Статті в журналах з теми "Self-supervised learning (artificial intelligence)"
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Neghawi, Elie, and Yan Liu. "Enhancing Self-Supervised Learning through Explainable Artificial Intelligence Mechanisms: A Computational Analysis." Big Data and Cognitive Computing 8, no. 6 (June 3, 2024): 58. http://dx.doi.org/10.3390/bdcc8060058.
CHAN, JASON, IRENA KOPRINSKA, and JOSIAH POON. "SEMI-SUPERVISED CLASSIFICATION USING BRIDGING." International Journal on Artificial Intelligence Tools 17, no. 03 (June 2008): 415–31. http://dx.doi.org/10.1142/s0218213008003972.
Yuya, KOBAYASHI, Masahiro SUZUKI, and Yutaka MATSUO. "Scene Interpretation Method using Transformer and Self-supervised Learning." Transactions of the Japanese Society for Artificial Intelligence 37, no. 2 (March 1, 2022): I—L75_1–17. http://dx.doi.org/10.1527/tjsai.37-2_i-l75.
Hrycej, Tomas. "Supporting supervised learning by self-organization." Neurocomputing 4, no. 1-2 (February 1992): 17–30. http://dx.doi.org/10.1016/0925-2312(92)90040-v.
Wang, Fei, and Changshui Zhang. "Robust self-tuning semi-supervised learning." Neurocomputing 70, no. 16-18 (October 2007): 2931–39. http://dx.doi.org/10.1016/j.neucom.2006.11.004.
Biscione, Valerio, and Jeffrey S. Bowers. "Learning online visual invariances for novel objects via supervised and self-supervised training." Neural Networks 150 (June 2022): 222–36. http://dx.doi.org/10.1016/j.neunet.2022.02.017.
Ma, Jun, Yakun Wen, and Liming Yang. "Lagrangian supervised and semi-supervised extreme learning machine." Applied Intelligence 49, no. 2 (August 25, 2018): 303–18. http://dx.doi.org/10.1007/s10489-018-1273-4.
Che, Feihu, Guohua Yang, Dawei Zhang, Jianhua Tao, and Tong Liu. "Self-supervised graph representation learning via bootstrapping." Neurocomputing 456 (October 2021): 88–96. http://dx.doi.org/10.1016/j.neucom.2021.03.123.
Gu, Nannan, Pengying Fan, Mingyu Fan, and Di Wang. "Structure regularized self-paced learning for robust semi-supervised pattern classification." Neural Computing and Applications 31, no. 10 (April 19, 2018): 6559–74. http://dx.doi.org/10.1007/s00521-018-3478-1.
Saravana Kumar, N. M. "IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE IN IMPARTING EDUCATION AND EVALUATING STUDENT PERFORMANCE." Journal of Artificial Intelligence and Capsule Networks 01, no. 01 (September 2, 2019): 1–9. http://dx.doi.org/10.36548/jaicn.2019.1.001.
Wei, Chen, Yiping Tang, Chuang Niu Chuang Niu, Haihong Hu, Yue Wang, and Jimin Liang. "Self-Supervised Representation Learning for Evolutionary Neural Architecture Search." IEEE Computational Intelligence Magazine 16, no. 3 (August 2021): 33–49. http://dx.doi.org/10.1109/mci.2021.3084415.
Xi, Liang, Zichao Yun, Han Liu, Ruidong Wang, Xunhua Huang, and Haoyi Fan. "Semi-supervised Time Series Classification Model with Self-supervised Learning." Engineering Applications of Artificial Intelligence 116 (November 2022): 105331. http://dx.doi.org/10.1016/j.engappai.2022.105331.
Serey, Joel, Luis Quezada, Miguel Alfaro, Guillermo Fuertes, Manuel Vargas, Rodrigo Ternero, Jorge Sabattin, Claudia Duran, and Sebastian Gutierrez. "Artificial Intelligence Methodologies for Data Management." Symmetry 13, no. 11 (October 29, 2021): 2040. http://dx.doi.org/10.3390/sym13112040.
Kozhuharov, Mihail. "Artificial Intelligence: Basic Concepts." Педагогически форум 11, no. 4 (2023): 3–24. http://dx.doi.org/10.15547/pf.2023.023.
Takama, Yasufumi. "Web Intelligence and Artificial Intelligence." Journal of Advanced Computational Intelligence and Intelligent Informatics 21, no. 1 (January 20, 2017): 25–30. http://dx.doi.org/10.20965/jaciii.2017.p0025.
Ledziński, Łukasz, and Grzegorz Grześk. "Artificial Intelligence Technologies in Cardiology." Journal of Cardiovascular Development and Disease 10, no. 5 (May 6, 2023): 202. http://dx.doi.org/10.3390/jcdd10050202.
Yamauchi, K., M. Oota, and N. Ishii. "A self-supervised learning system for pattern recognition by sensory integration." Neural Networks 12, no. 10 (December 1999): 1347–58. http://dx.doi.org/10.1016/s0893-6080(99)00064-7.
Dushkin, R. V. "Semantic Supervised Training for General Artificial Cognitive Agents." Siberian Journal of Philosophy 19, no. 2 (October 21, 2021): 51–64. http://dx.doi.org/10.25205/2541-7517-2021-19-2-51-64.
Florence, Peter, Lucas Manuelli, and Russ Tedrake. "Self-Supervised Correspondence in Visuomotor Policy Learning." IEEE Robotics and Automation Letters 5, no. 2 (April 2020): 492–99. http://dx.doi.org/10.1109/lra.2019.2956365.
Pal, S. K., A. Pathak, and C. Basu. "Dynamic guard zone for self-supervised learning." Pattern Recognition Letters 7, no. 3 (March 1988): 135–44. http://dx.doi.org/10.1016/0167-8655(88)90056-6.
Soni, Kuldeep, Nidhi Pateria, and Gulafsha Anjum. "Artificial Intelligence and Machine Learning in Sport Medicines." International Journal of Innovative Research in Computer and Communication Engineering 12, Special Is (March 25, 2024): 69–73. http://dx.doi.org/10.15680/ijircce.2024.1203511.
Li, Li, Kaiyi Zhao, Sicong Li, Ruizhi Sun, and Saihua Cai. "Extreme Learning Machine for Supervised Classification with Self-paced Learning." Neural Processing Letters 52, no. 3 (June 14, 2020): 1723–44. http://dx.doi.org/10.1007/s11063-020-10286-9.
Miranda, Enrique, and Jordi Suñé. "Memristors for Neuromorphic Circuits and Artificial Intelligence Applications." Materials 13, no. 4 (February 20, 2020): 938. http://dx.doi.org/10.3390/ma13040938.
Mody, Rohit, Debabrata Dash, and Deepanshu Mody. "Artificial intelligence in coronary physiology: where do we stand?" Journal of Transcatheter Interventions 30 (October 28, 2022): 1–9. http://dx.doi.org/10.31160/jotci202230a20220009.
Okadome, Yuya, Kenshiro Ata, Hiroshi Ishiguro, and Yutaka Nakamura. "Self-supervised Learning Method for Behavior Prediction during Dialogue Based on Temporal Consistency." Transactions of the Japanese Society for Artificial Intelligence 37, no. 6 (November 1, 2022): B—M43_1–13. http://dx.doi.org/10.1527/tjsai.37-6_b-m43.
Benavides-Prado, Diana, Yun Sing Koh, and Patricia Riddle. "Towards Knowledgeable Supervised Lifelong Learning Systems." Journal of Artificial Intelligence Research 68 (May 8, 2020): 159–224. http://dx.doi.org/10.1613/jair.1.11432.
Okori, Washington, and Joseph Obua. "SUPERVISED LEARNING ALGORITHMS FOR FAMINE PREDICTION." Applied Artificial Intelligence 25, no. 9 (October 2011): 822–35. http://dx.doi.org/10.1080/08839514.2011.611930.
Poulos, Jason, and Rafael Valle. "Missing Data Imputation for Supervised Learning." Applied Artificial Intelligence 32, no. 2 (March 19, 2018): 186–96. http://dx.doi.org/10.1080/08839514.2018.1448143.
Weinlichová, Jana, and Jiří Fejfar. "Usage of self-organizing neural networks in evaluation of consumer behaviour." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 58, no. 6 (2010): 625–32. http://dx.doi.org/10.11118/actaun201058060625.
Hashimoto, Daniel A., Elan Witkowski, Lei Gao, Ozanan Meireles, and Guy Rosman. "Artificial Intelligence in Anesthesiology." Anesthesiology 132, no. 2 (February 1, 2020): 379–94. http://dx.doi.org/10.1097/aln.0000000000002960.
Lu, Keyu, Chengyi Zeng, and Yonghu Zeng. "Self-supervised learning of monocular depth using quantized networks." Neurocomputing 488 (June 2022): 634–46. http://dx.doi.org/10.1016/j.neucom.2021.11.071.
Hou, Wenjie, Zheyun Qin, Xiaoming Xi, Xiankai Lu, and Yilong Yin. "Learning disentangled representation for self-supervised video object segmentation." Neurocomputing 481 (April 2022): 270–80. http://dx.doi.org/10.1016/j.neucom.2022.01.066.
Chen, Long, Wen Tang, Tao Ruan Wan, and Nigel W. John. "Self-supervised monocular image depth learning and confidence estimation." Neurocomputing 381 (March 2020): 272–81. http://dx.doi.org/10.1016/j.neucom.2019.11.038.
Aryal, Gopi. "Artificial intelligence in surgical pathology." Journal of Pathology of Nepal 9, no. 1 (April 2, 2019): I. http://dx.doi.org/10.3126/jpn.v9i1.23444.
Xu, Rongge, Ruiyang Hao, and Biqing Huang. "Efficient surface defect detection using self-supervised learning strategy and segmentation network." Advanced Engineering Informatics 52 (April 2022): 101566. http://dx.doi.org/10.1016/j.aei.2022.101566.
Liu, Chicheng, Libin Song, Jiwen Zhang, Ken Chen, and Jing Xu. "Self-Supervised Learning for Specified Latent Representation." IEEE Transactions on Fuzzy Systems 28, no. 1 (January 2020): 47–59. http://dx.doi.org/10.1109/tfuzz.2019.2904237.
PETROVIC, SMILJANA, and SUSAN L. EPSTEIN. "RANDOM SUBSETS SUPPORT LEARNING A MIXTURE OF HEURISTICS." International Journal on Artificial Intelligence Tools 17, no. 03 (June 2008): 501–20. http://dx.doi.org/10.1142/s0218213008004023.
Xu, Ke, Guoqiang Zhong, Zhaoyang Deng, Kang Zhang, and Kaizhu Huang. "Self-supervised generative learning for sequential data prediction." Applied Intelligence, April 20, 2023. http://dx.doi.org/10.1007/s10489-023-04578-5.
"Artificial Intelligence Methodologies for Supervised Learning." International Journal of Advanced Research in Big Data Management System 3, no. 1 (May 30, 2019). http://dx.doi.org/10.21742/ijarbms.2019.3.1.03.
Li, Simou, Yuxing Mao, Jian Li, Yihang Xu, Jinsen Li, Xueshuo Chen, Siyang Liu, and Xianping Zhao. "FedUTN: federated self-supervised learning with updating target network." Applied Intelligence, August 26, 2022. http://dx.doi.org/10.1007/s10489-022-04070-6.
Kim, Sangwon, Jimi Lee, and Byoung Chul Ko. "SSL-MOT: self-supervised learning based multi-object tracking." Applied Intelligence, April 22, 2022. http://dx.doi.org/10.1007/s10489-022-03473-9.
Wang, Zhipeng, Chunping Hou, Guanghui Yue, and Qingyuan Yang. "Dynamic-boosting attention for self-supervised video representation learning." Applied Intelligence, July 1, 2021. http://dx.doi.org/10.1007/s10489-021-02440-0.
Hafez, Muhammad Burhan, and Stefan Wermter. "Continual Robot Learning Using Self-Supervised Task Inference." IEEE Transactions on Cognitive and Developmental Systems, 2023, 1. http://dx.doi.org/10.1109/tcds.2023.3315513.
Wang, Jing, Jun Wu, Caiyan Jia, and Zhifei Zhang. "Self-supervised variational autoencoder towards recommendation by nested contrastive learning." Applied Intelligence, February 14, 2023. http://dx.doi.org/10.1007/s10489-023-04488-6.
Li, Jinlong, Zequn Jie, Xu Wang, Yu Zhou, Lin Ma, and Jianmin Jiang. "Weakly supervised semantic segmentation via self-supervised destruction learning." Neurocomputing, September 2023, 126821. http://dx.doi.org/10.1016/j.neucom.2023.126821.
Liu, Jiabin, Biao Li, Minglong Lei, and Yong Shi. "Self-supervised knowledge distillation for complementary label learning." Neural Networks, August 2022. http://dx.doi.org/10.1016/j.neunet.2022.08.014.
Huang, Lang, Chao Zhang, and Hongyang Zhang. "Self-Adaptive Training: Bridging Supervised and Self-Supervised Learning." IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 1–17. http://dx.doi.org/10.1109/tpami.2022.3217792.
Rafiei, Mohammad H., Lynne V. Gauthier, Hojjat Adeli, and Daniel Takabi. "Self-Supervised Learning for Electroencephalography." IEEE Transactions on Neural Networks and Learning Systems, 2022, 1–15. http://dx.doi.org/10.1109/tnnls.2022.3190448.
Ye, Fei, and Adrian G. Bors. "Self-supervised adversarial variational learning." Pattern Recognition, November 2023, 110156. http://dx.doi.org/10.1016/j.patcog.2023.110156.
Verleysen, Andreas, Matthijs Biondina, and Francis wyffels. "Learning self-supervised task progression metrics: a case of cloth folding." Applied Intelligence, May 2, 2022. http://dx.doi.org/10.1007/s10489-022-03466-8.