Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Morales, Giorgio"'
Autor:
Morales, Giorgio, Sheppard, John W.
Symbolic regression (SR) methods attempt to learn mathematical expressions that approximate the behavior of an observed system. However, when dealing with multivariate systems, they often fail to identify the functional form that explains the relatio
Externí odkaz:
http://arxiv.org/abs/2406.17834
Autor:
Morales, Giorgio, Sheppard, John
In Precision Agriculture, the utilization of management zones (MZs) that take into account within-field variability facilitates effective fertilizer management. This approach enables the optimization of nitrogen (N) rates to maximize crop yield produ
Externí odkaz:
http://arxiv.org/abs/2403.10730
Autor:
Morales, Giorgio, Sheppard, John
Response curves exhibit the magnitude of the response of a sensitive system to a varying stimulus. However, response of such systems may be sensitive to multiple stimuli (i.e., input features) that are not necessarily independent. As a consequence, t
Externí odkaz:
http://arxiv.org/abs/2304.04063
Autor:
Morales, Giorgio, Sheppard, John W.
Publikováno v:
G. Morales and J. W. Sheppard, "Dual Accuracy-Quality-Driven Neural Network for Prediction Interval Generation," in IEEE Transactions on Neural Networks and Learning Systems, 2023
Accurate uncertainty quantification is necessary to enhance the reliability of deep learning models in real-world applications. In the case of regression tasks, prediction intervals (PIs) should be provided along with the deterministic predictions of
Externí odkaz:
http://arxiv.org/abs/2212.06370
Autor:
Morales, Giorgio, Sheppard, John W.
Crop yield prediction is one of the tasks of Precision Agriculture that can be automated based on multi-source periodic observations of the fields. We tackle the yield prediction problem using a Convolutional Neural Network (CNN) trained on data that
Externí odkaz:
http://arxiv.org/abs/2111.08069
In recent years, Hyperspectral Imaging (HSI) has become a powerful source for reliable data in applications such as remote sensing, agriculture, and biomedicine. However, hyperspectral images are highly data-dense and often benefit from methods to re
Externí odkaz:
http://arxiv.org/abs/2106.00645
Publikováno v:
2019 IEEE XXVI International Conference on Electronics, Electrical Engineering and Computing (INTERCON)
The parameters estimation of a system using indirect measurements over the same system is a problem that occurs in many fields of engineering, known as the inverse problem. It also happens in the field of underwater acoustic, especially in mediums th
Externí odkaz:
http://arxiv.org/abs/1906.04310
End-to-end Cloud Segmentation in High-Resolution Multispectral Satellite Imagery Using Deep Learning
Publikováno v:
2019 IEEE XXVI International Conference on Electronics, Electrical Engineering and Computing (INTERCON)
Segmenting clouds in high-resolution satellite images is an arduous and challenging task due to the many types of geographies and clouds a satellite can capture. Therefore, it needs to be automated and optimized, specially for those who regularly pro
Externí odkaz:
http://arxiv.org/abs/1904.12743
Autor:
Morales, Giorgio1 (AUTHOR), Sheppard, John W.1 (AUTHOR) john.sheppard@montana.edu, Hegedus, Paul B.2 (AUTHOR), Maxwell, Bruce D.2 (AUTHOR)
Publikováno v:
Sensors (14248220). Jan2023, Vol. 23 Issue 1, p489. 22p.
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