| Full text | |
| Author(s): |
Neto, Eduardo B.
;
Faria, Fabio A.
;
de Oliveira, Amanda A. S.
;
Fazenda, Alvaro L.
Total Authors: 4
|
| Document type: | Journal article |
| Source: | PROCEEDINGS OF THE 2024 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, GECCO 2024; v. N/A, p. 9-pg., 2024-01-01. |
| Abstract | |
The conservation of tropical forests is a topic of significant social and ecological relevance due to their crucial role in the global ecosystem. Unfortunately, deforestation and degradation impact millions of hectares annually, necessitating government or private initiatives for effective forest monitoring. This study introduces a novel framework that employs the Univariate Marginal Distribution Algorithm (UMDA) to select spectral bands from Landsat-8 satellite optical sensor, optimizing the representation of deforested areas. This selection guides a semantic segmentation architecture, DeepLabv3+, enhancing its performance. Experimental results revealed several band compositions that achieved superior balanced accuracy compared to commonly adopted combinations for deforestation detection, utilizing segment classification via a Support Vector Machine (SVM). Moreover, the optimal band compositions identified by the UMDA-based approach improved the performance of the DeepLabv3+ architecture, surpassing state-of-the-art approaches compared in this study. The observation that a few selected bands outperform the total contradicts the data-driven paradigm prevalent in the deep learning field. Therefore, this suggests an exception to the conventional wisdom that 'more is always better'. (AU) | |
| FAPESP's process: | 15/24485-9 - Future internet for smart cities |
| Grantee: | Fabio Kon |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 23/00811-0 - EcoSustain: computer and data science for the environment |
| Grantee: | Antonio Jorge Gomes Abelém |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 14/50937-1 - INCT 2014: on the Internet of the Future |
| Grantee: | Fabio Kon |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 23/00782-0 - ForestEyes Project - Citizens monitoring deforestation |
| Grantee: | Álvaro Luiz Fazenda |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 17/25908-6 - Weakly supervised learning for compressed video analysis on retrieval and classification tasks for visual alert |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Research Grants - Research Partnership for Technological Innovation - PITE |
| FAPESP's process: | 18/23908-1 - Towards the Robustness in Deep Learning Architectures for e-Science Applications |
| Grantee: | Fabio Augusto Faria |
| Support Opportunities: | Scholarships abroad - Research |