Results 11 to 20 of about 171,040 (210)
Сучасні інформаційні системи, 2019 This paper contains formal problem definition of predicting unfavorable airborne events during flight. Restrictions and assumptions are put into the prognosis method of unfavorable airborne events during flight.
Evhenii Gryshmanov +2 more
doaj +1 more source
Applied Sciences, 2022 Hyperparameter tuning is a critical function necessary for the effective deployment of most machine learning (ML) algorithms. It is used to find the optimal hyperparameter settings of an ML algorithm in order to improve its overall output performance. To
Ismail Damilola Raji +5 more
doaj +1 more source
Hyperparameter-free losses for model-based monocular reconstruction [PDF]
, 2019 This work proposes novel hyperparameter-free losses for single view 3D reconstruction with morphable models (3DMM). We dispense with the hyperparameters used in other works by exploiting geometry, so that the shape of the object and the camera pose are ...
Batard, Thomas +3 more
core +2 more sources
Sensors, 2021 Electrical resistivity is used to obtain various types of information for soil strata. Hence, the prediction of electrical resistivity is helpful to predict the future behavior of soil.
Seung-Jae Lee, Hyung-Koo Yoon
doaj +1 more source
Combining cosmological datasets: hyperparameters and Bayesian evidence [PDF]
, 2002 A method is presented for performing joint analyses of cosmological datasets, in which the weight assigned to each dataset is determined directly by it own statistical properties.
Bishop +22 more
core +3 more sources
Future Internet, 2020 Web service composition is the process of combining and reusing existing web services to create new business processes to satisfy specific user requirements. Reliability plays an important role in ensuring the quality of web service composition. However,
Yang Song, Yawen Wang, Dahai Jin
doaj +1 more source
Hyperparameter Estimation in Bayesian MAP Estimation: Parameterizations and Consistency [PDF]
, 2019 The Bayesian formulation of inverse problems is attractive for three primary reasons: it provides a clear modelling framework; means for uncertainty quantification; and it allows for principled learning of hyperparameters.
Dunlop, Matthew M. +2 more
core +4 more sources
Diagnostics, 2022 Numerous research have demonstrated that Convolutional Neural Network (CNN) models are capable of classifying visual field (VF) defects with great accuracy.
Masyitah Abu +6 more
doaj +1 more source
Remote Sensing, 2022 Aflaj (plural of falaj) are tunnels or trenches built to deliver groundwater from its source to the point of consumption. Support vector machine (SVM) and extreme gradient boosting (XGB) machine learning models were used to predict groundwater aflaj ...
Khalifa M. Al-Kindi, Saeid Janizadeh
doaj +1 more source
Improving the Robustness and Quality of Biomedical CNN Models through Adaptive Hyperparameter Tuning
Applied Sciences, 2022 Deep learning is an obvious method for the detection of disease, analyzing medical images and many researchers have looked into it. However, the performance of deep learning algorithms is frequently influenced by hyperparameter selection, the question of
Saeed Iqbal +4 more
doaj +1 more source