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Speech Interactive Emotion Recognition System Based on Random Forest

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DOI
10.1109/IWCMC48107.2020.9148117
Yan, S.; Ye, L.; Han, S.; Han, T.; Li, Y.; Alasaarela, E.
International Wireless Communications and Mobile Computing Conference2020Publicationer information ikon

A New Evolutionary Hybrid Random Forest Model for SPEI Forecasting

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DOI
10.3390/w14050755
Danandeh Mehr, Ali; Torabi Haghighi, Ali; Jabarnejad, Masood; Safari, Mir Jafar Sadegh; Nourani, Vah...
Water2022Publicationer information ikon

Data-driven Optimal Scheduling of Isolated Microgrid Using Random Forest Regressor

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10.1109/eeeic/icpseurope61470.2024.10751201
Zandrazavi, Seyed Farhad; Shafie-khah, Miadreza; Pashaei, Meysam
International Conference on Environment and Electrical Engineering2024Publicationer information ikon

Random forest learning method to identify different objects using channel estimations from VLC link

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10.1109/PIMRC48278.2020.9217131
Ilter, Mehmet C.; Dowhuszko, Alexis A.; Vangapattu, Kiran K.; Kutlu, Kubra; Hämäläinen, Jyri
IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications workshops2020Publicationer information ikon

Precise transformer fault diagnosis via random forest model enhanced by synthetic minority over-sampling technique

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10.1016/j.epsr.2023.109361
Prasojo, Rahman Azis; Putra, Muhammad Akmal A.; Ekojono, ; Apriyani, Meyti Eka; Rahmanto, Anugrah Nu...
Electric Power Systems Research2023Publicationer information ikon

Snow depth estimation and historical data reconstruction over China based on a random forest machine learning approach

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DOI
10.5194/tc-14-1763-2020
Yang, Jianwei; Jiang, Lingmei; Luojus, Kari; Pan, Jinmei; Lemmetyinen, Juha; Takala, Matias; Wu, She...
Cryosphere2020Publicationer information ikon

Improving snow depth estimation by coupling HUT-optimized effective snow grain size parameters with the random forest approach

Referentgranskad
DOI
10.1016/j.rse.2021.112630
Yang, J.W.; Jiang, L.M.; Lemmetyinen, J.; Pan, J.M.; Luojus, K.; Takala, M.
Remote sensing of environment2021Publicationer information ikon

Illumination correction for close-range hyperspectral images using spectral invariants and random forest regression

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DOI
10.1016/j.rse.2024.114467
Ihalainen, Olli; Sandmann, Theresa; Rascher, Uwe; Mõttus, Matti
Remote Sensing of Environment2024Publicationer information ikon

Random Forest Oriented Fast QTBT Frame Partitioning

Referentgranskad
DOI
10.1109/ICASSP.2019.8683413
Amestoy, Thomas;Mercat, Alexandre;Hamidouche, Wassim;Bergeron, Cyril;Menard, Daniel
IEEE International Conference on Acoustics, Speech, and Signal Processing2019Publicationer information ikon

The relationship between forest structure and naturalness in the Finnish national forest inventory

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DOI
10.1093/forestry/cpad053
Myllymäki, Mari; Tuominen, Sakari; Kuronen, Mikko; Packalen, Petteri; Kangas, Annika
Forestry2024

Speech Interactive Emotion Recognition System Based on Random Forest

Referentgranskad
Öppen tillgång
DOI
10.1109/IWCMC48107.2020.9148117
2020

A New Evolutionary Hybrid Random Forest Model for SPEI Forecasting

Referentgranskad
Öppen tillgång
DOI
10.3390/w14050755
2022

Data-driven Optimal Scheduling of Isolated Microgrid Using Random Forest Regressor

Referentgranskad
Öppen tillgång
DOI
10.1109/eeeic/icpseurope61470.2024.10751201
2024

Random forest learning method to identify different objects using channel estimations from VLC link

Referentgranskad
Öppen tillgång
DOI
10.1109/PIMRC48278.2020.9217131
2020

Precise transformer fault diagnosis via random forest model enhanced by synthetic minority over-sampling technique

Referentgranskad
Öppen tillgång
DOI
10.1016/j.epsr.2023.109361
2023

Snow depth estimation and historical data reconstruction over China based on a random forest machine learning approach

Referentgranskad
Öppen tillgång
DOI
10.5194/tc-14-1763-2020
2020

Improving snow depth estimation by coupling HUT-optimized effective snow grain size parameters with the random forest approach

Referentgranskad
DOI
10.1016/j.rse.2021.112630
2021

Illumination correction for close-range hyperspectral images using spectral invariants and random forest regression

Referentgranskad
Öppen tillgång
DOI
10.1016/j.rse.2024.114467
2024

Random Forest Oriented Fast QTBT Frame Partitioning

Referentgranskad
DOI
10.1109/ICASSP.2019.8683413
2019

The relationship between forest structure and naturalness in the Finnish national forest inventory

Referentgranskad
Öppen tillgång
DOI
10.1093/forestry/cpad053
2024