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Contrasting and Combining Least Squares Based Learners for Emotion Recognition in the Wild.

, , , and . ICMI, page 459-466. ACM, (2015)

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Predicting CO and NOxemissions from gas turbines: novel data and abenchmark PEMS., , and . Turkish J. Electr. Eng. Comput. Sci., 27 (6): 4783-4796 (2019)The sound of silence: Breathing analysis for finding traces of trauma and depression in oral history archives., , , , and . Digit. Scholarsh. Humanit., 36 (Supplement): 2 (2021)Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos., , , , , , , , , and 7 other author(s). CoRR, (2018)Ensemble CCA for Continuous Emotion Prediction., , and . AVEC@MM, page 19-26. ACM, (2014)Towards using Breathing Features for Multimodal Estimation of Depression Severity., , , and . ICMI, page 128-138. ACM, (2022)Feature Selection and Multimodal Fusion for Estimating Emotions Evoked by Movie Clips., , , and . ICMR, page 405-412. ACM, (2018)Complex Paralinguistic Analysis of Speech: Predicting Gender, Emotions and Deception in a Hierarchical Framework., , , and . INTERSPEECH, page 4735-4739. ISCA, (2022)Is Everything Fine, Grandma? Acoustic and Linguistic Modeling for Robust Elderly Speech Emotion Recognition., , , , , , and . INTERSPEECH, page 2097-2101. ISCA, (2020)Fusing Acoustic Feature Representations for Computational Paralinguistics Tasks., and . INTERSPEECH, page 2046-2050. ISCA, (2016)Multimodal fusion of audio, scene, and face features for first impression estimation., , and . ICPR, page 43-48. IEEE, (2016)