A large evaluation using NHANES data shows that machine learning imputation methods can reconstruct missing values more ...
A conditional generative adversarial network tuned by an Adaptive Jaya Algorithm generated synthetic forest images that, ...
This note is very long. If you are short on time, I would be happy if you could at least read the "Afterword" at the ...
Forest canopies are more than just a ceiling of leaves—they are living archives of ecosystem health, carbon storage, and ...
Kipu Quantum demonstrated a novel method for molecular toxicity classification using analog quantum feature extraction on ...
That makes Klein an additional option for local AI imagery, but the ability to download its weights does not give every ...
Abstract: Accurate recognition of road surface type and condition is essential for intelligent vehicle systems. While Support Vector Machines (SVM) and Random Forests (RF) offer complementary ...
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: Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches ...
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 ...
Abstract: Predicting whether an earthquake will generate a tsunami is critical for early warning systems and disaster mitigation. In this study, we present an AI-driven approach to classify ...
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