Yongli Chang

Orcid: 0000-0002-2803-6983

According to our database1, Yongli Chang authored at least 25 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Multi-Scale Visual Perception Based Progressive Feature Interaction Network for Stereo Image Super-Resolution.
IEEE Trans. Circuits Syst. Video Technol., March, 2024

Bidirectional Feature Aggregation Network for Stereo Image Quality Assessment Considering Parallax Attention-Based Binocular Fusion.
IEEE Trans. Broadcast., March, 2024

2023
Cross-resolution feature attention network for image super-resolution.
Vis. Comput., September, 2023

Coarse-to-Fine Feedback Guidance Based Stereo Image Quality Assessment Considering Dominant Eye Fusion.
IEEE Trans. Multim., 2023

Towards Top-Down Stereoscopic Image Quality Assessment via Stereo Attention.
CoRR, 2023

2022
Image super-resolution using progressive residual multi-dilated aggregation network.
Signal Image Video Process., 2022

Hierarchical multi-scale stereoscopic image quality assessment based on visual mechanism.
Signal Image Video Process., 2022

Stereo image quality assessment considering the difference of statistical feature in early visual pathway.
J. Vis. Commun. Image Represent., 2022

Stochastic configuration network based cascade generalized predictive control of main steam temperature in power plants.
Inf. Sci., 2022

2021
Quality assessment of screen content images based on multi-stage dictionary learning.
J. Vis. Commun. Image Represent., 2021

Multi-Dimension Aware Back Projection Network For Scene Text Detection.
Proceedings of the International Conference on Visual Communications and Image Processing, 2021

No-Reference Stereoscopic Image Quality Assessment Considering Binocular Disparity and Fusion Compensation.
Proceedings of the International Conference on Visual Communications and Image Processing, 2021

Binocular Visual Mechanism Guided No-Reference Stereoscopic Image Quality Assessment Considering Spatial Saliency.
Proceedings of the International Conference on Visual Communications and Image Processing, 2021

Quality Assessment of Screen Content Images Based on Convolutional Neural Network with Dual Pathways.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

No-Reference Stereoscopic Image Quality Assessment Based on the Human Visual System.
Proceedings of the IEEE International Conference on Acoustics, 2021

Image Super-Resolution Using Multi-Resolution Attention Network.
Proceedings of the IEEE International Conference on Acoustics, 2021

Multi-Scale Feature-Guided Stereoscopic Video Quality Assessment Based on 3d Convolutional Neural Network.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
No-reference stereoscopic image quality assessment based on cyclopean image and enhanced image.
Signal Image Video Process., 2020

No-Reference Stereoscopic Image Quality Assessment Based On Visual Attention Mechanism.
Proceedings of the 2020 IEEE International Conference on Visual Communications and Image Processing, 2020

No-Reference Stereoscopic Image Quality Assessment Considering Multi-loss Constraints.
Proceedings of the 2020 IEEE International Conference on Visual Communications and Image Processing, 2020

Stereo Image Quality Assessment Considering the Asymmetry of Statistical Information in Early Visual Pathway.
Proceedings of the 2020 IEEE International Conference on Visual Communications and Image Processing, 2020

2019
Adaptive Cyclopean Image-Based Stereoscopic Image-Quality Assessment Using Ensemble Learning.
IEEE Trans. Multim., 2019

No-Reference Stereoscopic Image Quality Assessment Based on Dilation Convolution.
Proceedings of the 2019 IEEE Visual Communications and Image Processing, 2019

Stereoscopic Image Quality Assessment Weighted Guidance by Disparity Map Using Convolutional Neural Network.
Proceedings of the 2019 IEEE Visual Communications and Image Processing, 2019

2018
Cyclopean Image Based Stereoscopic Image Quality Assessment by Using Sparse Representation.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018


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