Journal articles on the topic '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.
Full textCHAN, 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.
Full textYuya, 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.
Full textHrycej, 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.
Full textWang, 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.
Full textBiscione, 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.
Full textMa, 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.
Full textChe, 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.
Full textGu, 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.
Full textSaravana 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.
Full textWei, 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.
Full textXi, 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.
Full textSerey, 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.
Full textKozhuharov, Mihail. "Artificial Intelligence: Basic Concepts." Педагогически форум 11, no. 4 (2023): 3–24. http://dx.doi.org/10.15547/pf.2023.023.
Full textTakama, 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.
Full textLedziński, 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.
Full textYamauchi, 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.
Full textDushkin, 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.
Full textFlorence, 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.
Full textPal, 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.
Full textSoni, 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.
Full textLi, 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.
Full textMiranda, 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.
Full textMody, 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.
Full textOkadome, 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.
Full textBenavides-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.
Full textOkori, 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.
Full textPoulos, 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.
Full textWeinlichová, 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.
Full textHashimoto, 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.
Full textLu, 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.
Full textHou, 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.
Full textChen, 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.
Full textAryal, 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.
Full textXu, 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.
Full textLiu, 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.
Full textPETROVIC, 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.
Full textXu, 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.
Full text"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.
Full textLi, 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.
Full textKim, 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.
Full textWang, 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.
Full textHafez, 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.
Full textWang, 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.
Full textLi, 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.
Full textLiu, 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.
Full textHuang, 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.
Full textRafiei, 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.
Full textYe, 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.
Full textVerleysen, 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.
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