Ensemble learning and personalized training for the improvement of unsupervised deep learning-based synthetic CT reconstruction.
Sign Up to like & getrecommendations! Published in 2022 at "Medical physics"
DOI: 10.1002/mp.16087
Abstract: BACKGROUND The growing adoption of MRI-guided radiation therapy (RT) platforms and a focus on MRI-only RT workflows has brought the technical challenge of synthetic CT (sCT) reconstruction to the forefront. Unpaired-data deep learning-based approaches to… read more here.
Keywords: unpaired data; training; training strategy; personalized training ... See more keywords
A new efficient training strategy for deep neural networks by hybridization of artificial bee colony and limited-memory BFGS optimization algorithms
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.05.061
Abstract: Abstract Working up with deep learning techniques requires profound understanding of the mechanisms underlying the optimization of the internal parameters of complex structures. The major factor limiting this understanding is that there exist only a… read more here.
Keywords: limited memory; training strategy; optimization; bfgs ... See more keywords
Research on the Training Strategy of Aerobic Physical Education Talents under the Background of Artificial Intelligence Era
Sign Up to like & getrecommendations! Published in 2022 at "Applied Bionics and Biomechanics"
DOI: 10.1155/2022/1102760
Abstract: Aerobic is loved by the public, especially the young people, through the combination of the art and power of dance. With people's attention to health, the demand for aerobic professionals is increasing. As an important… read more here.
Keywords: artificial intelligence; physical education; training strategy; intelligence ... See more keywords
Optimized U-shape convolutional neural network with a novel training strategy for segmentation of concrete cracks
Sign Up to like & getrecommendations! Published in 2023 at "Structural Health Monitoring"
DOI: 10.1177/14759217221105647
Abstract: Crack detection is a vital component of structural health monitoring. Several computer vision-based studies have been proposed to conduct crack detection on concrete surfaces, but most cases have difficulties in detecting fine cracks. This study… read more here.
Keywords: training strategy; novel training; concrete; model ... See more keywords
A training strategy for hybrid models to break the curse of dimensionality
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DOI: 10.1371/journal.pone.0274569
Abstract: Mechanistic/data-driven hybrid modeling is a key approach when the mechanistic details of the processes at hand are not sufficiently well understood, but also inferring a model purely from data is too complex. By the integration… read more here.
Keywords: training strategy; hybrid models; strategy hybrid; strategy ... See more keywords
The Muscle Fatigue’s Effects on the sEMG-Based Gait Phase Classification: An Experimental Study and a Novel Training Strategy
Sign Up to like & getrecommendations! Published in 2021 at "Applied Sciences"
DOI: 10.3390/app11093821
Abstract: Surface Electromyography (sEMG) enables an intuitive control of wearable robots. The muscle fatigue-induced changes of sEMG signals might limit the long-term usage of the sEMG-based control algorithms. This paper presents the performance deterioration of sEMG-based… read more here.
Keywords: training strategy; semg based; fatigue; muscle fatigue ... See more keywords