Results 131 to 140 of about 4,120 (175)

Towards Quality Assessment for Arbitrary Translational 6DoF Video: Subjective Quality Database and Objective Assessment Metric. [PDF]

Entropy (Basel)
Jin C, Chen Y.
europepmc   +1 more source

Examining the role of compression in influencing AI-generated image authenticity. [PDF]

Sci Rep
Fang X, Chen P, Wang M, Wang S.
europepmc   +1 more source

No-reference image quality assessment based on global awareness. [PDF]

PLoS One
Hu Z, Yang G, Du Z, Huang X, Zhang P, Liu D.   +5 more
europepmc   +1 more source

Evaluating the performance of an artificial intelligence-based electronic reader for malaria rapid diagnostic tests across Benin, Côte d'Ivoire, Nigeria and Uganda. [PDF]

Malar J
Lindblade KA, Ngufor C, Yavo W, Atobatele S, Mpimbaza A, Ssewante N, Akpiroroh E, Konaté-Toure A, Ahogni I, Kpemasse A, Tanoh AM, Ntadom G, Opigo J, Zobrist S, Griffith K, Humes M.   +15 more
europepmc   +1 more source

Ultrawidefield-to-Conventional Fundus Image Translation with Scaled Feature Registration and Distorted Vessel Correction. [PDF]

Bioengineering (Basel)
Kim J, Bum J, Le DT, Son CH, Lee EJ, Han JC, Choo H.   +6 more
europepmc   +1 more source

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QL-IQA: Learning distance distribution from quality levels for blind image quality assessment

Signal Processing: Image Communication, 2022
Abstract Recently, blind image quality assessment (BIQA) has been intensively studied with deep learning. However, the limited quality-annotated datasets restrict its further development. Although patch-based methods have been leveraged to generate more training data, they usually assign the image quality score to all patches in an image ...
Rui Gao, Ziqing Huang, Shiguang Liu
openaire   +1 more source

Deep blind image quality assessment by employing FR-IQA

2017 IEEE International Conference on Image Processing (ICIP), 2017
In this paper, we propose a convolutional neural network (CNN)-based no-reference image quality assessment (NR-IQA). Though deep learning has yielded superior performance in a number of computer vision studies, applying the deep CNN to the NR-IQA framework is not straightforward, since we face a few critical problems: 1) lack of training data; 2 ...
Jongyoo Kim, Sanghoon Lee
openaire   +1 more source

Illumination Classification based on No-Reference Image Quality Assessment (NR-IQA)

Proceedings of the 2019 Asia Pacific Information Technology Conference, 2019
In this paper, we propose an approach to categorize an image's illumination using no-reference image quality assessment metric (NR-IQA). Two NR-IQA metric (image entropy (IE) and standard deviation (SD), and mean of the pixel value (Mean) were used to categorize the illumination.
Syed Mohd Zahid Syed Zainal Ariffin, Nursuriati Jamil   +1 more
openaire   +1 more source

BN-IQA: A Rapid Image Quality Assessment based on Blue Noise Dithering

2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW), 2019
A simplistic full reference image quality assessment (IQA) based on digital halftone (DH) technique is proposed. The method exploits the properties of ordered dithering screens of digital halftoning and attempt to capture the quality degradation by evaluating its halftone output.
Jing-Ming Guo, S. Sankarasrinivasan
openaire   +1 more source