keywords: sucrose phosphorylase; reversibility point; domain shift;
Mitigating Domain Shift in AI-Based TB Screening With Unsupervised Domain Adaptation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3168680
Abstract: We demonstrate that Domain Invariant Feature Learning (DIFL) can improve the out-of-domain generalizability of a deep learning Tuberculosis (TB) screening algorithm. It is well known that state of the art deep learning algorithms often have… read more here.
Keywords: domain adaptation; shift based; domain; domain shift ... See more keywords
PEAMATL: A Strategy for Developing Near-Infrared Spectral Prediction Models Under Domain Shift Using Self-Supervised Transfer Learning
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2023.3273689
Abstract: Near-infrared (NIR) spectroscopy combined with spectra prediction models has been widely employed as quick and cost-effective analytical techniques in the pharmaceutical, chemical, and food industries. However, calibration has to be conducted for a prediction model… read more here.
Keywords: self supervised; domain; prediction models; prediction ... See more keywords
Domain Shift Preservation for Zero-Shot Domain Adaptation
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DOI: 10.1109/tip.2021.3084354
Abstract: In learning-based image processing a model that is learned in one domain often performs poorly in another since the image samples originate from different sources and thus have different distributions. Domain adaptation techniques alleviate the… read more here.
Keywords: domain; domain adaptation; target domain; domain shift ... See more keywords
Training Deep Network Ultrasound Beamformers With Unlabeled In Vivo Data
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2021.3107198
Abstract: Conventional delay-and-sum (DAS) beamforming is highly efficient but also suffers from various sources of image degradation. Several adaptive beamformers have been proposed to address this problem, including more recently proposed deep learning methods. With deep… read more here.
Keywords: vivo data; domain shift; unlabeled vivo; domain ... See more keywords