These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

134 related articles for article (PubMed ID: 28574353)

  • 1. dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs.
    Kede Ma ; Wentao Liu ; Tongliang Liu ; Zhou Wang ; Dacheng Tao
    IEEE Trans Image Process; 2017 Aug; 26(8):3951-3964. PubMed ID: 28574353
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Learning to rank for blind image quality assessment.
    Gao F; Tao D; Gao X; Li X
    IEEE Trans Neural Netw Learn Syst; 2015 Oct; 26(10):2275-90. PubMed ID: 25616080
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A feature-enriched completely blind image quality evaluator.
    Lin Zhang ; Lei Zhang ; Bovik AC
    IEEE Trans Image Process; 2015 Aug; 24(8):2579-91. PubMed ID: 25915960
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Blind image quality assessment using joint statistics of gradient magnitude and Laplacian features.
    Xue W; Mou X; Zhang L; Bovik AC; Feng X
    IEEE Trans Image Process; 2014 Nov; 23(11):4850-62. PubMed ID: 25216482
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild.
    Zhang W; Ma K; Zhai G; Yang X
    IEEE Trans Image Process; 2021; 30():3474-3486. PubMed ID: 33661733
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Continual Learning for Blind Image Quality Assessment.
    Zhang W; Li D; Ma C; Zhai G; Yang X; Ma K
    IEEE Trans Pattern Anal Mach Intell; 2023 Mar; 45(3):2864-2878. PubMed ID: 35635807
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Blind Image Quality Assessment Based on High Order Statistics Aggregation.
    Jingtao Xu ; Peng Ye ; Qiaohong Li ; Haiqing Du ; Yong Liu ; Doermann D
    IEEE Trans Image Process; 2016 Sep; 25(9):4444-4457. PubMed ID: 27362977
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Waterloo Exploration Database: New Challenges for Image Quality Assessment Models.
    Kede Ma ; Zhengfang Duanmu ; Qingbo Wu ; Zhou Wang ; Hongwei Yong ; Hongliang Li ; Lei Zhang
    IEEE Trans Image Process; 2017 Feb; 26(2):1004-1016. PubMed ID: 27893392
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Multiscale Approach to Deep Blind Image Quality Assessment.
    Liu M; Huang J; Zeng D; Ding X; Paisley J
    IEEE Trans Image Process; 2023 Feb; PP():. PubMed ID: 37027757
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Active Fine-Tuning From gMAD Examples Improves Blind Image Quality Assessment.
    Wang Z; Ma K
    IEEE Trans Pattern Anal Mach Intell; 2022 Sep; 44(9):4577-4590. PubMed ID: 33830918
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Utilizing image scales towards totally training free blind image quality assessment.
    Saha A; Wu QM
    IEEE Trans Image Process; 2015 Jun; 24(6):1879-92. PubMed ID: 25775489
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Task-Specific Normalization for Continual Learning of Blind Image Quality Models.
    Zhang W; Ma K; Zhai G; Yang X
    IEEE Trans Image Process; 2024; 33():1898-1910. PubMed ID: 38451761
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Unsupervised blind image quality assessment via joint spatial and transform features.
    Yang C; He Q; An P
    Sci Rep; 2023 Jul; 13(1):10865. PubMed ID: 37407688
    [TBL] [Abstract][Full Text] [Related]  

  • 14. End-to-End Blind Image Quality Assessment Using Deep Neural Networks.
    Ma K; Liu W; Zhang K; Duanmu Z; Wang Z; Zuo W
    IEEE Trans Image Process; 2018 Mar; 27(3):1202-1213. PubMed ID: 29220321
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Exploiting Unlabeled Data in CNNs by Self-Supervised Learning to Rank.
    Liu X; Weijer JV; Bagdanov AD
    IEEE Trans Pattern Anal Mach Intell; 2019 Aug; 41(8):1862-1878. PubMed ID: 30794168
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Blind quality assessment of authentically distorted images.
    Celona L; Schettini R
    J Opt Soc Am A Opt Image Sci Vis; 2022 Jun; 39(6):B1-B10. PubMed ID: 36215522
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Magnetic Resonance Image Quality Assessment by Using Non-Maximum Suppression and Entropy Analysis.
    Obuchowicz R; Oszust M; Bielecka M; Bielecki A; Piórkowski A
    Entropy (Basel); 2020 Feb; 22(2):. PubMed ID: 33285994
    [TBL] [Abstract][Full Text] [Related]  

  • 18. BM-IQE: An Image Quality Evaluator with Block-Matching for Both Real-Life Scenes and Remote Sensing Scenes.
    Xu N; Ma D; Ren G; Huang Y
    Sensors (Basel); 2020 Jun; 20(12):. PubMed ID: 32575567
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Reduced-Reference Quality Assessment Based on the Entropy of DWT Coefficients of Locally Weighted Gradient Magnitudes.
    Golestaneh SA; Karam L
    IEEE Trans Image Process; 2016 Nov; 25(11):5293-5303. PubMed ID: 28113627
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Universal blind image quality assessment metrics via natural scene statistics and multiple kernel learning.
    Gao X; Gao F; Tao D; Li X
    IEEE Trans Neural Netw Learn Syst; 2013 Dec; 24(12):2013-26. PubMed ID: 24805219
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.