Results 31 to 40 of about 212,881 (293)
Image reconstruction in optical interferometry: Benchmarking the regularization [PDF]
, 2011 With the advent of infrared long-baseline interferometers with more than two telescopes, both the size and the completeness of interferometric data sets have significantly increased, allowing images based on models with no a priori assumptions to be ...
Besnerais +27 more
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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
Axioms, 2023 As solar energy generation has become more and more important for the economies of numerous countries in the last couple of decades, it is highly important to build accurate models for forecasting the amount of green energy that will be produced ...
C. Stoean +6 more
semanticscholar +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
Hyperparameter Optimization for AST Differencing
IEEE Transactions on Software Engineering, 2023 Computing the differences between two versions of the same program is an essential task for software development and software evolution research. AST differencing is the most advanced way of doing so, and an active research area. Yet, AST differencing algorithms rely on configuration parameters that may have a strong impact on their effectiveness.
Matias Martinez +2 more
openaire +3 more sources
Deep Learning in Forest Structural Parameter Estimation Using Airborne LiDAR Data
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Accurately estimating and mapping forest structural parameters are essential for monitoring forest resources and understanding ecological processes. The novel deep learning algorithm has the potential to be a promising approach to improve the estimation ...
Hao Liu +7 more
doaj +1 more source
Interpolation Models with Multiple Hyperparameters [PDF]
Statistics and Computing, 1996 A traditional interpolation model is characterized by the choice of regularizer applied to the interpolant, and the choice of noise model. Typically, the regularizer has a single regularization constant α, and the noise model has a single parameter β.
DAVID J. C. MACKAY, RYO TAKEUCHI
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PyHopper -- Hyperparameter optimization
, 2022 Hyperparameter tuning is a fundamental aspect of machine learning research. Setting up the infrastructure for systematic optimization of hyperparameters can take a significant amount of time. Here, we present PyHopper, a black-box optimization platform designed to streamline the hyperparameter tuning workflow of machine learning researchers. PyHopper's
Lechner, Mathias +4 more
openaire +2 more sources
IEEE Access, 2023 Prediction of work Travel mode choice is one of the most important parts of travel demand forecasting. Planners can achieve sustainability goals by accurately forecasting how people will get to and from work.
Mahdi Aghaabbasi +4 more
semanticscholar +1 more source