{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T03:38:49Z","timestamp":1776915529520,"version":"3.51.2"},"reference-count":56,"publisher":"World Scientific Pub Co Pte Ltd","issue":"08","funder":[{"name":"Guangdong Power Grid Co., Ltd. Digital and Intelligent Operations Center","award":["030000KC23040069"],"award-info":[{"award-number":["030000KC23040069"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2026,6,30]]},"abstract":"<jats:p>NR-IQA aims at assessing the perceptual quality of images based on human subjective perception. However, existing NR-IQA methods are likely to miss important fine-grained texture and structural information of key targets, and thus cannot provide reliable quality scores for UAV-captured images in complex power grid inspection scenes. In practical power grid inspection, images are typically captured at high resolutions (e.g. [Formula: see text]K or above) under varying illumination and weather conditions, while quality assessment is required to be performed with low latency on edge or ground-based computing platforms to support downstream inspection tasks. To address these challenges, we propose MASC-IQA, a no-reference image quality assessment model designed for complex background environments. First, we train a Feature Contrastive Module (FCM) on a large-scale real dataset to learn distortion types and degradation levels through supervised contrastive learning, enabling robust distortion-aware feature representation without relying on subjective image ratings during inference. Second, we introduce a Multi-Channel Attention Module (MCAM) to explicitly model inter-channel dependencies and enhance the interaction between global context and local structural details, which is particularly important for preserving perceptually critical information in cluttered industrial scenes. In addition, we release GridVision, a dedicated dataset for NR-IQA in power grid inspection scenarios, consisting of UAV-captured images with realistic distortions annotated by domain experts. Experimental results on several public IQA benchmarks and GridVision demonstrate that MASC-IQA consistently outperforms existing state-of-the-art methods in terms of both prediction accuracy and robustness.<\/jats:p>","DOI":"10.1142\/s0218001426550049","type":"journal-article","created":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T03:03:46Z","timestamp":1770174226000},"source":"Crossref","is-referenced-by-count":0,"title":["MASC-IQA: No-Reference Image Quality Assessment Based on Multi-Channel Attention Mechanism via Supervised Contrastive Learning"],"prefix":"10.1142","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8192-542X","authenticated-orcid":false,"given":"Jijun","family":"Zeng","sequence":"first","affiliation":[{"name":"Information Center of Guangdong Power Grid Co. Ltd., Guangdong, Guangzhou 510000, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-4897-4705","authenticated-orcid":false,"given":"Junwei","family":"Li","sequence":"additional","affiliation":[{"name":"Information Center of Guangdong Power Grid Co. Ltd., Guangdong, Guangzhou 510000, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-1094-3363","authenticated-orcid":false,"given":"Tianwen","family":"Kong","sequence":"additional","affiliation":[{"name":"Information Center of Guangdong Power Grid Co. Ltd., Guangdong, Guangzhou 510000, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2969-8309","authenticated-orcid":false,"given":"Huaquan","family":"Su","sequence":"additional","affiliation":[{"name":"Information Center of Guangdong Power Grid Co. Ltd., Guangdong, Guangzhou 510000, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9017-0852","authenticated-orcid":false,"given":"Yang","family":"Wu","sequence":"additional","affiliation":[{"name":"Information Center of Guangdong Power Grid Co. Ltd., Guangdong, Guangzhou 510000, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9728-3135","authenticated-orcid":false,"given":"Xin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science, Guangdong University of Technology, Guangdong, Guangzhou 510062, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3081-4546","authenticated-orcid":false,"given":"Baiyu","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Business Administration, Guangdong University of Finance and Economics, Guangzhou, Guangdong 510320, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2239-8674","authenticated-orcid":false,"given":"Shiting","family":"Wu","sequence":"additional","affiliation":[{"name":"Huizhou Boluo Power Supply Bureau Guangdong Power Grid Co. Ltd., Huizhou, Guangdong 516000, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2026,3,28]]},"reference":[{"key":"S0218001426550049BIB001","doi-asserted-by":"publisher","DOI":"10.1007\/s11760-017-1166-8"},{"key":"S0218001426550049BIB002","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2760518"},{"key":"S0218001426550049BIB003","volume-title":"International Conference on Learning Representations","author":"Dosovitskiy A.","year":"2021"},{"key":"S0218001426550049BIB004","first-page":"766","volume-title":"Proc. 27th Int. Conf. Neural Information Processing Systems","author":"Dosovitskiy A.","year":"2014"},{"key":"S0218001426550049BIB005","first-page":"838","volume":"22","author":"Fang Y.","year":"2015","journal-title":"IEEE Signal Process. Lett."},{"key":"S0218001426550049BIB006","doi-asserted-by":"publisher","DOI":"10.3390\/s24010001"},{"key":"S0218001426550049BIB007","doi-asserted-by":"publisher","DOI":"10.1167\/17.1.32"},{"key":"S0218001426550049BIB008","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00404"},{"key":"S0218001426550049BIB009","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3680745"},{"key":"S0218001426550049BIB010","first-page":"297","volume-title":"Proc. Int. Conf. Artificial Intelligence and Statistics","volume":"9","author":"Gutmann M. U.","year":"2010"},{"key":"S0218001426550049BIB011","doi-asserted-by":"publisher","DOI":"10.3390\/s23010427"},{"key":"S0218001426550049BIB012","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"S0218001426550049BIB013","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"S0218001426550049BIB014","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2967829"},{"key":"S0218001426550049BIB015","doi-asserted-by":"publisher","DOI":"10.1109\/BIBM62325.2024.10822792"},{"key":"S0218001426550049BIB016","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.224"},{"key":"S0218001426550049BIB017","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00510"},{"key":"S0218001426550049BIB018","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2016.2639328"},{"key":"S0218001426550049BIB019","doi-asserted-by":"publisher","DOI":"10.1117\/1.3267105"},{"key":"S0218001426550049BIB020","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01144"},{"key":"S0218001426550049BIB021","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2022.108438"},{"key":"S0218001426550049BIB022","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3180737"},{"key":"S0218001426550049BIB023","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i1.25214"},{"key":"S0218001426550049BIB024","doi-asserted-by":"publisher","DOI":"10.1109\/QoMEX.2019.8743252"},{"key":"S0218001426550049BIB025","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00083"},{"key":"S0218001426550049BIB026","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i2.25263"},{"key":"S0218001426550049BIB027","doi-asserted-by":"publisher","DOI":"10.1109\/TBC.2016.2597545"},{"key":"S0218001426550049BIB028","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.118"},{"key":"S0218001426550049BIB029","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2708503"},{"key":"S0218001426550049BIB030","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2774045"},{"key":"S0218001426550049BIB031","doi-asserted-by":"publisher","DOI":"10.1109\/ACSSC.2011.6190099"},{"key":"S0218001426550049BIB032","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2214050"},{"key":"S0218001426550049BIB033","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2012.2227726"},{"key":"S0218001426550049BIB034","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2147325"},{"key":"S0218001426550049BIB035","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2025.113392"},{"key":"S0218001426550049BIB036","first-page":"1","author":"Pei J.","year":"2025","journal-title":"IEEE Trans. Intelli. Transp. Syst."},{"key":"S0218001426550049BIB037","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2014.10.009"},{"key":"S0218001426550049BIB038","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2191563"},{"key":"S0218001426550049BIB039","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2006.881959"},{"issue":"5","key":"S0218001426550049BIB040","first-page":"4829","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"38","author":"Shi J.","year":"2023"},{"key":"S0218001426550049BIB041","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00372"},{"key":"S0218001426550049BIB042","doi-asserted-by":"publisher","DOI":"10.1109\/OJSP.2021.3090333"},{"key":"S0218001426550049BIB043","volume-title":"Proc. Neural Information Processing System","author":"Vaswani A.","year":"2017"},{"key":"S0218001426550049BIB044","doi-asserted-by":"publisher","DOI":"10.1109\/VCIP.2017.8305041"},{"key":"S0218001426550049BIB045","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00126"},{"key":"S0218001426550049BIB046","first-page":"1098","volume-title":"Proc. IEEE Conf. Computer Vision and Pattern Recognition","author":"Ye P.","year":"2012"},{"key":"S0218001426550049BIB047","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00363"},{"key":"S0218001426550049BIB048","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP42928.2021.9506075"},{"key":"S0218001426550049BIB049","doi-asserted-by":"publisher","DOI":"10.1016\/j.csbj.2022.04.003"},{"key":"S0218001426550049BIB050","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2018.2886771"},{"key":"S0218001426550049BIB051","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2426416"},{"key":"S0218001426550049BIB052","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2109730"},{"key":"S0218001426550049BIB053","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298853"},{"key":"S0218001426550049BIB054","first-page":"22302","volume-title":"Proc. IEEE\/CVF Conf. Computer Vision and Pattern Recognition","author":"Zhao K.","year":"2023"},{"key":"S0218001426550049BIB055","unstructured":"F. Zheng, X. Chen, X. Chen, H. Li, X. Guo, G. Huang, C. M. Pun and S. Zhou, ASSNet: Adaptive semantic segmentation network for microtumors and multi-organ segmentation (2024)."},{"key":"S0218001426550049BIB056","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01415"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001426550049","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T02:53:08Z","timestamp":1776912788000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/10.1142\/S0218001426550049"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,28]]},"references-count":56,"journal-issue":{"issue":"08","published-print":{"date-parts":[[2026,6,30]]}},"alternative-id":["10.1142\/S0218001426550049"],"URL":"https:\/\/doi.org\/10.1142\/s0218001426550049","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"value":"0218-0014","type":"print"},{"value":"1793-6381","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,28]]},"article-number":"2655004"}}