A Purdue University digital forestry team has created a computational tool to obtain and analyze urban tree inventories on ...
Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...
Urban landscapes could be cooled by up to 3.5 degrees using a QUT-developed AI-based tool that optimizes where trees and which species are planted to make cities cooler, greener and more resilient in ...
RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.
Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...
This paper first discusses the storage structure of trees, selects a convenient storage method for solving the nullity of trees, and then applies the relationship between the maximum matching number ...
Computer vision systems combined with machine learning techniques have demonstrated success as alternatives to empirical methods for classification and selection. This study aimed to classify tomatoes ...
Abstract: We proposed a novel Kinematic Batch Informed Trees algorithm (K-BIT*) to solve problems of the low efficiency, poor geometric smoothness and local optimum when conducting path planning for ...
WEST LAFAYETTE, Ind. — Trees compete for space as they grow. A tree with branches close to a wall will develop differently from one growing on open ground. Now everyone from urban planners and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results