Results 201 to 210 of about 129,605 (253)

Calibrated and Explainable CIN2+ Risk Stratification Using Routine Clinical Data: Development and External Validation. [PDF]

Int J Womens Health
Wu Y, Wang A.
europepmc   +1 more source

Impact of Simulated Artifacts on the Classification Performance of Apical Views in Transthoracic Echocardiography Using Convolutional Neural Networks. [PDF]

Bioengineering (Basel)
Orzeł-Łomozik GB, Łomozik Ł, Podolski M, Rożek M, Światlak K, Radwan W, Przybylska Z, Michalska P, Pruski M, Mizia-Stec K.   +9 more
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A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms

IEEE Transactions on Image Processing, 2006
Measurement of visual quality is of fundamental importance for numerous image and video processing applications, where the goal of quality assessment (QA) algorithms is to automatically assess the quality of images or videos in agreement with human quality judgments.
Alan C Bovik
exaly   +3 more sources

Full-reference image quality assessment based on image segmentation with edge feature

Signal Processing, 2018
Abstract Full-reference image quality assessment is widely used in many applications, such as image compression, image transmission and image mosaic. The visual masking effect has a significant impact on the perception of the human visual system, which is ignored in previous image quality assessments.
Zaifeng Shi, Qingjie Cao, Ke Pang
exaly   +2 more sources

Dynamic Receptive Field Generation for Full-Reference Image Quality Assessment

IEEE Transactions on Image Processing, 2020
Most full-reference image quality assessment (FR-IQA) methods advanced to date have been holistically designed without regard to the type of distortion impairing the image. However, the perception of distortion depends nonlinearly on the distortion type.
Woojae Kim, Anh-Duc Nguyen, Sanghoon Lee   +2 more
exaly   +3 more sources

Saliency-Guided Local Full-Reference Image Quality Assessment

Signals, 2022
Research and development of image quality assessment (IQA) algorithms have been in the focus of the computer vision and image processing community for decades.
Domonkos Varga
exaly   +3 more sources

A Combined Full-Reference Image Quality Assessment Method Based on Convolutional Activation Maps

Algorithms, 2020
The goal of full-reference image quality assessment (FR-IQA) is to predict the perceptual quality of an image as perceived by human observers using its pristine (distortion free) reference counterpart. In this study, we explore a novel, combined approach
Domonkos Varga
exaly   +3 more sources

Fine-Tuning of the Measure for Full Reference Image Quality Assessment

2021
In this paper, we proposed a new measure to solve the full reference image quality assessment problem. The core of the approach is known as peak signal-to-noise ratio improved with the estimation of local block-wise distortions, contrast, and saturation differences between test and referenced images.
Oleksii Gorokhovatskyi, Olena Peredrii
openaire   +1 more source