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MSFFAL: Few-Shot Object Detection via Multi-Scale Feature Fusion and Attentive Learning
Few-shot object detection (FSOD) is proposed to solve the application problem of traditional detectors in scenarios lacking training samples. The meta-learning methods have attracted the researchers’ attention for their excellent generalization performance. They usually select the same class of supp...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099036/ https://www.ncbi.nlm.nih.gov/pubmed/37050671 http://dx.doi.org/10.3390/s23073609 |