Blind image quality assessment: A fuzzy neural network for opinion score distribution prediction
Image quality assessment (IQA) has always been a popular research topic. There have
been many methods proposed for predicting image quality, also known as the mean opinion …
been many methods proposed for predicting image quality, also known as the mean opinion …
Hierarchical curriculum learning for no-reference image quality assessment
Despite remarkable success has been achieved by convolutional neural networks (CNNs) in
no-reference image quality assessment (NR-IQA), there still exist many challenges in …
no-reference image quality assessment (NR-IQA), there still exist many challenges in …
Blind image quality assessment for in-the-wild images by integrating distorted patch selection and multi-scale-and-granularity fusion
J **-based motion deblurring methods lack the regularization of prior
knowledge, resulting in an over-reliance on the training data and limited generalization …
knowledge, resulting in an over-reliance on the training data and limited generalization …
Efficient Deep-Detector Image Quality Assessment Based on Knowledge Distillation
An efficient deep-detector image quality assessment (EDIQA) is proposed to address the
need for an objective and efficient medical image quality assessment (IQA) without requiring …
need for an objective and efficient medical image quality assessment (IQA) without requiring …
Learning with Noisy Low-Cost MOS for Image Quality Assessment via Dual-Bias Calibration
Learning based image quality assessment (IQA) models have obtained impressive
performance with the help of reliable subjective quality labels, where mean opinion score …
performance with the help of reliable subjective quality labels, where mean opinion score …