Artykuły w czasopismach na temat „No-Reference image quality assessment (NR-IQA)”
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Zhang, Haopeng, Bo Yuan, Bo Dong i Zhiguo Jiang. "No-Reference Blurred Image Quality Assessment by Structural Similarity Index". Applied Sciences 8, nr 10 (22.10.2018): 2003. http://dx.doi.org/10.3390/app8102003.
Pełny tekst źródłaShi, Jinsong, Pan Gao i Jie Qin. "Transformer-Based No-Reference Image Quality Assessment via Supervised Contrastive Learning". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 5 (24.03.2024): 4829–37. http://dx.doi.org/10.1609/aaai.v38i5.28285.
Pełny tekst źródłaLee, Wonkyeong, Eunbyeol Cho, Wonjin Kim, Hyebin Choi, Kyongmin Sarah Beck, Hyun Jung Yoon, Jongduk Baek i Jang-Hwan Choi. "No-reference perceptual CT image quality assessment based on a self-supervised learning framework". Machine Learning: Science and Technology 3, nr 4 (1.12.2022): 045033. http://dx.doi.org/10.1088/2632-2153/aca87d.
Pełny tekst źródłaOszust, Mariusz. "No-Reference Image Quality Assessment with Local Gradient Orientations". Symmetry 11, nr 1 (16.01.2019): 95. http://dx.doi.org/10.3390/sym11010095.
Pełny tekst źródłaAhmed, Ismail Taha, Chen Soong Der, Baraa Tareq Hammad i Norziana Jamil. "Contrast-distorted image quality assessment based on curvelet domain features". International Journal of Electrical and Computer Engineering (IJECE) 11, nr 3 (1.06.2021): 2595. http://dx.doi.org/10.11591/ijece.v11i3.pp2595-2603.
Pełny tekst źródłaGarcia Freitas, Pedro, Luísa da Eira, Samuel Santos i Mylene Farias. "On the Application LBP Texture Descriptors and Its Variants for No-Reference Image Quality Assessment". Journal of Imaging 4, nr 10 (4.10.2018): 114. http://dx.doi.org/10.3390/jimaging4100114.
Pełny tekst źródłaGu, Jie, Gaofeng Meng, Cheng Da, Shiming Xiang i Chunhong Pan. "No-Reference Image Quality Assessment with Reinforcement Recursive List-Wise Ranking". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17.07.2019): 8336–43. http://dx.doi.org/10.1609/aaai.v33i01.33018336.
Pełny tekst źródłaVarga, Domonkos. "No-Reference Image Quality Assessment with Convolutional Neural Networks and Decision Fusion". Applied Sciences 12, nr 1 (23.12.2021): 101. http://dx.doi.org/10.3390/app12010101.
Pełny tekst źródłaYin, Guanghao, Wei Wang, Zehuan Yuan, Chuchu Han, Wei Ji, Shouqian Sun i Changhu Wang. "Content-Variant Reference Image Quality Assessment via Knowledge Distillation". Proceedings of the AAAI Conference on Artificial Intelligence 36, nr 3 (28.06.2022): 3134–42. http://dx.doi.org/10.1609/aaai.v36i3.20221.
Pełny tekst źródłaGavrovska, Ana, Dragi Dujković, Andreja Samčović, Yuliya Golub i Valery Starovoitov. "Quadratic fitting model in no-reference image quality assessment". Telfor Journal 15, nr 2 (2023): 32–37. http://dx.doi.org/10.5937/telfor2302032g.
Pełny tekst źródłaVarga, Domonkos. "No-Reference Image Quality Assessment with Multi-Scale Orderless Pooling of Deep Features". Journal of Imaging 7, nr 7 (10.07.2021): 112. http://dx.doi.org/10.3390/jimaging7070112.
Pełny tekst źródłaYan, Chenggang, Tong Teng, Yutao Liu, Yongbing Zhang, Haoqian Wang i Xiangyang Ji. "Precise No-Reference Image Quality Evaluation Based on Distortion Identification". ACM Transactions on Multimedia Computing, Communications, and Applications 17, nr 3s (31.10.2021): 1–21. http://dx.doi.org/10.1145/3468872.
Pełny tekst źródłaStępień, Igor, i Mariusz Oszust. "A Brief Survey on No-Reference Image Quality Assessment Methods for Magnetic Resonance Images". Journal of Imaging 8, nr 6 (4.06.2022): 160. http://dx.doi.org/10.3390/jimaging8060160.
Pełny tekst źródłaYe, Zhongchang, Xin Ye i Zhonghua Zhao. "Hybrid No-Reference Quality Assessment for Surveillance Images". Information 13, nr 12 (16.12.2022): 588. http://dx.doi.org/10.3390/info13120588.
Pełny tekst źródłaFu, Hao, Guojun Liu, Xiaoqin Yang, Lili Wei i Lixia Yang. "Two Low-Level Feature Distributions Based No Reference Image Quality Assessment". Applied Sciences 12, nr 10 (14.05.2022): 4975. http://dx.doi.org/10.3390/app12104975.
Pełny tekst źródłaGuan, Xiaodi, Fan Li i Lijun He. "Quality Assessment on Authentically Distorted Images by Expanding Proxy Labels". Electronics 9, nr 2 (3.02.2020): 252. http://dx.doi.org/10.3390/electronics9020252.
Pełny tekst źródłaVarga, Domonkos. "No-Reference Image Quality Assessment Based on the Fusion of Statistical and Perceptual Features". Journal of Imaging 6, nr 8 (30.07.2020): 75. http://dx.doi.org/10.3390/jimaging6080075.
Pełny tekst źródłaAhmed, Ismail Taha, Chen Soong Der, Norziana Jamil i Mohamad Afendee Mohamed. "Improve of contrast-distorted image quality assessment based on convolutional neural networks". International Journal of Electrical and Computer Engineering (IJECE) 9, nr 6 (1.12.2019): 5604. http://dx.doi.org/10.11591/ijece.v9i6.pp5604-5614.
Pełny tekst źródłaStępień, Igor, i Mariusz Oszust. "No-Reference Quality Assessment of Pan-Sharpening Images with Multi-Level Deep Image Representations". Remote Sensing 14, nr 5 (24.02.2022): 1119. http://dx.doi.org/10.3390/rs14051119.
Pełny tekst źródłaRyu, Jihyoung. "Improved Image Quality Assessment by Utilizing Pre-Trained Architecture Features with Unified Learning Mechanism". Applied Sciences 13, nr 4 (19.02.2023): 2682. http://dx.doi.org/10.3390/app13042682.
Pełny tekst źródłaVarga, Domonkos. "A Human Visual System Inspired No-Reference Image Quality Assessment Method Based on Local Feature Descriptors". Sensors 22, nr 18 (7.09.2022): 6775. http://dx.doi.org/10.3390/s22186775.
Pełny tekst źródłaRyu, Jihyoung. "A Visual Saliency-Based Neural Network Architecture for No-Reference Image Quality Assessment". Applied Sciences 12, nr 19 (23.09.2022): 9567. http://dx.doi.org/10.3390/app12199567.
Pełny tekst źródłaAbdalmajeed, Saifeldeen, i Jiao Shuhong. "Using the Natural Scenes’ Edges for Assessing Image Quality Blindly and Efficiently". Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/389504.
Pełny tekst źródłaMahmood, Saifeldeen Abdalmajeed. "Three Different Features Based Metric To Assess Image Quality Blindly". FES Journal of Engineering Sciences 8, nr 2 (23.05.2020): 97–103. http://dx.doi.org/10.52981/fjes.v8i2.121.
Pełny tekst źródłaLU, WEN, LIHUO HE, WENJIAN TANG, FEI GAO i WEILONG HOU. "A NOVEL COMPRESSED IMAGES QUALITY METRIC". International Journal of Image and Graphics 11, nr 02 (kwiecień 2011): 281–92. http://dx.doi.org/10.1142/s021946781100410x.
Pełny tekst źródłaUllah, Hayat, Muhammad Irfan, Kyungjin Han i Jong Weon Lee. "DLNR-SIQA: Deep Learning-Based No-Reference Stitched Image Quality Assessment". Sensors 20, nr 22 (12.11.2020): 6457. http://dx.doi.org/10.3390/s20226457.
Pełny tekst źródłaZhang, Run, i Yongbin Wang. "Natural Image Quality Assessment Based on Visual Biological Cognitive Mechanism". International Journal of Software Innovation 7, nr 1 (styczeń 2019): 1–26. http://dx.doi.org/10.4018/ijsi.2019010101.
Pełny tekst źródłaWang, Yue, Zeng Gang Lin i Zi Cheng Liao. "Image Quality Assessment Based on Region of Interest". Applied Mechanics and Materials 596 (lipiec 2014): 350–54. http://dx.doi.org/10.4028/www.scientific.net/amm.596.350.
Pełny tekst źródłaHan, Lintao, Hengyi Lv, Yuchen Zhao, Hailong Liu, Guoling Bi, Zhiyong Yin i Yuqiang Fang. "Conv-Former: A Novel Network Combining Convolution and Self-Attention for Image Quality Assessment". Sensors 23, nr 1 (30.12.2022): 427. http://dx.doi.org/10.3390/s23010427.
Pełny tekst źródłaStępień, Igor, Rafał Obuchowicz, Adam Piórkowski i Mariusz Oszust. "Fusion of Deep Convolutional Neural Networks for No-Reference Magnetic Resonance Image Quality Assessment". Sensors 21, nr 4 (3.02.2021): 1043. http://dx.doi.org/10.3390/s21041043.
Pełny tekst źródłaCui, Yueli. "No-Reference Image Quality Assessment Based on Dual-Domain Feature Fusion". Entropy 22, nr 3 (17.03.2020): 344. http://dx.doi.org/10.3390/e22030344.
Pełny tekst źródłaQian, Qi, i Qingbing Sang. "No-reference image quality assessment based on automatic machine learning". ITM Web of Conferences 45 (2022): 01034. http://dx.doi.org/10.1051/itmconf/20224501034.
Pełny tekst źródłaChandler, Damon M. "Seven Challenges in Image Quality Assessment: Past, Present, and Future Research". ISRN Signal Processing 2013 (6.02.2013): 1–53. http://dx.doi.org/10.1155/2013/905685.
Pełny tekst źródłaVarga, Domonkos. "No-Reference Quality Assessment of Authentically Distorted Images Based on Local and Global Features". Journal of Imaging 8, nr 6 (19.06.2022): 173. http://dx.doi.org/10.3390/jimaging8060173.
Pełny tekst źródłaGupta, Praful, Christos Bampis, Jack Glover, Nicholas Paulter i Alan Bovik. "Multivariate Statistical Approach to Image Quality Tasks". Journal of Imaging 4, nr 10 (12.10.2018): 117. http://dx.doi.org/10.3390/jimaging4100117.
Pełny tekst źródłaGao, Guoqing, Lingxiao Li, Hao Chen, Ning Jiang, Shuqi Li, Qing Bian, Hua Bao i Changhui Rao. "No-Reference Quality Assessment of Extended Target Adaptive Optics Images Using Deep Neural Network". Sensors 24, nr 1 (19.12.2023): 1. http://dx.doi.org/10.3390/s24010001.
Pełny tekst źródłaGu, Ke, Guangtao Zhai, Xiaokang Yang i Wenjun Zhang. "No-Reference Stereoscopic IQA Approach: From Nonlinear Effect to Parallax Compensation". Journal of Electrical and Computer Engineering 2012 (2012): 1–12. http://dx.doi.org/10.1155/2012/436031.
Pełny tekst źródłaLei, Shu, Huang Zijian, Yan Jiebin i Fei Fengchang. "Super Resolution Image Visual Quality Assessment Based on Feature Optimization". Computational Intelligence and Neuroscience 2022 (20.06.2022): 1–10. http://dx.doi.org/10.1155/2022/1263348.
Pełny tekst źródłaVarga, Domonkos. "Multi-Pooled Inception Features for No-Reference Image Quality Assessment". Applied Sciences 10, nr 6 (23.03.2020): 2186. http://dx.doi.org/10.3390/app10062186.
Pełny tekst źródłaHu, Kai, Yanwen Zhang, Feiyu Lu, Zhiliang Deng i Yunping Liu. "An Underwater Image Enhancement Algorithm Based on MSR Parameter Optimization". Journal of Marine Science and Engineering 8, nr 10 (25.09.2020): 741. http://dx.doi.org/10.3390/jmse8100741.
Pełny tekst źródłaCourtney, Jane. "SEDIQA: Sound Emitting Document Image Quality Assessment in a Reading Aid for the Visually Impaired". Journal of Imaging 7, nr 9 (30.08.2021): 168. http://dx.doi.org/10.3390/jimaging7090168.
Pełny tekst źródłaLi, Yuyan, Yubo Dong, Haoyong Li, Danhua Liu, Fang Xue i Dahua Gao. "No-Reference Hyperspectral Image Quality Assessment via Ranking Feature Learning". Remote Sensing 16, nr 10 (8.05.2024): 1657. http://dx.doi.org/10.3390/rs16101657.
Pełny tekst źródłaWang, Bin. "An Image Quality Assessment Approach Based on Saliency Map in Space Domain". Advanced Materials Research 1006-1007 (sierpień 2014): 768–72. http://dx.doi.org/10.4028/www.scientific.net/amr.1006-1007.768.
Pełny tekst źródłaStarovoitov, V. V., i F. V. Starovoitov. "COMPARATIVE ANALYSIS OF NO-REFERENCE QUALITY MEASURES FOR DIGITAL IMAGES". «System analysis and applied information science», nr 1 (4.05.2017): 24–32. http://dx.doi.org/10.21122/2309-4923-2017-1-24-32.
Pełny tekst źródłaModak, Sourav, Jonathan Heil i Anthony Stein. "Pansharpening Low-Altitude Multispectral Images of Potato Plants Using a Generative Adversarial Network". Remote Sensing 16, nr 5 (1.03.2024): 874. http://dx.doi.org/10.3390/rs16050874.
Pełny tekst źródłaZhang, Lin, Xilin Yang, Lijun Zhang, Xiao Liu, Shengjie Zhao i Yong Ma. "Towards Automatic Image Exposure Level Assessment". Mathematical Problems in Engineering 2020 (23.11.2020): 1–14. http://dx.doi.org/10.1155/2020/2789854.
Pełny tekst źródłaJin, Chongchong, Zongju Peng, Wenhui Zou, Fen Chen, Gangyi Jiang i Mei Yu. "No-Reference Quality Assessment for 3D Synthesized Images Based on Visual-Entropy-Guided Multi-Layer Features Analysis". Entropy 23, nr 6 (18.06.2021): 770. http://dx.doi.org/10.3390/e23060770.
Pełny tekst źródłaSybingco, Edwin, i Elmer P. Dadios. "Blind Image Quality Assessment Based on Natural Statistics of Double-Opponency". Journal of Advanced Computational Intelligence and Intelligent Informatics 22, nr 5 (20.09.2018): 725–30. http://dx.doi.org/10.20965/jaciii.2018.p0725.
Pełny tekst źródłaZheng, Yuanfeng, Yuchen Yan i Hao Jiang. "Semi-TSGAN: Semi-Supervised Learning for Highlight Removal Based on Teacher-Student Generative Adversarial Network". Sensors 24, nr 10 (13.05.2024): 3090. http://dx.doi.org/10.3390/s24103090.
Pełny tekst źródłaIrshad, Muhammad, Camilo Sanchez-Ferreira, Sana Alamgeer, Carlos H. Llanos i Mylène C. Q. Farias. "No-reference Image Quality Assessment of Underwater Images Using Multi-Scale Salient Local Binary Patterns". Electronic Imaging 2021, nr 9 (18.01.2021): 265–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.9.iqsp-265.
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