Jan 9, 2021 · Abstract:Active fire detection in satellite imagery is of critical importance to the management of environmental conservation policies, ...
The dataset was split in two parts, and contains 10-band spectral images with associated outputs, produced by three well known handcrafted algorithms for active ...
Jan 9, 2021 · Active fire detection in satellite imagery is of critical importance to the management of environmental conservation policies, ...
Active fire detection in Landsat-8 imagery: a large-scale dataset and a deep-learning study. Authors: Gabriel Henrique de Almeida Pereira, Andre Minoro Fusioka.
An automated active fire detection framework using Sentinel-2 imagery that can serve as a powerful tool to deal with large volumes of high-resolution data ...
This study presented a deep convolutional neural network (CNN) “MultiScale-Net” for AFD in Landsat-8 datasets at the pixel level.
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Active fire detection in satellite imagery is of critical importance to the management of environmental conservation policies, supporting decision-making ...
Oct 22, 2024 · Stacking AFI with the three Landsat-8 bands led to fewer false negative (FN) pixels. Furthermore, our qualitative assessment revealed that these ...
This paper proposes a fully convolutional variational autoencoder (VAE) for features extraction from a large-scale dataset of fire images. 1. Paper · Code ...
This paper provides a comprehensive review of fire detection using deep learning, spanning from 1990 to 2023.