Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...
The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
Recently, the French firm AVISIA, specialized in data and artificial intelligence, unveiled its prediction for the 2025 Ballon d'Or using the AVISIA Player Index. According to their model—built on a ...
Recently, the French firm AVISIA, specialized in data and artificial intelligence, unveiled its prediction for the 2025 Ballon d'Or using the AVISIA Player Index. According to their model—built on a ...
Thank you for this wonderful repo! I'm currently using emlearn to run a Random Forest classifier. I noticed that the generated code uses if-else conditions and return <class> statements to perform ...
This repository provides an efficient binary video classification pipeline using PyTorch, optimized for local GPU-enabled PCs. It includes preprocessing and model inference tools for classifying ...
ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...
ABSTRACT: In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat ...
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