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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

No-reference stereoscopic image quality assessment using a multi-task CNN and registered distortion representation
Yiqing Shi, Wen-Zhong Guo, Yuzhen Niu, et al.
Pattern Recognition (2019) Vol. 100, pp. 107168-107168
Closed Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

A no-Reference Stereoscopic Image Quality Assessment Network Based on Binocular Interaction and Fusion Mechanisms
Jianwei Si, Baoxiang Huang, Huan Yang, et al.
IEEE Transactions on Image Processing (2022) Vol. 31, pp. 3066-3080
Closed Access | Times Cited: 29
DeepRPN-BIQA: Deep architectures with region proposal network for natural-scene and screen-content blind image quality assessment
Mobeen Ur Rehman, Imran Fareed Nizami, Muhammad Majid
Displays (2021) Vol. 71, pp. 102101-102101
Closed Access | Times Cited: 28
SECS: An effective CNN joint construction strategy for breast cancer histopathological image classification
Dianzhi Yu, Jianwu Lin, Tengbao Cao, et al.
Journal of King Saud University - Computer and Information Sciences (2023) Vol. 35, Iss. 2, pp. 810-820
Open Access | Times Cited: 10
CoDIQE3D: A completely blind, no-reference stereoscopic image quality estimator using joint color and depth statistics
Ajay Kumar Reddy Poreddy, Peter A. Kara, Roopak R. Tamboli, et al.
The Visual Computer (2023) Vol. 39, Iss. 12, pp. 6743-6753
Closed Access | Times Cited: 9
Feature Sampling based on Multilayer Perceptive Neural Network for image quality assessment
Dharmalingam Muthusamy, Sandeep Sathyamoorthy
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 106015-106015
Closed Access | Times Cited: 8
Image Retargeting Quality Assessment Based on Registration Confidence Measure and Noticeability-Based Pooling
Yuzhen Niu, Shuai Zhang, Zhishan Wu, et al.
IEEE Transactions on Circuits and Systems for Video Technology (2020) Vol. 31, Iss. 3, pp. 972-985
Closed Access | Times Cited: 13
Deep belief network for solving the image quality assessment in full reference and no reference model
Dharmalingam Muthusamy, Sandeep Sathyamoorthy
Neural Computing and Applications (2022) Vol. 34, Iss. 24, pp. 21809-21833
Closed Access | Times Cited: 8
Staged-Learning: Assessing the Quality of Screen Content Images from Distortion Information
Jiachen Yang, Zilin Bian, Yang Zhao, et al.
IEEE Signal Processing Letters (2021) Vol. 28, pp. 1480-1484
Closed Access | Times Cited: 11
DistilIQA: Distilling Vision Transformers for no-reference perceptual CT image quality assessment
María Baldeon-Calisto, Francisco Rivera-Velastegui, Susana K. Lai-Yuen, et al.
Computers in Biology and Medicine (2024) Vol. 177, pp. 108670-108670
Closed Access | Times Cited: 1
Article Review: Integration of Science, Technology, Entrepreneurship in Learning Science through Bibliometric Analysis
Sri Jumini, Sutikno Madnasri, Edy Cahyono, et al.
Journal of Turkish Science Education (2022) Vol. 19, Iss. 4, pp. 1237-1253
Open Access | Times Cited: 7
PGF-BIQA: Blind image quality assessment via probability multi-grained cascade forest
Hao Liu, Ce Li, Shangang Jin, et al.
Computer Vision and Image Understanding (2023) Vol. 232, pp. 103695-103695
Closed Access | Times Cited: 3
Improved Equilibrium Optimizer for Short-Term Traffic Flow Prediction
Jeng‐Shyang Pan, Pei Hu, Tien-Szu Pan, et al.
Journal of Database Management (2023) Vol. 34, Iss. 1, pp. 1-20
Open Access | Times Cited: 3
A ‘Complete Blind’ No-Reference Stereoscopic Image Quality Assessment Algorithm
Balasubramanyam Appina
(2020), pp. 1-5
Closed Access | Times Cited: 7
Coarse-to-Fine Feedback Guidance Based Stereo Image Quality Assessment Considering Dominant Eye Fusion
Yongli Chang, Sumei Li, Anqi Liu, et al.
IEEE Transactions on Multimedia (2023) Vol. 25, pp. 8855-8867
Closed Access | Times Cited: 2
A full reference quality assessment method with fused monocular and binocular features for stereo images
Xiaojuan Hu, Jinxin Bai, Chunyi Chen, et al.
PeerJ Computer Science (2024) Vol. 10, pp. e2083-e2083
Open Access
Are Standard CNNs Good Enough for No-Reference Stereoscopic Image Quality Assessment?
Ishita Bardhan, Sumohana S. Channappayya, Abhik Banerjee, et al.
(2024), pp. 1-5
Closed Access
A No-Reference Stereoscopic Image Quality Assessment Based on Cartoon Texture Decomposition and Human Visual System
Yun Liu, Yan Bai, Yaohui Wang, et al.
Communications in computer and information science (2024), pp. 68-81
Closed Access
No-reference stereoscopic image quality assessment based on binocular collaboration
Hanling Wang, Xiao Ke, Wenzhong Guo, et al.
Neural Networks (2024) Vol. 180, pp. 106752-106752
Closed Access
Multitask Learning with Single Gradient Step Update for Task Balancing
Sungjae Lee, Youngdoo Son
arXiv (Cornell University) (2020)
Open Access | Times Cited: 3
Blind Quality Assessment of Images Containing Objects of Interest
Wentong He, Ze Luo
Sensors (2023) Vol. 23, Iss. 19, pp. 8205-8205
Open Access | Times Cited: 1
Two-stream interactive network based on local and global information for No-Reference Stereoscopic Image Quality Assessment
Yun Liu, Baoqing Huang, Guanghui Yue, et al.
Journal of Visual Communication and Image Representation (2022) Vol. 87, pp. 103586-103586
Closed Access | Times Cited: 2
Registration-based distortion and binocular representation for blind quality assessment of multiply-distorted stereoscopic image
Yiqing Shi, Wenzhong Guo, Yuzhen Niu, et al.
Communications in Information and Systems (2023) Vol. 23, Iss. 4, pp. 423-445
Open Access
No-reference stereo image quality evaluation method integrating monocular and binocular features
Jinxin Bai, Xiaojuan Hu
(2023), pp. 449-453
Closed Access
A Novel Blind Reference Method for Multi-Purpose Image Quality Assessment Tasks
Wenhao Sun, Yanxiang Hu, Bo Zhang, et al.
SSRN Electronic Journal (2022)
Closed Access
HFFNet: hierarchical feature fusion network for blind binocular image quality prediction
Yi Pan, Wujie Zhou, Lv Ye, et al.
Applied Optics (2022) Vol. 61, Iss. 26, pp. 7602-7602
Closed Access
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