Ghent University Academic Bibliography

Your filters: cql: keyword exact "support vector machine (SVM)"

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Wind turbine hybrid physics-based deep learning model for a health monitoring approach considering provision of ancillary services

Nezmin Kayedpour (UGent) , Jixiang Qing, Jolan Wauters (UGent) , Jeroen De Kooning (UGent) , Ivo Couckuyt (UGent) and Guillaume Crevecoeur (UGent)

(2024) IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT. 73.
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A novel hybrid sand and dust storm detection method using MODIS data on GEE platform

Wei Wang, Alim Samat, Jilili Abuduwaili, Yongxiao Ge, Philippe De Maeyer (UGent) and Tim Van de Voorde (UGent)

(2022) EUROPEAN JOURNAL OF REMOTE SENSING. 55(1). p.420-428
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Spatiotemporal prediction and mapping of heavy metals at regional scale using regression methods and Landsat 7

Abdul Mouazen (UGent) , Felix Nyarko, Muhammad Qaswar (UGent) , Gergely Toth, Anne Gobin and Dimitrios Moshou

(2021) REMOTE SENSING. 13(22).
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Prediction of active microwave backscatter over snow-covered terrain across Western Colorado using a land surface model and support vector machine regression

Jongmin Park, Barton A. Forman and Hans Lievens (UGent)

(2021) IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING. 14. p.2403-2417
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Automatic detection of welding defects using the convolutional neural network

Roman Sizyakin, Viacheslav V. Voronin, Nikolay Gapon, Aleksandr Zelensky and Aleksandra Pizurica (UGent)

(2019) AUTOMATED VISUAL INSPECTION AND MACHINE VISION III. In Proceedings of SPIE 11061.
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A practical approach to model selection for support vector machines with a gaussian kernel

Matthias Varewyck (UGent) and Jean-Pierre Martens (UGent)

(2011) IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS. 41(2). p.330-340

Academic Bibliography

Wind turbine hybrid physics-based deep learning model for a health monitoring approach considering provision of ancillary services

A novel hybrid sand and dust storm detection method using MODIS data on GEE platform

Spatiotemporal prediction and mapping of heavy metals at regional scale using regression methods and Landsat 7

Prediction of active microwave backscatter over snow-covered terrain across Western Colorado using a land surface model and support vector machine regression

Automatic detection of welding defects using the convolutional neural network

A practical approach to model selection for support vector machines with a gaussian kernel

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