AI helps find trees in a forest: Researchers achieve 3D forest reconstruction from remote sensing data

Existing algorithms can partially reconstruct the shape of a single tree from a clean point-cloud dataset acquired by ...
IEEE

Change Detection in Remote Sensing Optical Images Using a SPSA-Based Improved Random Forest Algorithm

Abstract: A precise change detection in the multi-temporal optical images is considered as a crucial task. Although a variety of machine learning-based change detection algorithms have been proposed ...
Scientific Research Publishing

Performance of Different Machine Learning Algorithms for Credit Risk Classification ()

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
Frontiers

Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery

Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...
Frontiers

Development of a predictive model for risk factors of multidrug-resistant bacterial pneumonia in critically ill post-neurosurgical patients

Background: Machine learning models have emerged as pivotal tools for enhancing the predictive accuracy of multidrug-resistant bacterial pneumonia (MDR-BP) risk in critically ill patients following ...
Scientific Research Publishing

Salman, H.A., Kalakech, A. and Steiti, A. (2024) Random Forest Algorithm Overview. Babylonian Journal of Machine Learning, 2024, 69-79.

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...
IEEE

Mental Health Classification and Diagnosis System Based on Random Forest Algorithm

Abstract: Boosting algorithm is a typical representative of ensemble learning models, which combines multiple weak learners into a strong learner to improve learning performance. The basic principle ...