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...

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Detalles Bibliográficos
Autores principales: Zhang, Tianzhao, Sun, Ruoxi, Wan, Yong, Zhang, Fuping, Wei, Jianming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099036/
https://www.ncbi.nlm.nih.gov/pubmed/37050671
http://dx.doi.org/10.3390/s23073609

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