Unsupervised Domain Adaptation for Mitigating Sensor Variability and Interspecies Heterogeneity in Animal Activity Recognition.

Ahn, Seong-Ho; Kim, Seeun; Jeong, Dong-Hwa

Ahn, Seong-Ho; Kim, Seeun; Jeong, Dong-Hwa.

Afiliación

Ahn SH; Department of Artificial Intelligence, The Catholic University of Korea, Bucheon 14662, Republic of Korea.
Kim S; School of Computer Science and Information Engineering, The Catholic University of Korea, Bucheon 14662, Republic of Korea.
Jeong DH; Department of Artificial Intelligence, The Catholic University of Korea, Bucheon 14662, Republic of Korea.

Animals (Basel) ; 13(20)2023 Oct 20.

Article en En | MEDLINE | ID: mdl-37894000

Palabras clave

animal activity recognition; deep adaptation network (DAN); deep reconstruction-classification network (DRCN); domain adversarial neural network (DANN); unsupervised domain adaptation (UDA); wearable devices

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Animals (Basel) Año: 2023 Tipo del documento: Article