Artigos de revistas sobre o tema "Self-Supervised models"
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Anton, Jonah, Liam Castelli, Mun Fai Chan, Mathilde Outters, Wan Hee Tang, Venus Cheung, Pancham Shukla, Rahee Walambe e Ketan Kotecha. "How Well Do Self-Supervised Models Transfer to Medical Imaging?" Journal of Imaging 8, n.º 12 (1 de dezembro de 2022): 320. http://dx.doi.org/10.3390/jimaging8120320.
Texto completo da fonteGatopoulos, Ioannis, e Jakub M. Tomczak. "Self-Supervised Variational Auto-Encoders". Entropy 23, n.º 6 (14 de junho de 2021): 747. http://dx.doi.org/10.3390/e23060747.
Texto completo da fonteZhang, Ronghua, Yuanyuan Wang, Fangyuan Liu, Changzheng Liu, Yaping Song e Baohua Yu. "S2NMF: Information Self-Enhancement Self-Supervised Nonnegative Matrix Factorization for Recommendation". Wireless Communications and Mobile Computing 2022 (30 de agosto de 2022): 1–10. http://dx.doi.org/10.1155/2022/4748858.
Texto completo da fonteDang, Thanh-Vu, JinYoung Kim, Gwang-Hyun Yu, Ji Yong Kim, Young Hwan Park e ChilWoo Lee. "Korean Text to Gloss: Self-Supervised Learning approach". Korean Institute of Smart Media 12, n.º 1 (28 de fevereiro de 2023): 32–46. http://dx.doi.org/10.30693/smj.2023.12.1.32.
Texto completo da fonteRisojević, V., e V. Stojnić. "DO WE STILL NEED IMAGENET PRE-TRAINING IN REMOTE SENSING SCENE CLASSIFICATION?" International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (31 de maio de 2022): 1399–406. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-1399-2022.
Texto completo da fonteImran, Abdullah-Al-Zubaer, Chao Huang, Hui Tang, Wei Fan, Yuan Xiao, Dingjun Hao, Zhen Qian e Demetri Terzopoulos. "Self-Supervised, Semi-Supervised, Multi-Context Learning for the Combined Classification and Segmentation of Medical Images (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 10 (3 de abril de 2020): 13815–16. http://dx.doi.org/10.1609/aaai.v34i10.7179.
Texto completo da fonteZhou, Meng, Zechen Li e Pengtao Xie. "Self-supervised Regularization for Text Classification". Transactions of the Association for Computational Linguistics 9 (2021): 641–56. http://dx.doi.org/10.1162/tacl_a_00389.
Texto completo da fonteGong, Yuan, Cheng-I. Lai, Yu-An Chung e James Glass. "SSAST: Self-Supervised Audio Spectrogram Transformer". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 10 (28 de junho de 2022): 10699–709. http://dx.doi.org/10.1609/aaai.v36i10.21315.
Texto completo da fonteChen, Xuehao, Jin Zhou, Yuehui Chen, Shiyuan Han, Yingxu Wang, Tao Du, Cheng Yang e Bowen Liu. "Self-Supervised Clustering Models Based on BYOL Network Structure". Electronics 12, n.º 23 (21 de novembro de 2023): 4723. http://dx.doi.org/10.3390/electronics12234723.
Texto completo da fonteLuo, Dezhao, Chang Liu, Yu Zhou, Dongbao Yang, Can Ma, Qixiang Ye e Weiping Wang. "Video Cloze Procedure for Self-Supervised Spatio-Temporal Learning". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 07 (3 de abril de 2020): 11701–8. http://dx.doi.org/10.1609/aaai.v34i07.6840.
Texto completo da fonteTuncal, Kubra, Boran Sekeroglu e Rahib Abiyev. "Self-Supervised and Supervised Image Enhancement Networks with Time-Shift Module". Electronics 13, n.º 12 (13 de junho de 2024): 2313. http://dx.doi.org/10.3390/electronics13122313.
Texto completo da fonteKnoedler, Luzia, Chadi Salmi, Hai Zhu, Bruno Brito e Javier Alonso-Mora. "Improving Pedestrian Prediction Models With Self-Supervised Continual Learning". IEEE Robotics and Automation Letters 7, n.º 2 (abril de 2022): 4781–88. http://dx.doi.org/10.1109/lra.2022.3148475.
Texto completo da fontePasad, Ankita, Chung-Ming Chien, Shane Settle e Karen Livescu. "What Do Self-Supervised Speech Models Know About Words?" Transactions of the Association for Computational Linguistics 12 (2024): 372–91. http://dx.doi.org/10.1162/tacl_a_00656.
Texto completo da fonteLi, Jingwei, Chi Zhang, Linyuan Wang, Penghui Ding, Lulu Hu, Bin Yan e Li Tong. "A Visual Encoding Model Based on Contrastive Self-Supervised Learning for Human Brain Activity along the Ventral Visual Stream". Brain Sciences 11, n.º 8 (29 de julho de 2021): 1004. http://dx.doi.org/10.3390/brainsci11081004.
Texto completo da fonteScheibenreif, L., M. Mommert e D. Borth. "CONTRASTIVE SELF-SUPERVISED DATA FUSION FOR SATELLITE IMAGERY". ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2022 (17 de maio de 2022): 705–11. http://dx.doi.org/10.5194/isprs-annals-v-3-2022-705-2022.
Texto completo da fonteYuan, Guotao, Hong Huang e Xin Li. "Self-supervised learning backdoor defense mixed with self-attention mechanism". Journal of Computing and Electronic Information Management 12, n.º 2 (30 de março de 2024): 81–88. http://dx.doi.org/10.54097/7hx9afkw.
Texto completo da fonteZhang, Ye. "Application of self-supervised learning in natural language processing". Journal of Computing and Electronic Information Management 12, n.º 1 (28 de fevereiro de 2024): 23–26. http://dx.doi.org/10.54097/urpv6i8g3j.
Texto completo da fonteDominic, Jeffrey, Nandita Bhaskhar, Arjun D. Desai, Andrew Schmidt, Elka Rubin, Beliz Gunel, Garry E. Gold et al. "Improving Data-Efficiency and Robustness of Medical Imaging Segmentation Using Inpainting-Based Self-Supervised Learning". Bioengineering 10, n.º 2 (4 de fevereiro de 2023): 207. http://dx.doi.org/10.3390/bioengineering10020207.
Texto completo da fonteZeng, Jiaqi, e Pengtao Xie. "Contrastive Self-supervised Learning for Graph Classification". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 12 (18 de maio de 2021): 10824–32. http://dx.doi.org/10.1609/aaai.v35i12.17293.
Texto completo da fonteWagner, Royden, Carlos Fernandez Lopez e Christoph Stiller. "Self-supervised pseudo-colorizing of masked cells". PLOS ONE 18, n.º 8 (24 de agosto de 2023): e0290561. http://dx.doi.org/10.1371/journal.pone.0290561.
Texto completo da fonteLiu, Yuanyuan, e Qianqian Liu. "Research on Self-Supervised Comparative Learning for Computer Vision". Journal of Electronic Research and Application 5, n.º 3 (17 de agosto de 2021): 5–17. http://dx.doi.org/10.26689/jera.v5i3.2320.
Texto completo da fonteEsser, Pascal, Maximilian Fleissner e Debarghya Ghoshdastidar. "Non-parametric Representation Learning with Kernels". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 11 (24 de março de 2024): 11910–18. http://dx.doi.org/10.1609/aaai.v38i11.29077.
Texto completo da fontePolceanu, Mihai, Julie Porteous, Alan Lindsay e Marc Cavazza. "Narrative Plan Generation with Self-Supervised Learning". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 7 (18 de maio de 2021): 5984–92. http://dx.doi.org/10.1609/aaai.v35i7.16747.
Texto completo da fonteTóth, Martos, e Nelson Sommerfeldt. "PV self-consumption prediction methods using supervised machine learning". E3S Web of Conferences 362 (2022): 02003. http://dx.doi.org/10.1051/e3sconf/202236202003.
Texto completo da fonteMustapha, Ahmad, Wael Khreich e Wes Masri. "Inter-model interpretability: Self-supervised models as a case study". Array 22 (julho de 2024): 100350. http://dx.doi.org/10.1016/j.array.2024.100350.
Texto completo da fonteShi, Haizhou, Youcai Zhang, Siliang Tang, Wenjie Zhu, Yaqian Li, Yandong Guo e Yueting Zhuang. "On the Efficacy of Small Self-Supervised Contrastive Models without Distillation Signals". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 2 (28 de junho de 2022): 2225–34. http://dx.doi.org/10.1609/aaai.v36i2.20120.
Texto completo da fonteMakarov, Ilya, Maria Bakhanova, Sergey Nikolenko e Olga Gerasimova. "Self-supervised recurrent depth estimation with attention mechanisms". PeerJ Computer Science 8 (31 de janeiro de 2022): e865. http://dx.doi.org/10.7717/peerj-cs.865.
Texto completo da fonteHu, Fanghuai, Zhiqing Shao e Tong Ruan. "Self-Supervised Chinese Ontology Learning from Online Encyclopedias". Scientific World Journal 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/848631.
Texto completo da fonteShwartz Ziv, Ravid, e Yann LeCun. "To Compress or Not to Compress—Self-Supervised Learning and Information Theory: A Review". Entropy 26, n.º 3 (12 de março de 2024): 252. http://dx.doi.org/10.3390/e26030252.
Texto completo da fonteMontero Quispe, Kevin G., Daniel M. S. Utyiama, Eulanda M. dos Santos, Horácio A. B. F. Oliveira e Eduardo J. P. Souto. "Applying Self-Supervised Representation Learning for Emotion Recognition Using Physiological Signals". Sensors 22, n.º 23 (23 de novembro de 2022): 9102. http://dx.doi.org/10.3390/s22239102.
Texto completo da fonteLivieris, Ioannis, Andreas Kanavos, Vassilis Tampakas e Panagiotis Pintelas. "An Auto-Adjustable Semi-Supervised Self-Training Algorithm". Algorithms 11, n.º 9 (14 de setembro de 2018): 139. http://dx.doi.org/10.3390/a11090139.
Texto completo da fonteKahatapitiya, Kumara, Zhou Ren, Haoxiang Li, Zhenyu Wu, Michael S. Ryoo e Gang Hua. "Weakly-Guided Self-Supervised Pretraining for Temporal Activity Detection". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 1 (26 de junho de 2023): 1078–86. http://dx.doi.org/10.1609/aaai.v37i1.25189.
Texto completo da fonteCheng, Jiashun, Man Li, Jia Li e Fugee Tsung. "Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 6 (26 de junho de 2023): 7131–39. http://dx.doi.org/10.1609/aaai.v37i6.25870.
Texto completo da fonteFedden, Leon, Zhenning Zhang, Khan Baykaner, Qin Li e Lucas Bordeaux. "Abstract 1937: DIME-CT: Self-supervised learning for medical image analysis using patch-based embeddings". Cancer Research 82, n.º 12_Supplement (15 de junho de 2022): 1937. http://dx.doi.org/10.1158/1538-7445.am2022-1937.
Texto completo da fonteXu, Xiangdong, Krzysztof Przystupa e Orest Kochan. "Social Recommendation Algorithm Based on Self-Supervised Hypergraph Attention". Electronics 12, n.º 4 (10 de fevereiro de 2023): 906. http://dx.doi.org/10.3390/electronics12040906.
Texto completo da fonteManessi, Franco, e Alessandro Rozza. "Graph-based neural network models with multiple self-supervised auxiliary tasks". Pattern Recognition Letters 148 (agosto de 2021): 15–21. http://dx.doi.org/10.1016/j.patrec.2021.04.021.
Texto completo da fonteZhang, Jian, Jianing Yang, Jun Yu e Jianping Fan. "Semisupervised image classification by mutual learning of multiple self‐supervised models". International Journal of Intelligent Systems 37, n.º 5 (14 de janeiro de 2022): 3117–41. http://dx.doi.org/10.1002/int.22814.
Texto completo da fonteLiu, Gang, Silu He, Xing Han, Qinyao Luo, Ronghua Du, Xinsha Fu e Ling Zhao. "Self-Supervised Spatiotemporal Masking Strategy-Based Models for Traffic Flow Forecasting". Symmetry 15, n.º 11 (31 de outubro de 2023): 2002. http://dx.doi.org/10.3390/sym15112002.
Texto completo da fonteJoshi, Amey, Hrishitaa Kurchania e Harikrishnan R. "Robust Object Segmentation using 3D Mesh Models and Self-Supervised Learning". Procedia Computer Science 235 (2024): 907–15. http://dx.doi.org/10.1016/j.procs.2024.04.086.
Texto completo da fonteGao, Min, Yingmei Wei, Yuxiang Xie e Yitong Zhang. "Traffic Prediction with Self-Supervised Learning: A Heterogeneity-Aware Model for Urban Traffic Flow Prediction Based on Self-Supervised Learning". Mathematics 12, n.º 9 (24 de abril de 2024): 1290. http://dx.doi.org/10.3390/math12091290.
Texto completo da fonteXu, Yanjie, Hao Sun, Jin Chen, Lin Lei, Kefeng Ji e Gangyao Kuang. "Adversarial Self-Supervised Learning for Robust SAR Target Recognition". Remote Sensing 13, n.º 20 (17 de outubro de 2021): 4158. http://dx.doi.org/10.3390/rs13204158.
Texto completo da fonteJaved, Tahir, Kaushal Bhogale, Abhigyan Raman, Pratyush Kumar, Anoop Kunchukuttan e Mitesh M. Khapra. "IndicSUPERB: A Speech Processing Universal Performance Benchmark for Indian Languages". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 11 (26 de junho de 2023): 12942–50. http://dx.doi.org/10.1609/aaai.v37i11.26521.
Texto completo da fonteZhao, Nanxuan, Zhirong Wu, Rynson W. H. Lau e Stephen Lin. "Distilling Localization for Self-Supervised Representation Learning". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 12 (18 de maio de 2021): 10990–98. http://dx.doi.org/10.1609/aaai.v35i12.17312.
Texto completo da fonteGuo, Yuzhi, Jiaxiang Wu, Hehuan Ma e Junzhou Huang. "Self-Supervised Pre-training for Protein Embeddings Using Tertiary Structures". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 6 (28 de junho de 2022): 6801–9. http://dx.doi.org/10.1609/aaai.v36i6.20636.
Texto completo da fonteLin, Ken, Xiongwen Quan, Wenya Yin e Han Zhang. "A Contrastive Learning Pre-Training Method for Motif Occupancy Identification". International Journal of Molecular Sciences 23, n.º 9 (24 de abril de 2022): 4699. http://dx.doi.org/10.3390/ijms23094699.
Texto completo da fonteNimitsurachat, Peranut, e Peter Washington. "Audio-Based Emotion Recognition Using Self-Supervised Learning on an Engineered Feature Space". AI 5, n.º 1 (17 de janeiro de 2024): 195–207. http://dx.doi.org/10.3390/ai5010011.
Texto completo da fonteParmar, Chaitanya, Albert Juan Ramon, Nicole L. Stone, Spyros Triantos, Joel Greshock e Kristopher Standish. "Generalizable FGFR prediction across tumor types using self supervised learning." Journal of Clinical Oncology 41, n.º 16_suppl (1 de junho de 2023): e15057-e15057. http://dx.doi.org/10.1200/jco.2023.41.16_suppl.e15057.
Texto completo da fonteDíaz, Gabriel, Billy Peralta, Luis Caro e Orietta Nicolis. "Co-Training for Visual Object Recognition Based on Self-Supervised Models Using a Cross-Entropy Regularization". Entropy 23, n.º 4 (1 de abril de 2021): 423. http://dx.doi.org/10.3390/e23040423.
Texto completo da fonteChoudhary, Nurendra, Charu C. Aggarwal, Karthik Subbian e Chandan K. Reddy. "Self-supervised Short-text Modeling through Auxiliary Context Generation". ACM Transactions on Intelligent Systems and Technology 13, n.º 3 (30 de junho de 2022): 1–21. http://dx.doi.org/10.1145/3511712.
Texto completo da fonteZhang, Ming, Xin Gu, Ji Qi, Zhenshi Zhang, Hemeng Yang, Jun Xu, Chengli Peng e Haifeng Li. "CDEST: Class Distinguishability-Enhanced Self-Training Method for Adopting Pre-Trained Models to Downstream Remote Sensing Image Semantic Segmentation". Remote Sensing 16, n.º 7 (6 de abril de 2024): 1293. http://dx.doi.org/10.3390/rs16071293.
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