Journal articles on the topic 'Super learning'
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Long, Jun, Jinhuan Zhang, and Ping Du. "Super-sampling by learning-based super-resolution." International Journal of Computational Science and Engineering 1, no. 1 (2019): 1. http://dx.doi.org/10.1504/ijcse.2019.10020177.
Du, Ping, Jinhuan Zhang, and Jun Long. "Super-sampling by learning-based super-resolution." International Journal of Computational Science and Engineering 21, no. 2 (2020): 249. http://dx.doi.org/10.1504/ijcse.2020.105731.
Haris, Muhammad, M. Rahmat Widyanto, and Hajime Nobuhara. "Inception learning super-resolution." Applied Optics 56, no. 22 (July 21, 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, no. 2 (May 2, 2022): 14–24. http://dx.doi.org/10.31891/2307-5732-2022-307-2-14-24.
Aitken, Michael R. F., Mark J. W. Larkin, and Anthony Dickinson. "Super-learning of Causal Judgements." Quarterly Journal of Experimental Psychology B 53, no. 1 (February 1, 2000): 59–81. http://dx.doi.org/10.1080/027249900392995.
Lim, Alane. "Machine learning method puts the “super” in super-resolution spectroscopy." Scilight 2021, no. 49 (December 3, 2021): 491108. http://dx.doi.org/10.1063/10.0009031.
Han, Tong, Li Zhao, and Chuang Wang. "Research on Super-resolution Image Based on Deep Learning." International Journal of Advanced Network, Monitoring and Controls 8, no. 1 (January 1, 2023): 58–65. http://dx.doi.org/10.2478/ijanmc-2023-0046.
Jiang, Jingyu, Li Zhao, and Yan Jiao. "Research on Image Super-resolution Reconstruction Based on Deep Learning." International Journal of Advanced Network, Monitoring and Controls 7, no. 1 (January 1, 2022): 1–21. http://dx.doi.org/10.2478/ijanmc-2022-0001.
Demontis, Ambra, Marco Melis, Battista Biggio, Giorgio Fumera, and Fabio Roli. "Super-Sparse Learning in Similarity Spaces." IEEE Computational Intelligence Magazine 11, no. 4 (November 2016): 36–45. http://dx.doi.org/10.1109/mci.2016.2601702.
Strack, Rita. "Deep learning advances super-resolution imaging." Nature Methods 15, no. 6 (May 31, 2018): 403. http://dx.doi.org/10.1038/s41592-018-0028-9.
Kita, Koji, Michifumi Yoshioka, Katsufumi Inoue, Naru Inage, and Shohei Tsunekawa. "Figure Patches Learning-based Super-Resolution." IEEJ Transactions on Electronics, Information and Systems 136, no. 7 (2016): 929–37. http://dx.doi.org/10.1541/ieejeiss.136.929.
Yang, Wenming, Fei Zhou, Rui Zhu, Kazuhiro Fukui, Guijin Wang, and Jing-Hao Xue. "Deep learning for image super-resolution." Neurocomputing 398 (July 2020): 291–92. http://dx.doi.org/10.1016/j.neucom.2019.09.091.
Wang, Wenjun, Chao Ren, Xiaohai He, Honggang Chen, and 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 and Yuan Yuan. "Learning From Errors in Super-Resolution." IEEE Transactions on Cybernetics 44, no. 11 (November 2014): 2143–54. http://dx.doi.org/10.1109/tcyb.2014.2301732.
R. Mhatre, Sneha, and Jagdish W. Bakal. "A Review of Image Super Resolution using Deep Learning." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 5s (May 17, 2023): 145–49. http://dx.doi.org/10.17762/ijritcc.v11i5s.6638.
Singh, Kajol, and Manish Saxena. "A Review on Medical Image Super Resolution with Application of Deep Learning." SMART MOVES JOURNAL IJOSCIENCE 7, no. 2 (March 27, 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, and 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 (May 30, 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, and Xiaqiong Yu. "DL-MRI: A Unified Framework of Deep Learning-Based MRI Super Resolution." Journal of Healthcare Engineering 2021 (April 9, 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, no. 6 (June 27, 2021): 288–301. http://dx.doi.org/10.14738/assrj.86.10366.
Ordyniak, S., and S. Szeider. "Parameterized Complexity Results for Exact Bayesian Network Structure Learning." Journal of Artificial Intelligence Research 46 (March 5, 2013): 263–302. http://dx.doi.org/10.1613/jair.3744.
Jian, Zhang, Xu Tengteng, Qian Jianjun, Yuchen Xiao, Heng Zhang, Hongran Li, and Cunhua Li. "Single Image Self-Learning Super-Resolution with Robust Matrix Regression." AATCC Journal of Research 8, no. 1_suppl (September 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, and Zhaoxiong Li. "A DEM Super-Resolution Reconstruction Network Combining Internal and External Learning." Remote Sensing 14, no. 9 (May 2, 2022): 2181. http://dx.doi.org/10.3390/rs14092181.
Maftuh, Muhammad Kholidin, and Dayat Hidayat. "THE EFFECT OF SUPERITEM LEARNING MODEL ON INCREASING STUDENTs LEARNING ACHIEVEMENTS." (JIML) JOURNAL OF INNOVATIVE MATHEMATICS LEARNING 1, no. 4 (November 28, 2018): 367. http://dx.doi.org/10.22460/jiml.v1i4.p367-373.
Davies, Molly Margaret, and Mark J. van der Laan. "Optimal Spatial Prediction Using Ensemble Machine Learning." International Journal of Biostatistics 12, no. 1 (May 1, 2016): 179–201. http://dx.doi.org/10.1515/ijb-2014-0060.
He, Yifan, Wei Cao, Xiaofeng Du, and Changlin Chen. "Internal Learning for Image Super-Resolution by Adaptive Feature Transform." Symmetry 12, no. 10 (October 14, 2020): 1686. http://dx.doi.org/10.3390/sym12101686.
Li, Xiaoyan, Lefei Zhang, and Jane You. "Domain Transfer Learning for Hyperspectral Image Super-Resolution." Remote Sensing 11, no. 6 (March 22, 2019): 694. http://dx.doi.org/10.3390/rs11060694.
Leli, Vito M., Saeed Osat, Timur Tlyachev, Dmitry V. Dylov, and Jacob D. Biamonte. "Deep learning super-diffusion in multiplex networks." Journal of Physics: Complexity 2, no. 3 (June 10, 2021): 035011. http://dx.doi.org/10.1088/2632-072x/abe6e9.
Heo, Bo-Young, and Byung Cheol Song. "Learning-based Super-resolution for Text Images." Journal of the Institute of Electronics and Information Engineers 52, no. 4 (April 25, 2015): 175–83. http://dx.doi.org/10.5573/ieie.2015.52.4.175.
Singh, Nisha, and Myna A.N. "Image Super-Resolution Using Deep Learning Technique." International Journal of Computer Sciences and Engineering 6, no. 7 (July 31, 2018): 150–55. http://dx.doi.org/10.26438/ijcse/v6i7.150155.
Chae, Byungjoo, Jinsun Park, Tae-Hyun Kim, and Donghyeon Cho. "Online Learning for Reference-Based Super-Resolution." Electronics 11, no. 7 (March 28, 2022): 1064. http://dx.doi.org/10.3390/electronics11071064.
Qin, Yu, Yuxing Li, Zhizheng Zhuo, Zhiwen Liu, Yaou Liu, and Chuyang Ye. "Multimodal super-resolved q-space deep learning." Medical Image Analysis 71 (July 2021): 102085. http://dx.doi.org/10.1016/j.media.2021.102085.
Chen, Chaofeng, Dihong Gong, Hao Wang, Zhifeng Li, and 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, and Jakub Nalepa. "Deep Learning for Multiple-Image Super-Resolution." IEEE Geoscience and Remote Sensing Letters 17, no. 6 (June 2020): 1062–66. http://dx.doi.org/10.1109/lgrs.2019.2940483.
Jiang, Zhuqing, Honghui Zhu, Yue Lu, Guodong Ju, and Aidong Men. "Lightweight Super-Resolution Using Deep Neural Learning." IEEE Transactions on Broadcasting 66, no. 4 (December 2020): 814–23. http://dx.doi.org/10.1109/tbc.2020.2977513.
Kumar, Neeraj, and Amit Sethi. "Fast Learning-Based Single Image Super-Resolution." IEEE Transactions on Multimedia 18, no. 8 (August 2016): 1504–15. http://dx.doi.org/10.1109/tmm.2016.2571625.
Huang, Weiqin, Xiaorui Li, Yikai Gu, Xiaofu Du, and 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, and Xuelong Li. "Single-image super-resolution via local learning." International Journal of Machine Learning and Cybernetics 2, no. 1 (February 12, 2011): 15–23. http://dx.doi.org/10.1007/s13042-011-0011-6.
Shamsolmoali, Pourya, Abdul Hamid Sadka, Huiyu Zhou, and Wankou Yang. "Advanced deep learning for image super-resolution." Signal Processing: Image Communication 82 (March 2020): 115732. http://dx.doi.org/10.1016/j.image.2019.115732.
Naimi, Ashley I., and Laura B. Balzer. "Stacked generalization: an introduction to super learning." European Journal of Epidemiology 33, no. 5 (April 10, 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, and Brian A. Hargreaves. "Super‐resolution musculoskeletal MRI using deep learning." Magnetic Resonance in Medicine 80, no. 5 (March 26, 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, no. 2 (2023): 34–42. http://dx.doi.org/10.54216/gjmsa.080204.
Yang, Guangtong, Chen Li, Yudong Yao, Ge Wang, and Yueyang Teng. "Quasi-supervised learning for super-resolution PET." Computerized Medical Imaging and Graphics 113 (April 2024): 102351. http://dx.doi.org/10.1016/j.compmedimag.2024.102351.
Geiss, Andrew, Sam J. Silva, and Joseph C. Hardin. "Downscaling atmospheric chemistry simulations with physically consistent deep learning." Geoscientific Model Development 15, no. 17 (September 5, 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 (January 26, 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, no. 2 (November 29, 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, and Thomas S. Huang. "Learning Temporal Dynamics for Video Super-Resolution: A Deep Learning Approach." IEEE Transactions on Image Processing 27, no. 7 (July 2018): 3432–45. http://dx.doi.org/10.1109/tip.2018.2820807.
Yue, Bo, Shuang Wang, Xuefeng Liang, and Licheng Jiao. "An external learning assisted self-examples learning for image super-resolution." Neurocomputing 312 (October 2018): 107–19. http://dx.doi.org/10.1016/j.neucom.2018.05.076.
Yu, Li, Yunpeng Ma, Song Hong, and Ke Chen. "Reivew of Light Field Image Super-Resolution." Electronics 11, no. 12 (June 17, 2022): 1904. http://dx.doi.org/10.3390/electronics11121904.
Masihu, Junardin Muhamad, and 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, no. 2 (December 1, 2022): 72–86. http://dx.doi.org/10.54373/ijset.v2i1.55.
Bhujade, Rakesh Kumar, and Stuti Asthana. "An Extensive Comparative Analysis on Various Efficient Techniques for Image Super-Resolution." International Journal of Emerging Technology and Advanced Engineering 12, no. 11 (November 1, 2022): 153–58. http://dx.doi.org/10.46338/ijetae1122_16.