This project was developed collaboratively by Priya Kumari and Nripendra Kumar as part of an Artificial Intelligence, Computer Vision, and Autonomous Systems learning initiative.

Based on clinical data from the first 24 hours of ICU admission, we used a two-stage feature selection process combining light gradient boosting machine (LightGBM) and Shapley additive explanation ...

DetectAnyLLM is an AI-generated text detection (i.e., Machine-Generated Text Detection) model based on the Fast-DetectGPT framework, optimized using DDL (Direct Discrepancy Learning). DDL is a novel ...

aDepartment of Medicine, University of California San Francisco, San Francisco, CA, USA bDepartment of Medicine, University of California Los Angeles, Los Angeles, CA, USA cDepartment of Medicine, ...

Abstract: This paper proposes a set of optimization algorithms to improve the correction accuracy and robustness in order to solve the problems of edge detection bias, feature point mismatching and ...

Abstract: In the field of fire prevention and industrial safety monitoring, it is very important to accurately and efficiently detect fires and deal with some factors that may affect fires in the ...

Significant predictors were selected on the training set using recursive feature elimination methods, followed by prediction model development using 7 machine learning algorithms (logistic regression, ...