Precision Meets Speed: An Attention Encoder-Decoder Network for Deforestation Segmentation

Deforestation remains a critical global environmental concern, requiring effective monitoring approaches. This letter presents a novel attention-powered encoder-decoder neural network designed to address the key challenges in deforestation mapping, including scale heterogeneity, temporal dynamics, a...

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Veröffentlicht in:	IEEE geoscience and remote sensing letters Jg. 22; S. 1 - 5
Hauptverfasser:	Benvenuto, Giovana A., Negri, Rogerio G., Colnago, Marilaine, Frery, Alejandro C., Casaca, Wallace
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Attention mechanisms Coders Computational efficiency Computer applications Computer architecture Computing costs Deep learning Deforestation Environmental perception Feature extraction Heterogeneity Monitoring Neural networks Remote sensing remote sensing (RS) Training
ISSN:	1545-598X, 1558-0571
Online-Zugang:	Volltext
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