Tilting Angle

"Tilting angle," in its various contexts, refers to the measurement and utilization of angular deviations from a reference orientation. Current research focuses on improving the accuracy and robustness of tilting angle estimation across diverse applications, employing techniques such as convolutional neural networks (CNNs) for image and sensor data analysis, exponential tilting for improved model robustness and fairness, and diffusion models for handling incomplete or noisy data in reconstruction problems. These advancements have significant implications for fields ranging from robotics and autonomous driving (improving object manipulation and navigation) to medical imaging (enhancing the quality and efficiency of CT scans) and machine learning (increasing model accuracy and reliability).