Quality Assessment

Quality assessment (QA) focuses on objectively evaluating the quality of various data types, ranging from images and videos to text, audio, and even biometric samples and code. Current research emphasizes developing automated QA systems using deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, and hybrid architectures, often incorporating techniques like contrastive learning and attention mechanisms to improve accuracy and efficiency. These advancements are crucial for improving the reliability of numerous applications, from automated manufacturing quality control and medical image analysis to enhancing the user experience in multimedia and improving the trustworthiness of AI-generated content.