Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.12008/34071
How to cite
| Title: | A brief analysis of the holistically-nested edge detector |
| Authors: | Grompone von Gioi, Rafael Randall, Gregory |
| Type: | Artículo |
| Keywords: | Image edge detection, Neural network, VGG16 |
| Issue Date: | 2022 |
| Abstract: | This work describes the HED method for edge detection. HED uses a neural network based on a VGG16 backbone, supplemented with some extra layers for merging the results at different scales. The training was performed on an augmented version of the BSDS500 dataset. We perform a brief analysis of the results produced by HED, highlighting its quality but also indicating its limitations. Overall, HED produces state-of-the-art results. |
| Description: | Este artículo está disponible en línea con materiales complementarios, software, conjuntos de datos y demostración en https://doi.org/10.5201/ipol.2022.422 |
| Publisher: | Centre Borelli, ENS Paris-Saclay; DMI, Universitat de les Illes Balears; Fing, Universidad de la República. |
| IN: | IPOL. Journal Image Processing On Line, no 12, Oct 2022, pp. 369-377 |
| Citation: | Grompone von Gioi, R. y Randall, G. "A brief analysis of the holistically-nested edge detector". IPOL. Journal Image Processing On Line. [en línea]. 2022, no 12, pp. 369-377. DOI: 10.5201/ipol.2022.422 |
| ISSN: | 2105–1232 |
| Academic department: | Procesamiento de Señales |
| Investigation group: | Tratamiento de Imágenes |
| License: | Licencia Creative Commons Atribución - No Comercial - Compartir Igual (CC - By-NC-SA 4.0) |
| Appears in Collections: | Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica |
This item is licensed under a Creative Commons License
