Abstract: In multi-label learning, each instance in the training set is associated with a set of labels, and the task is to output a label set whose size is unknown a priori for each unseen instance.

The CPU and GPU confusion matrices are nearly identical. The prediction agreement between both implementations reached 99.82%, showing that the CUDA implementation preserved the classification ...

🚀 K-Nearest Neighbors (KNN) Classifier Implementation This repository demonstrates the implementation of the K-Nearest Neighbors (KNN) classification algorithm using Python and Scikit-learn. It walks ...

Abstract: Sea-surface small target detection is always a difficult problem in high-resolution maritime ubiquitous radars for complex characteristics of sea clutter, weak target returns, and diversity ...

The emerging convergence of AI-first design principles and environmental consciousness is reshaping how we think about ...

What about ChatGPT and related large AI Systems? How will they impact us all? As a longtime researcher in AI, I'm excited about the ways in which these new AI systems can improve our healthcare, ...

LR was chosen as the best algorithm for model construction, and the model demonstrated excellent performance, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.866, a ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...