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Action unit classification for facial expression recognition using active learning and SVM

Description: Article utilizing active learning and support vector machine (SVM) algorithms to classify facial action units (AU) for human facial expression recognition. Experimental results show that the proposed algorithm can effectively suppress correlated noise and achieve higher recognition rates than principal component analysis and a human observer on seven different facial expressions.
Date: April 4, 2021
Creator: Yao, Li; Wan, Yan & Xu, Bugao
Item Type: Refine your search to only Article
Partner: UNT College of Engineering

Interview about health practices

Description: This is an interview about traditional health practices in the Lai community. The interviewee, born in 1962, is originally from Falam and speaks Hakha, Falam, Mizo, Kawl, and English. Interviews were collected as part of the Linguistically Underserved Communities and Health (LUCAH) project, which aims to make health information more accessible and culturally relevant for the Chin refugee community in order to ensure that they are getting clear and accurate information.
Date: April 4, 2021
Duration: 49 minutes 24 seconds
Item Type: Refine your search to only Sound
Partner: UNT College of Information
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