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Development and validation of the geriatrics health behavior questionnaire (GHBQ)
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In: BMC Public Health (2022)
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Enhanced protection face masks do not adversely impact thermophysiological comfort
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In: PLoS One (2022)
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Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help? ...
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Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection ...
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Uncertainty-Aware Balancing for Multilingual and Multi-Domain Neural Machine Translation Training ...
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Neural-Symbolic Commonsense Reasoner with Relation Predictors ...
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Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event Detection ...
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Learning to Explain: Generating Stable Explanations Fast ...
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It Is Not As Good As You Think! Evaluating Simultaneous Machine Translation on Interpretation Data ...
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Total Recall: a Customized Continual Learning Method for Neural Semantic Parsers ...
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Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection ...
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Multilingual Neural Machine Translation: Can Linguistic Hierarchies Help? ...
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Uncertainty-Aware Balancing for Multilingual and Multi-Domain Neural Machine Translation Training ...
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Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages ...
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Two-Stage Recognition and beyond for Compound Facial Emotion Recognition
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In: Electronics ; Volume 10 ; Issue 22 (2021)
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Abstract:
Facial emotion recognition is an inherently complex problem due to individual diversity in facial features and racial and cultural differences. Moreover, facial expressions typically reflect the mixture of people’s emotional statuses, which can be expressed using compound emotions. Compound facial emotion recognition makes the problem even more difficult because the discrimination between dominant and complementary emotions is usually weak. We have created a database that includes 31,250 facial images with different emotions of 115 subjects whose gender distribution is almost uniform to address compound emotion recognition. In addition, we have organized a competition based on the proposed dataset, held at FG workshop 2020. This paper analyzes the winner’s approach—a two-stage recognition method (1st stage, coarse recognition ; 2nd stage, fine recognition), which enhances the classification of symmetrical emotion labels.
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Keyword:
compound emotion recognition; deep learning; dominant and complementary emotion recognition; facial expression recognition
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URL: https://doi.org/10.3390/electronics10222847
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Psychometric properties of modified MOS social support survey 5-item (MSSS-5-item) among Iranian older adults
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In: BMC Geriatr (2021)
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Concurrent Group-Dynamic Assessment of Intermediate EFL Learners’ Receptive and Productive Vocabulary Size
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In: Porta Linguarum: revista internacional de didáctica de las lenguas extranjeras, ISSN 1697-7467, Nº. 36, 2021, pags. 119-137 (2021)
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