A meta-methodology for preserving narrow objects when using spatial contextual classifiers for remote sensing data
Author:
Affiliation:
1. Image Processing Department, National Institute for Space Research (INPE), São José dos Campos, Brazil
Funder
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences
Link
https://www.tandfonline.com/doi/pdf/10.1080/01431161.2022.2145580
Reference48 articles.
1. Object based image analysis for remote sensing
2. Geographic Object-Based Image Analysis – Towards a new paradigm
3. The Classification of Noise-Afflicted Remotely Sensed Data Using Three Machine-Learning Techniques: Effect of Different Levels and Types of Noise on Accuracy
4. Implications of sensor design for coral reef detection: Upscaling ground hyperspectral imagery in spatial and spectral scales
5. Contextual Information-Preserved Architecture Learning for Remote-Sensing Scene Classification
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