Search results for "BiLSTM"

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Deep learning for agricultural land use classification from Sentinel-2

2020

[ES] En el campo de la teledetección se ha producido recientemente un incremento del uso de técnicas de aprendizaje profundo (deep learning). Estos algoritmos se utilizan con éxito principalmente en la estimación de parámetros y en la clasificación de imágenes. Sin embargo, se han realizado pocos esfuerzos encaminados a su comprensión, lo que lleva a ejecutarlos como si fueran “cajas negras”. Este trabajo pretende evaluar el rendimiento y acercarnos al entendimiento de un algoritmo de aprendizaje profundo, basado en una red recurrente bidireccional de memoria corta a largo plazo (2-BiLSTM), a través de un ejemplo de clasificación de usos de suelo agrícola de la Comunidad Valenciana dentro d…

Series temporalesTime series010504 meteorology & atmospheric sciencesComputer scienceRemote sensing applicationGeography Planning and Development0211 other engineering and technologiesDecision treelcsh:G1-92202 engineering and technologyClasificaciónMachine learningcomputer.software_genre01 natural sciencesBiLSTMClassifier (linguistics)Earth and Planetary Sciences (miscellaneous)Spatial analysis021101 geological & geomatics engineering0105 earth and related environmental sciencesArtificial neural networkbusiness.industryDeep learningDeep learningClassificationRandom forestSupport vector machineArtificial intelligenceSentinel-2businesscomputerlcsh:Geography (General)
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Cross-Subject Emotion Recognition Using Fused Entropy Features of EEG.

2022

Emotion recognition based on electroencephalography (EEG) has attracted high interest in fields such as health care, user experience evaluation, and human–computer interaction (HCI), as it plays an important role in human daily life. Although various approaches have been proposed to detect emotion states in previous studies, there is still a need to further study the dynamic changes of EEG in different emotions to detect emotion states accurately. Entropy-based features have been proved to be effective in mining the complexity information in EEG in many areas. However, different entropy features vary in revealing the implicit information of EEG. To improve system reliability, in this paper,…

ihmisen ja tietokoneen vuorovaikutusGeneral Physics and AstronomyneuroverkotentropiamittausmenetelmätMSEBiLSTMtunteetemotion recognitionfeature fusionemotion recognition; EEG; feature fusion; MSE; BiLSTMEEGaivotfysiologiset vaikutuksetEntropy (Basel, Switzerland)
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