Fusing multi-season UAS images with convolutional neural networks to map tree species in Amazonian forests-Reference-Cited by-同舟云学术

Fusing multi-season UAS images with convolutional neural networks to map tree species in Amazonian forests

Published:2022-11 Issue: Volume:71 Page:101815
ISSN:1574-9541
Container-title:Ecological Informatics
language:en
Short-container-title:Ecological Informatics

Author:

Veras Hudson Franklin Pessoa,Ferreira Matheus Pinheiro,da Cunha Neto Ernandes Macedo,Figueiredo Evandro Orfanó,Corte Ana Paula Dalla,Sanquetta Carlos Roberto

Funder

Nvidia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computer Science Applications,Ecological Modeling,Modeling and Simulation,Ecology,Ecology, Evolution, Behavior and Systematics

Reference25 articles.

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4. Encoder-decoder with atrous separable convolution for semantic image segmentation;Chen,2018

5. Measuring individual tree diameter and height using gatoreye high-density uav-lidar in an integrated crop-livestock-forest system;Dalla Corte;Remote Sens.,2020

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1. Tree species recognition from close-range sensing: A review;Remote Sensing of Environment;2024-11

2. Detecting Canopy Gaps in Uneven-Aged Mixed Forests through the Combined Use of Unmanned Aerial Vehicle Imagery and Deep Learning;Drones;2024-09-13

3. A Robust Dual-Mode Machine Learning Framework for Classifying Deforestation Patterns in Amazon Native Lands;Land;2024-09-04

4. Influence of temperate forest autumn leaf phenology on segmentation of tree species from UAV imagery using deep learning;Remote Sensing of Environment;2024-09

5. Individual canopy tree species maps for the National Ecological Observatory Network;PLOS Biology;2024-07-16