Brain-Inspired Domain-Incremental Adaptive Detection for Autonomous Driving

Most existing methods for unsupervised domain adaptation (UDA) only involve two domains, i.e., source domain and the target domain. However, such trained adaptive models have poor performance when applied to a new domain without learning. Moreover, using UDA methods to adapt from the source domain t...

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Detalles Bibliográficos
Autores principales: Liang, Weihao, Gan, Lu, Wang, Pengfei, Meng, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9241162/
https://www.ncbi.nlm.nih.gov/pubmed/35783366
http://dx.doi.org/10.3389/fnbot.2022.916808

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9241162/
https://www.ncbi.nlm.nih.gov/pubmed/35783366
http://dx.doi.org/10.3389/fnbot.2022.916808

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