Anomaly Detection of Outlier Features from Spatio-temporal Databases of Landsat-8 Sensor, using Cloud Computing Platform
There has recently been a surge in the number of research articles published in peer-reviewed journals about machine learning and specialized algorithms for feature identification, feature selection, and feature extraction studies. This article distinguishes proof-of-concept applications from domains such as computer vision, remote sensing, image processing, and geospatial database technology. Using satellite imagery from the Landsat-8 sensor for rendering in multimedia and scalable vector processing modes, The article validates the fundamentals and principles of digital image analysis. The article describes the RSVM and DAFE scientific methods in the cloud computing platform in detail using a user-defined algorithm and a scientific approach. It is proposed to introduce data analytics nuances in distributed computing and parallel databases.
Author (S) Details
Department of Computer Science Engineering, Bharath Institute of Higher Education and Research, Selaiyur, Chennai, Tamilnadu, India.
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algorithms climate change data analytics feature extraction. feature selection Google earth engine linear discriminant analysis Machine learning predictive analytics supervised learning methods support vector machine