Título:
A brief analysis of the iterative next boundary detection network for tree rings delineation in images of Pinus taeda.
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Autor:
Marichal, Henry
Randall, Gregory
Randall, Gregory
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Tipo de documento:
Preprint
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Palabras clave:
Tree-rings
U-Net
Cross-section
Segmentation
U-Net
Cross-section
Segmentation
Descriptores:
Año de publicación:
2024
Contenido:
Resumen:
This work presents the INBD network proposed by Gillert et al. [1] and studies its application for delineating tree rings in RGB images of Pinus taeda cross sections captured by a smartphone (UruDendro dataset), which are images with different characteristics from the ones used to train the method. The INBD network operates in two stages: first, it segments the background, pith, and ring boundaries. In the second stage, the image is transformed into polar coordinates and ring boundaries are iteratively segmented from the pith to the bark. Both stages are based on the U-Net architecture. The method achieves an F-Score of 77.5, a mAR of 0.540, and an ARAND of 0.205 on the evaluation set. The code for the experiments is available at https://github.com/hmarichal93/mlbrief_inbd.
Descripción:
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Editorial:
arXiv
EN:
Computer Science. Computer Vision and Pattern Recognition (cs.CV), arXiv:2408.14343v1, aug. 2024, pp. 1-10.
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Citación:
Marichal, H. y Randall, G. A brief analysis of the iterative next boundary detection network for tree rings delineation in images of Pinus taeda. [Preprint]. Publicado en: Computer Science. Computer Vision and Pattern Recognition (cs.CV), 2024, pp. 1-10. arXiv:2408.14343v1. DOI: 10.48550/arXiv.2408.14343.
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Departamento académico:
Procesamiento de Señales
Grupo de investigación:
Tratamiento de Imagenes
Licencia:
Licencia Creative Commons Atribución - No Comercial - Compartir Igual (CC - By-NC-SA 4.0)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| MR24.pdf | Preprint | 8.24 MB | Adobe PDF |