Results 31 to 40 of about 4,189 (182)

Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Accepted to IEEE/CVF CVPR 2023. Code will be released post conference in July 2023.
Saha, Avinab, Mishra, Sandeep, Bovik, Alan C.   +2 more
openaire   +2 more sources

Blind Quality Assessment of Images Containing Objects of Interest

Sensors, 2023
To monitor objects of interest, such as wildlife and people, image-capturing devices are used to collect a large number of images with and without objects of interest.
Wentong He, Ze Luo
doaj   +1 more source

Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank [PDF]

, 2019
For many applications the collection of labeled data is expensive laborious. Exploitation of unlabeled data during training is thus a long pursued objective of machine learning.
Bagdanov, Andrew D., Liu, Xialei, van de Weijer, Joost   +2 more
core   +2 more sources

No-Reference Blurred Image Quality Assessment by Structural Similarity Index

Applied Sciences, 2018
No-reference (NR) image quality assessment (IQA) objectively measures the image quality consistently with subjective evaluations by using only the distorted image.
Haopeng Zhang, Bo Yuan, Bo Dong, Zhiguo Jiang   +3 more
doaj   +1 more source

ER-IQA: Boosting Perceptual Quality Assessment Using External Reference Images

, 2021
10 pages, 5 figures; Modified content and updated ...
Guo, Jingyu, Wang, Wei, Yang, Wenming, Liao, Qingmin, Zhou, Jie   +4 more
openaire   +2 more sources

Siamese-Network-Based Learning to Rank for No-Reference 2D and 3D Image Quality Assessment

IEEE Access, 2019
2D image quality assessment (IQA) and stereoscopic 3D IQA are considered as two different tasks in the literature. In this paper, we present an index for both no-reference 2D and 3D IQA.
Yuzhen Niu, Dong Huang, Yiqing Shi, Xiao Ke   +3 more
doaj   +1 more source

Long-Range Dependencies and High-Order Spatial Pooling for Deep Model-Based Full-Reference Image Quality Assessment

IEEE Access, 2020
Deep Learning based image quality assessment (IQA) has been shown to greatly improve the quality score prediction accuracy of images with single distortion.
Mengyang Liu, Lai-Man Po, Xuyuan Xu, Kwok Wai Cheung, Yuzhi Zhao, Kin Wai Lau, Chang Zhou   +6 more
doaj   +1 more source

A Soft-Reference Breast Ultrasound Image Quality Assessment Method That Considers the Local Lesion Area

Bioengineering, 2023
The quality of breast ultrasound images has a significant impact on the accuracy of disease diagnosis. Existing image quality assessment (IQA) methods usually use pixel-level feature statistical methods or end-to-end deep learning methods, which focus on
Ziwen Wang, Yuxin Song, Baoliang Zhao, Zhaoming Zhong, Liang Yao, Faqin Lv, Bing Li, Ying Hu   +7 more
doaj   +1 more source

Scalable image quality assessment with 2D mel-cepstrum and machine learning approach [PDF]

, 2012
Cataloged from PDF version of article.Measurement of image quality is of fundamental importance to numerous image and video processing applications.
Cetin, A. E., Lin, W., Narwaria, M.
core   +1 more source

VR IQA NET: Deep Virtual Reality Image Quality Assessment Using Adversarial Learning [PDF]

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
In this paper, we propose a novel virtual reality image quality assessment (VR IQA) with adversarial learning for omnidirectional images. To take into account the characteristics of the omnidirectional image, we devise deep networks including novel quality score predictor and human perception guider.
Heaun-Taek Lim, Hak Gu Kim, Yang Man Ra
openaire   +3 more sources