Quality Regression Network

Quality regression networks are deep learning models designed to predict the quality of various data types, such as images and point clouds, by regressing to a numerical quality score. Current research focuses on improving the efficiency and robustness of these networks, often employing lightweight architectures and incorporating self-supervised learning techniques to reduce computational demands and enhance generalization across diverse datasets. These models are significant for automating quality assessment tasks in various fields, including image processing, remote sensing, and medical imaging, potentially streamlining workflows and improving the efficiency of quality control processes.