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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Giovanna, Castellano | - |
| dc.contributor.author | Nicola, Macchiarulo | - |
| dc.contributor.author | Berardina De, Carolis | - |
| dc.date.accessioned | 2023-03-30T08:43:51Z | - |
| dc.date.available | 2023-03-30T08:43:51Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | https://link.springer.com/article/10.1007/s11042-022-14050-0 | - |
| dc.identifier.uri | https://dlib.phenikaa-uni.edu.vn/handle/PNK/7343 | - |
| dc.description | CC BY | vi |
| dc.description.abstract | People use various nonverbal communicative channels to convey emotions, among which facial expressions are considered the most important ones. Thus, automatic Facial Expression Recognition (FER) is a fundamental task to increase the perceptive skills of computers, especially in human-computer interaction. Like humans, state-of-art FER systems are able to recognize emotions from the entire face of a person. | vi |
| dc.language.iso | en | vi |
| dc.publisher | Springer | vi |
| dc.subject | nonverbal communicative channels | vi |
| dc.subject | Facial Expression Recognition | vi |
| dc.title | Automatic facial emotion recognition at the COVID-19 pandemic time | vi |
| dc.type | Book | vi |
| Appears in Collections | OER - Công nghệ thông tin | |
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