Noise Estimation

Noise estimation aims to quantify and characterize noise in various data types, from images and audio to sensor readings and simulation outputs, ultimately improving data quality and model robustness. Current research emphasizes developing deep learning-based methods, including convolutional neural networks and autoencoders, for noise estimation across diverse applications, often integrating noise estimation with other tasks like denoising or model refinement in an iterative or joint learning framework. Accurate noise estimation is crucial for enhancing the reliability and performance of numerous applications, ranging from image processing and speech recognition to autonomous systems and medical image analysis.