Combining drone data and machine learning can help cover more ground in monitoring forest soil health, University of Alberta ...
Researchers review how AI combines mineral chemistry, geophysical surveys, satellite imagery, geological maps, and text to ...
Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...
ABSTRACT: Sugar content in cashew apples is a critical indicator of fruit quality and maturity, directly influencing processing and market value. This study explores the use of spectral indices ...
The lack of precise, autonomous tools for monitoring and classifying cattle behavior limits farmers’ ability to make proactive and informed decisions regarding grazing and herd management. Currently, ...
“I woke up this morning and went out onto my hotel balcony. I shouted ‘You Reds!’ and, immediately, somebody shouted it back from down the street. I put my shirt on and my bucket hat, and I felt ready ...
Abstract: Intelligent transportation systems are increasingly reliant on precise and efficient vehicle classification to support traffic management, safety applications, and infrastructure planning.
ABSTRACT: Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral ...
The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.
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