Deep CNN-Based Blind Image Quality Predictor

Image recognition based on convolutional neural networks (CNNs) has recently been shown to deliver the state-of-the-art performance in various areas of computer vision and image processing. Nevertheless, applying a deep CNN to no-reference image quality assessment (NR-IQA) remains a challenging task...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2019-01, Vol.30 (1), p.11-24
Hauptverfasser:	Kim, Jongyoo, Nguyen, Anh-Duc, Lee, Sanghoon
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Computer vision Convolutional neural network (CNN) deep learning Distortion Error analysis Image processing Image quality image quality assessment (IQA) Machine learning Mathematical models Neural networks no-reference IQA (NR-IQA) Object recognition Quality assessment Quality control Reliability State of the art Training Visual system Visualization
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