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Abstract: It is the comparative study of three algorithms based on machine learning approaches RF), Support Vector Machine (SVM) and Classification and Regression Tree (CART)) in Landsat 8 satellite ...

Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...

Abstract: Identification of naval mines is a very tedious task due to turbulent nature in ocean and the varying deployment of mines, which differ by location and type, such as buoyant mines, moored ...

Optimiz-rs provides blazingly fast, production-ready implementations of advanced optimization and statistical inference algorithms. Built with Rust for maximum performance and exposed to Python ...

Monitoring of natural resources is a major challenge that remote sensing tools help to facilitate. The Sissili province in Burkina Faso is a territory that includes significant areas dedicated for the ...

As a Navy mathematician in the 1950s and beyond, she played an unheralded but foundational role in making possible the global satellite-based mapping system. Dr. Gladys West spent her career in ...

Comparison of the ANFIS algorithm with classical machine learning models in wine quality classification - dawidolko/Comparison-ANFIS-Classical-Machine-Learning-Models-Python ...

Individual sensor systems have limitations in the complex task of classifying shredded tobacco. This study aims to overcome these limitations by developing a novel evolutionary algorithm-based feature ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...