Efficient-Lightweight YOLO: Improving Small Object Detection in YOLO for Aerial Images

The most significant technical challenges of current aerial image object-detection tasks are the extremely low accuracy for detecting small objects that are densely distributed within a scene and the lack of semantic information. Moreover, existing detectors with large parameter scales are unsuitabl...

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Detalles Bibliográficos
Autores principales: Hu, Mengzi, Li, Ziyang, Yu, Jiong, Wan, Xueqiang, Tan, Haotian, Lin, Zeyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10385816/
https://www.ncbi.nlm.nih.gov/pubmed/37514717
http://dx.doi.org/10.3390/s23146423

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10385816/
https://www.ncbi.nlm.nih.gov/pubmed/37514717
http://dx.doi.org/10.3390/s23146423

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