Machine learning and SLIC for Tree Canopies segmentation in urban areas

Author:

Correa Martins José AugustoORCID,Menezes Geazy,Gonçalves Wesley,Sant’Ana Diego AndréORCID,Osco Lucas Prado,Liesenberg VeraldoORCID,Li Jonathan,Ma LingfeiORCID,Oliveira Paulo Tarso,Astolfi Gilberto,Pistori HemersonORCID,Junior José Marcato

Publisher

Elsevier BV

Subject

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

Reference49 articles.

1. Finger application using K-Curvature method and Kinect sensor in real-time;Abu Bakar,2015

2. SLIC superpixels;Achanta;IEEE Trans. Pattern Anal. Mach. Intell.,2012

3. An integrated object and machine learning approach for tree canopy extraction from UAV datasets;Adhikari;J. Indian Soc. Remote Sens.,2021

4. Contribution of ecosystem services to air quality and climate change mitigation policies: the case of urban forests in Barcelona, Spain;Baró;Ambio,2014

5. The lovász-softmax loss: A Tractable Surrogate for The Optimization of The Intersection-Over-Union Measure in Neural Networks;Berman,2018

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