Deep Convolutional Neural Models for Picture-Quality Prediction: Challenges and Solutions to Data-Driven Image Quality Assessment

Cited by (278)

Items 201–278 of 278

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3. Predicting the Empirical Distribution of Video Quality Scores Using Recurrent Neural Networks
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4. Improving IQA Performance Based on Deep Mutual Learning
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5. No Reference Image Quality Assessment Via Quality Difference Learning
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6. Blind Image Quality Assessment with Visual Sensitivity Enhanced Dual-Channel Deep Convolutional Neural Network
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7. FP-Nets for Blind Image Quality Assessment
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8. Portrait Quality Assessment using Multi-Scale CNN
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9. Visual-Language Multi-Task Blind Image Quality Assessment With Local Quality Weighting
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10. No‐reference image quality assessment via a dual‐branch residual network
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11. Research on aesthetic models based on neural architecture search
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12. Image Quality Assessment Based on Multi-Scale Representation and Shifting Transformer
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13. No-Reference Video Quality Assessment based on Convolutional Neural Network and Human Temporal Behavior
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14. A No-Reference Image Quality Comprehensive Assessment Method
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15. Collaborative Auto-encoding for Blind Image Quality Assessment
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16. Saliency-guided convolution neural network–transformer fusion network for no-reference image quality assessment
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17. A restoration method for distorted comics to improve comic contents identification
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18. Learning Based Hybrid No-Reference Video Quality Assessment of Compressed Videos
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19. No-Reference Image Quality Assessment via Multi-order Perception Similarity
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20. MP2020: Visual quality assessment database for macro photography images
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21. Predicting perceptual quality of images in realistic scenario using deep filter banks
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22. Integrating Disparate Sources of Experts for Robust Image Denoising.
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23. Controllable List-wise Ranking for Universal No-reference Image Quality Assessment
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24. Image quality assessment by enabling inter-patch message passing via graph convolutional networks
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25. Automated Testing of Graphics Units by Deep-Learning Detection of Visual Anomalies
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26. An Adaptive Unsupervised Method for Powerline Aerial Image Quality Assessment
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27. The Effects of Different Image Parameters on Human Action Recognition Models Trained on Real and Synthetic Image Data
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28. Learning to Predict Image‐based Rendering Artifacts with Respect to a Hidden Reference Image
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29. In-the-wild No-Reference Image Quality Assessment using Deep Convolutional Neural Networks
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30. Image Quality Assessment by Combining Masking Texture and Perceptual Color Difference Model
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31. Understanding the perceived quality of video predictions
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32. A Temporal Statistics Model For UGC Video Quality Prediction
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33. Development of a No-Reference CT Image Quality Assessment Method Using RadImageNet Pre-trained Deep Learning Models
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34. Deep Blind Image Quality Assessment by Learning Sensitivity Map
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35. Two-channel deep recursive multi-scale network based on multi-attention for no-reference image quality assessment
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36. No-reference video quality assessment based on spatiotemporal slice images and deep convolutional neural networks
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37. Weakly Supervised Learning for Blind Image Quality Assessment
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38. SEM Image Quality Assessment Based on Texture Inpainting
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39. Neural network solution for a real-time no-reference video quality assessment of H.264/AVC video bitstreams
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40. CPL-IQA: Blind image quality assessment via convolutional prototype learning
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41. Automated quality evaluation of Cervical Cytopathology Whole Slide Images based on content analysis
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42. 5GMediaHUB QoS/QoE Monitoring Engine
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43. AI-Driven Video Quality Assessment and Enhancement Techniques
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44. Towards automated quality curation of video collections from a realistic perspective
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45. USRRM: Pairwise Ranking and Scoring Images Using Its Aesthetic Quality
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46. A Novel Contractive GAN Model for a Unified Approach Towards Blind Quality Assessment of Images from Heterogeneous Sources
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47. On the Agreement of Deep Neural Networks with the Brain in Encoding Visual Stimuli: Implications for Image Quality Assessment
    Saeed Mahmoudpour, Peter Schelkens · 2023 · IEEE International Conference on Digital Signal Processing (DSP)
48. [For Your Consideration]
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49. Multivariate Statistics for Blind Image Quality Applications
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50. Deep Convolutional Neural Network Applied to Quality Assessment for Video Tracking
    Roger Gomez Nieto, Eugenio Tamura Morimitsu · 2018 · arXiv (Cornell University)
51. RANK-SMOOTHED PAIRWISE LEARNING IN PERCEPTUAL QUALITY ASSESSMENT
    Hossein Talebi, Ehsan Amid, Peyman Milanfar, Manfred K. Warmuth · 2020 · arXiv (Cornell University)
52. Transfer Entropy Based Causality From Head Motion To Eye Movement
    Zezhong Lv, Qing Xu, Klaus Schoeffmann, Simon Parkinson · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
53. Visual saliency computation and quality evaluation via deep learning
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54. AesTech - A Deep Learning Based Image Evaluation Model
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55. Convolutional neural network for distortion Classification in face images.
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56. Bibliography
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57. Introduction to smart O&G industry
    Razin Farhan Hussain, Ali Mokhtari, Ali Ghalambor, Mohsen Amini Salehi · 2022 · Elsevier eBooks
58. A Document Image Quality Assessment Algorithm Based on Information Entropy in Text Region
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59. Challenges and Solutions of the Application of Data-Driven Technology in Network 3D Game Design
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60. Quadratic Polynomial Residual Network for No-Reference Image Quality Assessment
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61. Hybrid CNN-Transformer and Multi-Region Selective Features for No-Reference Screen Content Image Quality Assessment
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62. Image Quality Assessments by Leveraging Diverse Visual Tasks
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63. Semi-Supervised Multi-Task Learning for Interpretable Quality Assessment of Fundus Images
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64. CNN based bilinear and spatial pyramid pooling for blind image quality assessment
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65. An improved accuracy to find online pharmacies by comparing convolutional neural network with SVM
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66. Unsupervised Normative Learning for Quality Assessment on Diffusion MRI
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67. Meta-learning enhanced global–local feature fusion for image quality assessment
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68. PPD-IQA: A Bottom-Up and Top-Down Combined Approach for Blind Image Quality Assessment via Prototype-Prompted Disentangling
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69. Prior-Guided Test Time Adaptation for Blind Image Quality Assessment
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70. Semi-supervised multi-task learning for interpretable quality assessment of fundus images
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71. The Marvelous Advances of Artificial Intelligence with Computer Vision on Occupational Health and Safety in Manufacturing Environments: A Systematic Literature Review
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72. Deep transfer learning for intrusion and anomaly detection
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74. Analytical validation of Smilo.ai: evaluating an AI-driven platform for automated oral health screening and global diagnostic accessibility
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75. Image Processing and Deep Learning Based Illumination Intensity (Lux) Estimation: An Application with MobileNetV2 Architecture
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76. From Pixels to Plans: A Review of Latent-Space Future Prediction
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77. Meta-learning based on Hypernetworks for State of Health prediction of lithium-ion batteries under data scarcity
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78. Region-Aware Degradation-Conditioned Vision-Language Learning for Blind Image-Quality Assessment of Power Field-Operation Imagery
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