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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2022
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| Materias: | |
| 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 |