Swin-Transformer-Based YOLOv5 for Small-Object Detection in Remote Sensing Images

This study aimed to address the problems of low detection accuracy and inaccurate positioning of small-object detection in remote sensing images. An improved architecture based on the Swin Transformer and YOLOv5 is proposed. First, Complete-IOU (CIOU) was introduced to improve the K-means clustering...

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Detalles Bibliográficos
Autores principales: Cao, Xuan, Zhang, Yanwei, Lang, Song, Gong, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098803/
https://www.ncbi.nlm.nih.gov/pubmed/37050694
http://dx.doi.org/10.3390/s23073634

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098803/
https://www.ncbi.nlm.nih.gov/pubmed/37050694
http://dx.doi.org/10.3390/s23073634

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