| Texto completo | |
| Autor(es): |
da Silva, Mateus Pinto
;
Schaefer, Mariana A. R.
;
Oliveira, Hugo N.
;
Reis, Julio C. S.
;
Nunes, Ian M.
;
dos Santos, Jefersson A.
Número total de Autores: 6
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2024 37TH SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES, SIBGRAPI 2024; v. N/A, p. 6-pg., 2024-01-01. |
| Resumo | |
Deep Learning based on Remote Sensing has become a powerful tool to increase agricultural productivity, mitigate the effects of climate change, and monitor deforestation. However, there is a lack of standardization and appropriate taxonomic classification of the literature available in the context of informatics. Against this background, this survey provides an overview of the relevant literature categorized into five main applications: Parcel Segmentation, Crop Mapping, Crop Yielding, Land Use and Land Cover, and Change Detection. We address notable trends, including transitioning from traditional to deep learning, convolutional models, recurrent and attention-based models, generative strategies, and self-supervised pre-training. The supplementary material also includes a comprehensive review of publicly available datasets for these applications. We hope that our work can be useful as a guide for future work in this context. (AU) | |
| Processo FAPESP: | 15/22308-2 - Representações intermediárias em Ciência Computacional para descoberta de conhecimento |
| Beneficiário: | Roberto Marcondes Cesar Junior |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |
| Processo FAPESP: | 20/06744-5 - Deep learning e representações intermediárias para análise de imagens pediátricas |
| Beneficiário: | Hugo Neves de Oliveira |
| Modalidade de apoio: | Bolsas no Brasil - Pós-Doutorado |
| Processo FAPESP: | 17/50236-1 - Análise espaço-temporal de imagens de ressonância magnética |
| Beneficiário: | Roberto Marcondes Cesar Junior |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |