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Improve the Deep Learning Models in Forestry Based on Explanations and Expertise
In forestry studies, deep learning models have achieved excellent performance in many application scenarios (e.g., detecting forest damage). However, the unclear model decisions (i.e., black-box) undermine the credibility of the results and hinder their practicality. This study intends to obtain exp...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169801/ https://www.ncbi.nlm.nih.gov/pubmed/35677249 http://dx.doi.org/10.3389/fpls.2022.902105 |