Exploratory Data Analysis of Heart Disease Prediction using Machine Learning Techniques-RS Algorithm
Abstract: Heart disease has become very common nowadays. Machine learning-based heart disease prediction has significant potential in clinical applications, enhancing early diagnosis and treatment.
Abstract: Submerged aquatic vegetation (SAV) is crucial for maintaining a clear-water state in lakes. Tracking the spatiotemporal changes in SAV is crucial for understanding the ecological evolution, ...
Abstract: The demand for 3D scanning of workpiece geometries in automated assembly within workshops is increasingly critical, playing a vital role in the process. Point cloud registration, as an ...
Abstract: Semantic segmentation of point clouds is an essential task for understanding the environment in autonomous driving and robotics. Recent range-based works achieve real-time efficiency, while ...
Abstract: In Unmanned Aerial Vehicle (UAV) systems, packet loss during sensor data transmission causes data missing, which reduces fault features in sensor signals and causes the accuracy of state ...
Abstract: The extensive adoption of cloud computing platforms in storing and processing data have brought forth a new age of efficiency in the way data is stored, processed and managed, requiring new ...
Introduction: Three-dimensional (3D) point clouds acquired by LiDAR are fundamental for applications such as autonomous navigation, mobile robotics, infrastructure inspection, and cultural-heritage ...
Abstract: This innovative practice full paper describes how to integrate generative Artificial Intelligence (AI) with Data Structures and Algorithm Analysis (CS2) homework at Oklahoma State University ...
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