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Investigating Keypoint Repeatability for 3D Correspondence Estimation in Cluttered Scenes.

, , , and . DICTA, page 1-7. IEEE, (2017)

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On the importance of glottal flow spectral energy for the recognition of emotions in speech., , and . INTERSPEECH, page 2346-2349. ISCA, (2010)Real time speech emotion recognition using RGB image classification and transfer learning., , , and . ICSPCS, page 1-8. IEEE, (2017)Towards autonomous machine reasoning: Multi-stage classification system with intermediate learning., , , and . ICSPCS, page 1-6. IEEE, (2017)Neural Networks and TEO Features for an Automatic Recognition of Stress in Spontaneous Speech., , , and . ICNC (2), page 227-231. IEEE Computer Society, (2009)Mel frequency cepstral feature and Gaussian Mixtures for modeling clinical depression in adolescents., , , and . IEEE ICCI, page 346-350. IEEE Computer Society, (2009)Detection of depression in adolescents based on statistical modeling of emotional influences in parent-adolescent conversations., , and . ICASSP, page 987-991. IEEE, (2015)Early prediction of major depression in adolescents using glottal wave characteristics and Teager Energy parameters., , , and . ICASSP, page 4613-4616. IEEE, (2012)A Fully Automatic Mid-Diastole Frame Detection in 2D Echocardiography Sequences., , , and . ICSPCS, page 1-7. IEEE, (2019)Acoustic Characteristics of Emotional Speech Using Spectrogram Image Classification., , , and . ICSPCS, page 1-5. IEEE, (2018)Detection of Clinical Depression in Adolescents' Speech During Family Interactions., , , , and . IEEE Trans. Biomed. Eng., 58 (3): 574-586 (2011)