Depression Assessment by Fusing High and Low Level Features from Audio, Video, and Text

Anastasia Pampouchidou, Olympia Simantiraki, Amir Fazlollahi, Matthew Pediaditis, Dimitris Manousos, Alexandros Roniotis, Georgios Giannakakis, Fabrice Meriaudeau, Panagiotis Simos, Kostas Marias, Fan Yang, Manolis Tsiknakis

Open source

DOI
10.1145/2988257.2988266
Published
2016-10-16
Container
Proceedings of the 6th International Workshop on Audio/Visual Emotion Challenge
Publisher
ACM
Open access
unknown

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BibTeX

@article{allodium:10.1145/2988257.2988266,
  title = {Depression Assessment by Fusing High and Low Level Features from Audio, Video, and Text},
  author = {Anastasia Pampouchidou and Olympia Simantiraki and Amir Fazlollahi and Matthew Pediaditis and Dimitris Manousos and Alexandros Roniotis and Georgios Giannakakis and Fabrice Meriaudeau and Panagiotis Simos and Kostas Marias and Fan Yang and Manolis Tsiknakis},
  year = {2016},
  journal = {Proceedings of the 6th International Workshop on Audio/Visual Emotion Challenge},
  doi = {10.1145/2988257.2988266},
  url = {https://doi.org/10.1145/2988257.2988266}
}

RIS

TY  - JOUR
TI  - Depression Assessment by Fusing High and Low Level Features from Audio, Video, and Text
AU  - Anastasia Pampouchidou
AU  - Olympia Simantiraki
AU  - Amir Fazlollahi
AU  - Matthew Pediaditis
AU  - Dimitris Manousos
AU  - Alexandros Roniotis
AU  - Georgios Giannakakis
AU  - Fabrice Meriaudeau
AU  - Panagiotis Simos
AU  - Kostas Marias
AU  - Fan Yang
AU  - Manolis Tsiknakis
PY  - 2016
JO  - Proceedings of the 6th International Workshop on Audio/Visual Emotion Challenge
DO  - 10.1145/2988257.2988266
UR  - https://doi.org/10.1145/2988257.2988266
ER  - 

APA

Pampouchidou, A., Simantiraki, O., Fazlollahi, A., Pediaditis, M., Manousos, D., Roniotis, A., Giannakakis, G., Meriaudeau, F., Simos, P., Marias, K., Yang, F., & Tsiknakis, M. (2016). Depression Assessment by Fusing High and Low Level Features from Audio, Video, and Text. Proceedings of the 6th International Workshop on Audio/Visual Emotion Challenge. https://doi.org/10.1145/2988257.2988266

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