Articoli di riviste sul tema "Super learning"
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Long, Jun, Jinhuan Zhang e Ping Du. "Super-sampling by learning-based super-resolution". International Journal of Computational Science and Engineering 1, n. 1 (2019): 1. http://dx.doi.org/10.1504/ijcse.2019.10020177.
Du, Ping, Jinhuan Zhang e Jun Long. "Super-sampling by learning-based super-resolution". International Journal of Computational Science and Engineering 21, n. 2 (2020): 249. http://dx.doi.org/10.1504/ijcse.2020.105731.
Haris, Muhammad, M. Rahmat Widyanto e Hajime Nobuhara. "Inception learning super-resolution". Applied Optics 56, n. 22 (21 luglio 2017): 6043. http://dx.doi.org/10.1364/ao.56.006043.
GURBYCH, A. "METHOD SUPER LEARNING FOR DETERMINATION OF MOLECULAR RELATIONSHIP". Herald of Khmelnytskyi National University. Technical sciences 307, n. 2 (2 maggio 2022): 14–24. http://dx.doi.org/10.31891/2307-5732-2022-307-2-14-24.
Aitken, Michael R. F., Mark J. W. Larkin e Anthony Dickinson. "Super-learning of Causal Judgements". Quarterly Journal of Experimental Psychology B 53, n. 1 (1 febbraio 2000): 59–81. http://dx.doi.org/10.1080/027249900392995.
Lim, Alane. "Machine learning method puts the “super” in super-resolution spectroscopy". Scilight 2021, n. 49 (3 dicembre 2021): 491108. http://dx.doi.org/10.1063/10.0009031.
Han, Tong, Li Zhao e Chuang Wang. "Research on Super-resolution Image Based on Deep Learning". International Journal of Advanced Network, Monitoring and Controls 8, n. 1 (1 gennaio 2023): 58–65. http://dx.doi.org/10.2478/ijanmc-2023-0046.
Jiang, Jingyu, Li Zhao e Yan Jiao. "Research on Image Super-resolution Reconstruction Based on Deep Learning". International Journal of Advanced Network, Monitoring and Controls 7, n. 1 (1 gennaio 2022): 1–21. http://dx.doi.org/10.2478/ijanmc-2022-0001.
Demontis, Ambra, Marco Melis, Battista Biggio, Giorgio Fumera e Fabio Roli. "Super-Sparse Learning in Similarity Spaces". IEEE Computational Intelligence Magazine 11, n. 4 (novembre 2016): 36–45. http://dx.doi.org/10.1109/mci.2016.2601702.
Strack, Rita. "Deep learning advances super-resolution imaging". Nature Methods 15, n. 6 (31 maggio 2018): 403. http://dx.doi.org/10.1038/s41592-018-0028-9.
Kita, Koji, Michifumi Yoshioka, Katsufumi Inoue, Naru Inage e Shohei Tsunekawa. "Figure Patches Learning-based Super-Resolution". IEEJ Transactions on Electronics, Information and Systems 136, n. 7 (2016): 929–37. http://dx.doi.org/10.1541/ieejeiss.136.929.
Yang, Wenming, Fei Zhou, Rui Zhu, Kazuhiro Fukui, Guijin Wang e Jing-Hao Xue. "Deep learning for image super-resolution". Neurocomputing 398 (luglio 2020): 291–92. http://dx.doi.org/10.1016/j.neucom.2019.09.091.
Wang, Wenjun, Chao Ren, Xiaohai He, Honggang Chen e Linbo Qing. "Video Super-Resolution via Residual Learning". IEEE Access 6 (2018): 23767–77. http://dx.doi.org/10.1109/access.2018.2829908.
Yi Tang e Yuan Yuan. "Learning From Errors in Super-Resolution". IEEE Transactions on Cybernetics 44, n. 11 (novembre 2014): 2143–54. http://dx.doi.org/10.1109/tcyb.2014.2301732.
R. Mhatre, Sneha, e Jagdish W. Bakal. "A Review of Image Super Resolution using Deep Learning". International Journal on Recent and Innovation Trends in Computing and Communication 11, n. 5s (17 maggio 2023): 145–49. http://dx.doi.org/10.17762/ijritcc.v11i5s.6638.
Singh, Kajol, e Manish Saxena. "A Review on Medical Image Super Resolution with Application of Deep Learning". SMART MOVES JOURNAL IJOSCIENCE 7, n. 2 (27 marzo 2021): 25–29. http://dx.doi.org/10.24113/ijoscience.v7i2.368.
He, H., K. Gao, W. Tan, L. Wang, S. N. Fatholahi, N. Chen, M. A. Chapman e J. Li. "IMPACT OF DEEP LEARNING-BASED SUPER-RESOLUTION ON BUILDING FOOTPRINT EXTRACTION". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2022 (30 maggio 2022): 31–37. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2022-31-2022.
Liu, Huanyu, Jiaqi Liu, Junbao Li, Jeng-Shyang Pan e Xiaqiong Yu. "DL-MRI: A Unified Framework of Deep Learning-Based MRI Super Resolution". Journal of Healthcare Engineering 2021 (9 aprile 2021): 1–9. http://dx.doi.org/10.1155/2021/5594649.
Pllana, Duli. "Combining Teaching Strategies, Learning Strategies, and Elements of Super Learning Principles". Advances in Social Sciences Research Journal 8, n. 6 (27 giugno 2021): 288–301. http://dx.doi.org/10.14738/assrj.86.10366.
Ordyniak, S., e S. Szeider. "Parameterized Complexity Results for Exact Bayesian Network Structure Learning". Journal of Artificial Intelligence Research 46 (5 marzo 2013): 263–302. http://dx.doi.org/10.1613/jair.3744.
Jian, Zhang, Xu Tengteng, Qian Jianjun, Yuchen Xiao, Heng Zhang, Hongran Li e Cunhua Li. "Single Image Self-Learning Super-Resolution with Robust Matrix Regression". AATCC Journal of Research 8, n. 1_suppl (settembre 2021): 135–42. http://dx.doi.org/10.14504/ajr.8.s1.17.
Lin, Xu, Qingqing Zhang, Hongyue Wang, Chaolong Yao, Changxin Chen, Lin Cheng e Zhaoxiong Li. "A DEM Super-Resolution Reconstruction Network Combining Internal and External Learning". Remote Sensing 14, n. 9 (2 maggio 2022): 2181. http://dx.doi.org/10.3390/rs14092181.
Maftuh, Muhammad Kholidin, e Dayat Hidayat. "THE EFFECT OF SUPERITEM LEARNING MODEL ON INCREASING STUDENTs LEARNING ACHIEVEMENTS". (JIML) JOURNAL OF INNOVATIVE MATHEMATICS LEARNING 1, n. 4 (28 novembre 2018): 367. http://dx.doi.org/10.22460/jiml.v1i4.p367-373.
Davies, Molly Margaret, e Mark J. van der Laan. "Optimal Spatial Prediction Using Ensemble Machine Learning". International Journal of Biostatistics 12, n. 1 (1 maggio 2016): 179–201. http://dx.doi.org/10.1515/ijb-2014-0060.
He, Yifan, Wei Cao, Xiaofeng Du e Changlin Chen. "Internal Learning for Image Super-Resolution by Adaptive Feature Transform". Symmetry 12, n. 10 (14 ottobre 2020): 1686. http://dx.doi.org/10.3390/sym12101686.
Li, Xiaoyan, Lefei Zhang e Jane You. "Domain Transfer Learning for Hyperspectral Image Super-Resolution". Remote Sensing 11, n. 6 (22 marzo 2019): 694. http://dx.doi.org/10.3390/rs11060694.
Leli, Vito M., Saeed Osat, Timur Tlyachev, Dmitry V. Dylov e Jacob D. Biamonte. "Deep learning super-diffusion in multiplex networks". Journal of Physics: Complexity 2, n. 3 (10 giugno 2021): 035011. http://dx.doi.org/10.1088/2632-072x/abe6e9.
Heo, Bo-Young, e Byung Cheol Song. "Learning-based Super-resolution for Text Images". Journal of the Institute of Electronics and Information Engineers 52, n. 4 (25 aprile 2015): 175–83. http://dx.doi.org/10.5573/ieie.2015.52.4.175.
Singh, Nisha, e Myna A.N. "Image Super-Resolution Using Deep Learning Technique". International Journal of Computer Sciences and Engineering 6, n. 7 (31 luglio 2018): 150–55. http://dx.doi.org/10.26438/ijcse/v6i7.150155.
Chae, Byungjoo, Jinsun Park, Tae-Hyun Kim e Donghyeon Cho. "Online Learning for Reference-Based Super-Resolution". Electronics 11, n. 7 (28 marzo 2022): 1064. http://dx.doi.org/10.3390/electronics11071064.
Qin, Yu, Yuxing Li, Zhizheng Zhuo, Zhiwen Liu, Yaou Liu e Chuyang Ye. "Multimodal super-resolved q-space deep learning". Medical Image Analysis 71 (luglio 2021): 102085. http://dx.doi.org/10.1016/j.media.2021.102085.
Chen, Chaofeng, Dihong Gong, Hao Wang, Zhifeng Li e Kwan-Yee K. Wong. "Learning Spatial Attention for Face Super-Resolution". IEEE Transactions on Image Processing 30 (2021): 1219–31. http://dx.doi.org/10.1109/tip.2020.3043093.
Kawulok, Michal, Pawel Benecki, Szymon Piechaczek, Krzysztof Hrynczenko, Daniel Kostrzewa e Jakub Nalepa. "Deep Learning for Multiple-Image Super-Resolution". IEEE Geoscience and Remote Sensing Letters 17, n. 6 (giugno 2020): 1062–66. http://dx.doi.org/10.1109/lgrs.2019.2940483.
Jiang, Zhuqing, Honghui Zhu, Yue Lu, Guodong Ju e Aidong Men. "Lightweight Super-Resolution Using Deep Neural Learning". IEEE Transactions on Broadcasting 66, n. 4 (dicembre 2020): 814–23. http://dx.doi.org/10.1109/tbc.2020.2977513.
Kumar, Neeraj, e Amit Sethi. "Fast Learning-Based Single Image Super-Resolution". IEEE Transactions on Multimedia 18, n. 8 (agosto 2016): 1504–15. http://dx.doi.org/10.1109/tmm.2016.2571625.
Huang, Weiqin, Xiaorui Li, Yikai Gu, Xiaofu Du e Xiancheng Zhu. "Learning Enriched Features for Image Super Resolution". IEEE Access 10 (2022): 113583–97. http://dx.doi.org/10.1109/access.2022.3216672.
Tang, Yi, Pingkun Yan, Yuan Yuan e Xuelong Li. "Single-image super-resolution via local learning". International Journal of Machine Learning and Cybernetics 2, n. 1 (12 febbraio 2011): 15–23. http://dx.doi.org/10.1007/s13042-011-0011-6.
Shamsolmoali, Pourya, Abdul Hamid Sadka, Huiyu Zhou e Wankou Yang. "Advanced deep learning for image super-resolution". Signal Processing: Image Communication 82 (marzo 2020): 115732. http://dx.doi.org/10.1016/j.image.2019.115732.
Naimi, Ashley I., e Laura B. Balzer. "Stacked generalization: an introduction to super learning". European Journal of Epidemiology 33, n. 5 (10 aprile 2018): 459–64. http://dx.doi.org/10.1007/s10654-018-0390-z.
Chaudhari, Akshay S., Zhongnan Fang, Feliks Kogan, Jeff Wood, Kathryn J. Stevens, Eric K. Gibbons, Jin Hyung Lee, Garry E. Gold e Brian A. Hargreaves. "Super‐resolution musculoskeletal MRI using deep learning". Magnetic Resonance in Medicine 80, n. 5 (26 marzo 2018): 2139–54. http://dx.doi.org/10.1002/mrm.27178.
Hasan, Zahraa. "Deep Learning for Super Resolution and Applications". Galoitica: Journal of Mathematical Structures and Applications 8, n. 2 (2023): 34–42. http://dx.doi.org/10.54216/gjmsa.080204.
Yang, Guangtong, Chen Li, Yudong Yao, Ge Wang e Yueyang Teng. "Quasi-supervised learning for super-resolution PET". Computerized Medical Imaging and Graphics 113 (aprile 2024): 102351. http://dx.doi.org/10.1016/j.compmedimag.2024.102351.
Geiss, Andrew, Sam J. Silva e Joseph C. Hardin. "Downscaling atmospheric chemistry simulations with physically consistent deep learning". Geoscientific Model Development 15, n. 17 (5 settembre 2022): 6677–94. http://dx.doi.org/10.5194/gmd-15-6677-2022.
Wu, Haozhe. "Super-Resolution of Lightweight Images Based on Deep Learning". Highlights in Science, Engineering and Technology 81 (26 gennaio 2024): 456–60. http://dx.doi.org/10.54097/f8y87181.
Dewi, Ratna Kumala. "INNOVATION OF BIOCHEMISTRY LEARNING IN WELCOMING THE SUPER SMART SOCIETY 5.0 ERA". INSECTA: Integrative Science Education and Teaching Activity Journal 2, n. 2 (29 novembre 2021): 197–208. http://dx.doi.org/10.21154/insecta.v2i2.3507.
Liu, Ding, Zhaowen Wang, Yuchen Fan, Xianming Liu, Zhangyang Wang, Shiyu Chang, Xinchao Wang e Thomas S. Huang. "Learning Temporal Dynamics for Video Super-Resolution: A Deep Learning Approach". IEEE Transactions on Image Processing 27, n. 7 (luglio 2018): 3432–45. http://dx.doi.org/10.1109/tip.2018.2820807.
Yue, Bo, Shuang Wang, Xuefeng Liang e Licheng Jiao. "An external learning assisted self-examples learning for image super-resolution". Neurocomputing 312 (ottobre 2018): 107–19. http://dx.doi.org/10.1016/j.neucom.2018.05.076.
Yu, Li, Yunpeng Ma, Song Hong e Ke Chen. "Reivew of Light Field Image Super-Resolution". Electronics 11, n. 12 (17 giugno 2022): 1904. http://dx.doi.org/10.3390/electronics11121904.
Masihu, Junardin Muhamad, e Edi Masihu. "Application of Super Item Learning Model in Improving Learning Outcomes of Photosynthesis Concept in Class VIII of SMP Al-Wathan Ambon". PEDAGOGIC: Indonesian Journal of Science Education and Technology 1, n. 2 (1 dicembre 2022): 72–86. http://dx.doi.org/10.54373/ijset.v2i1.55.
Bhujade, Rakesh Kumar, e Stuti Asthana. "An Extensive Comparative Analysis on Various Efficient Techniques for Image Super-Resolution". International Journal of Emerging Technology and Advanced Engineering 12, n. 11 (1 novembre 2022): 153–58. http://dx.doi.org/10.46338/ijetae1122_16.