A Machine Learning Strategy Based on Kittler’s Taxonomy to Detect Anomalies and Recognize Contexts Applied to Monitor Water Bodies in Environments

A Machine Learning Strategy Based on Kittler’s Taxonomy to Detect Anomalies and Recognize Contexts Applied to Monitor Water Bodies in Environments

Environmental monitoring, such as analyses of water bodies to detect anomalies, is recognized worldwide as a task necessary to reduce the impacts arising from pollution. However, the large number of data available to be analyzed in different contexts, such as in an image time series acquired by sate...

Full description

Bibliographic Details
Main Authors: Maurício Araújo Dias, Giovanna Carreira Marinho, Rogério Galante Negri, Wallace Casaca, Ignácio Bravo Muñoz, Danilo Medeiros Eler
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Remote Sensing
Subjects:
remote sensing
Kittler’s taxonomy
anomaly detection
machine learning
time series
pattern recognition
Online Access:https://www.mdpi.com/2072-4292/14/9/2222

Internet

https://www.mdpi.com/2072-4292/14/9/2222

Similar Items