Статті в журналах з теми "Domain Adversarial Learning"
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Rosenberg, Ishai, Asaf Shabtai, Yuval Elovici, and Lior Rokach. "Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain." ACM Computing Surveys 54, no. 5 (June 2021): 1–36. http://dx.doi.org/10.1145/3453158.
Повний текст джерелаXu, Minghao, Jian Zhang, Bingbing Ni, Teng Li, Chengjie Wang, Qi Tian, and Wenjun Zhang. "Adversarial Domain Adaptation with Domain Mixup." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6502–9. http://dx.doi.org/10.1609/aaai.v34i04.6123.
Повний текст джерелаWu, Lan, Chongyang Li, Qiliang Chen, and Binquan Li. "Deep adversarial domain adaptation network." International Journal of Advanced Robotic Systems 17, no. 5 (September 1, 2020): 172988142096464. http://dx.doi.org/10.1177/1729881420964648.
Повний текст джерелаZhou, Kaiyang, Yongxin Yang, Timothy Hospedales, and Tao Xiang. "Deep Domain-Adversarial Image Generation for Domain Generalisation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 13025–32. http://dx.doi.org/10.1609/aaai.v34i07.7003.
Повний текст джерелаChen, Minghao, Shuai Zhao, Haifeng Liu, and Deng Cai. "Adversarial-Learned Loss for Domain Adaptation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 3521–28. http://dx.doi.org/10.1609/aaai.v34i04.5757.
Повний текст джерелаWu, Yuan, and Yuhong Guo. "Dual Adversarial Co-Learning for Multi-Domain Text Classification." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6438–45. http://dx.doi.org/10.1609/aaai.v34i04.6115.
Повний текст джерелаZou, Han, Yuxun Zhou, Jianfei Yang, Huihan Liu, Hari Prasanna Das, and Costas J. Spanos. "Consensus Adversarial Domain Adaptation." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5997–6004. http://dx.doi.org/10.1609/aaai.v33i01.33015997.
Повний текст джерелаTang, Hui, and Kui Jia. "Discriminative Adversarial Domain Adaptation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 5940–47. http://dx.doi.org/10.1609/aaai.v34i04.6054.
Повний текст джерелаLi, Wenjing, and Zhongcheng Wu. "OVL: One-View Learning for Human Retrieval." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 11410–17. http://dx.doi.org/10.1609/aaai.v34i07.6804.
Повний текст джерелаNguyen Duc, Tho, Chanh Minh Tran, Phan Xuan Tan, and Eiji Kamioka. "Domain Adaptation for Imitation Learning Using Generative Adversarial Network." Sensors 21, no. 14 (July 9, 2021): 4718. http://dx.doi.org/10.3390/s21144718.
Повний текст джерелаWALCZAK, STEVEN. "PATTERN-BASED TACTICAL PLANNING." International Journal of Pattern Recognition and Artificial Intelligence 06, no. 05 (December 1992): 955–88. http://dx.doi.org/10.1142/s0218001492000473.
Повний текст джерелаJia, Meixia, Jinrui Wang, Zongzhen Zhang, Baokun Han, Zhaoting Shi, Lei Guo, and Weitao Zhao. "A novel method for diagnosing bearing transfer faults based on a maximum mean discrepancies guided domain-adversarial mechanism." Measurement Science and Technology 33, no. 1 (November 26, 2021): 015109. http://dx.doi.org/10.1088/1361-6501/ac346e.
Повний текст джерелаRasheed, Bader, Adil Khan, Muhammad Ahmad, Manuel Mazzara, and S. M. Ahsan Kazmi. "Multiple Adversarial Domains Adaptation Approach for Mitigating Adversarial Attacks Effects." International Transactions on Electrical Energy Systems 2022 (October 10, 2022): 1–11. http://dx.doi.org/10.1155/2022/2890761.
Повний текст джерелаWu, Hanjie, Yongtuo Liu, Hongmin Cai, and Shengfeng He. "Learning Transferable Perturbations for Image Captioning." ACM Transactions on Multimedia Computing, Communications, and Applications 18, no. 2 (May 31, 2022): 1–18. http://dx.doi.org/10.1145/3478024.
Повний текст джерелаXue, Qianming, Wei Zhang, and Hongyuan Zha. "Improving Domain-Adapted Sentiment Classification by Deep Adversarial Mutual Learning." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 9362–69. http://dx.doi.org/10.1609/aaai.v34i05.6477.
Повний текст джерелаYang, Kaichen, Tzungyu Tsai, Honggang Yu, Tsung-Yi Ho, and Yier Jin. "Beyond Digital Domain: Fooling Deep Learning Based Recognition System in Physical World." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (April 3, 2020): 1088–95. http://dx.doi.org/10.1609/aaai.v34i01.5459.
Повний текст джерелаDixit, Akhil. "Few-Shot Learning under Domain Shift using Adversarial Domain Adaptation." International Journal for Research in Applied Science and Engineering Technology 7, no. 9 (September 30, 2019): 969–76. http://dx.doi.org/10.22214/ijraset.2019.9135.
Повний текст джерелаJan, Steve T. K., Joseph Messou, Yen-Chen Lin, Jia-Bin Huang, and Gang Wang. "Connecting the Digital and Physical World: Improving the Robustness of Adversarial Attacks." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 962–69. http://dx.doi.org/10.1609/aaai.v33i01.3301962.
Повний текст джерелаLeece, Michael. "Unsupervised Learning of HTNs in Complex Adversarial Domains." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 10, no. 6 (June 29, 2021): 6–9. http://dx.doi.org/10.1609/aiide.v10i6.12697.
Повний текст джерелаLi, Ranran, Shunming Li, Kun Xu, Xianglian Li, Jiantao Lu, Mengjie Zeng, Miaozhen Li, and Jun Du. "Adversarial domain adaptation of asymmetric mapping with CORAL alignment for intelligent fault diagnosis." Measurement Science and Technology 33, no. 5 (February 1, 2022): 055101. http://dx.doi.org/10.1088/1361-6501/ac3d47.
Повний текст джерелаFeiyan Fan, Feiyan Fan, Jiazhen Hou Feiyan Fan, and Tanghuai Fan Jiazhen Hou. "Fault Diagnosis under Varying Working Conditions with Domain Adversarial Capsule Networks." 電腦學刊 33, no. 3 (June 2022): 135–46. http://dx.doi.org/10.53106/199115992022063303011.
Повний текст джерелаWang, Ximei, Liang Li, Weirui Ye, Mingsheng Long, and Jianmin Wang. "Transferable Attention for Domain Adaptation." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5345–52. http://dx.doi.org/10.1609/aaai.v33i01.33015345.
Повний текст джерелаLi, Haoliang, Sinno Jialin Pan, Renjie Wan, and Alex C. Kot. "Heterogeneous Transfer Learning via Deep Matrix Completion with Adversarial Kernel Embedding." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8602–9. http://dx.doi.org/10.1609/aaai.v33i01.33018602.
Повний текст джерелаChen, Jifa, Guojun Zhai, Gang Chen, Bo Fang, Ping Zhou, and Nan Yu. "Unsupervised Domain Adaption for High-Resolution Coastal Land Cover Mapping with Category-Space Constrained Adversarial Network." Remote Sensing 13, no. 8 (April 13, 2021): 1493. http://dx.doi.org/10.3390/rs13081493.
Повний текст джерелаHuo, Lin, Huanchao Qi, Simiao Fei, Cong Guan, and Ji Li. "A Generative Adversarial Network Based a Rolling Bearing Data Generation Method Towards Fault Diagnosis." Computational Intelligence and Neuroscience 2022 (July 13, 2022): 1–21. http://dx.doi.org/10.1155/2022/7592258.
Повний текст джерелаWang, Jinrui, Shanshan Ji, Baokun Han, Huaiqian Bao, and Xingxing Jiang. "Deep Adaptive Adversarial Network-Based Method for Mechanical Fault Diagnosis under Different Working Conditions." Complexity 2020 (July 23, 2020): 1–11. http://dx.doi.org/10.1155/2020/6946702.
Повний текст джерелаNoa, J., P. J. Soto, G. A. O. P. Costa, D. Wittich, R. Q. Feitosa, and F. Rottensteiner. "ADVERSARIAL DISCRIMINATIVE DOMAIN ADAPTATION FOR DEFORESTATION DETECTION." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2021 (June 17, 2021): 151–58. http://dx.doi.org/10.5194/isprs-annals-v-3-2021-151-2021.
Повний текст джерелаXiang, Shoubing, Jiangquan Zhang, Hongli Gao, Dalei Shi, and Liang Chen. "A Deep Transfer Learning Method for Bearing Fault Diagnosis Based on Domain Separation and Adversarial Learning." Shock and Vibration 2021 (June 18, 2021): 1–9. http://dx.doi.org/10.1155/2021/5540084.
Повний текст джерелаZhang, Yixin, and Zilei Wang. "Joint Adversarial Learning for Domain Adaptation in Semantic Segmentation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6877–84. http://dx.doi.org/10.1609/aaai.v34i04.6169.
Повний текст джерелаHuang, Min, and Jinghan Yin. "Research on Adversarial Domain Adaptation Method and Its Application in Power Load Forecasting." Mathematics 10, no. 18 (September 6, 2022): 3223. http://dx.doi.org/10.3390/math10183223.
Повний текст джерелаKushchuk, Denis, Maxim Ryndin, Alexander Yatskov, and Maksim Varlamov. "Using Domain Adversarial Learning for Text Captchas Recognition." Proceedings of the Institute for System Programming of the RAS 32, no. 4 (2020): 203–16. http://dx.doi.org/10.15514/ispras-2020-32(4)-15.
Повний текст джерелаWang, Shanshan, Lei Zhang, and Jingru Fu. "Adversarial transfer learning for cross-domain visual recognition." Knowledge-Based Systems 204 (September 2020): 106258. http://dx.doi.org/10.1016/j.knosys.2020.106258.
Повний текст джерелаGrießhaber, Daniel, Ngoc Thang Vu, and Johannes Maucher. "Low-resource text classification using domain-adversarial learning." Computer Speech & Language 62 (July 2020): 101056. http://dx.doi.org/10.1016/j.csl.2019.101056.
Повний текст джерелаWang, Peng (Edward), and Matthew Russell. "Domain Adversarial Transfer Learning for Generalized Tool Wear Prediction." Annual Conference of the PHM Society 12, no. 1 (November 3, 2020): 8. http://dx.doi.org/10.36001/phmconf.2020.v12i1.1137.
Повний текст джерелаChen, Keyu, Di Zhuang, and J. Morris Chang. "Discriminative adversarial domain generalization with meta-learning based cross-domain validation." Neurocomputing 467 (January 2022): 418–26. http://dx.doi.org/10.1016/j.neucom.2021.09.046.
Повний текст джерелаPan, Boxiao, Zhangjie Cao, Ehsan Adeli, and Juan Carlos Niebles. "Adversarial Cross-Domain Action Recognition with Co-Attention." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 11815–22. http://dx.doi.org/10.1609/aaai.v34i07.6854.
Повний текст джерелаVitorino, João, Nuno Oliveira, and Isabel Praça. "Adaptative Perturbation Patterns: Realistic Adversarial Learning for Robust Intrusion Detection." Future Internet 14, no. 4 (March 29, 2022): 108. http://dx.doi.org/10.3390/fi14040108.
Повний текст джерелаZhao, Liquan, and Yan Liu. "Spectral Normalization for Domain Adaptation." Information 11, no. 2 (January 27, 2020): 68. http://dx.doi.org/10.3390/info11020068.
Повний текст джерелаMao, Ye, Farzaneh Khoshnevisan, Thomas Price, Tiffany Barnes, and Min Chi. "Cross-Lingual Adversarial Domain Adaptation for Novice Programming." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 7 (June 28, 2022): 7682–90. http://dx.doi.org/10.1609/aaai.v36i7.20735.
Повний текст джерелаSoto, P. J., G. A. O. P. Costa, R. Q. Feitosa, P. N. Happ, M. X. Ortega, J. Noa, C. A. Almeida, and C. Heipke. "DOMAIN ADAPTATION WITH CYCLEGAN FOR CHANGE DETECTION IN THE AMAZON FOREST." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 22, 2020): 1635–43. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1635-2020.
Повний текст джерелаZhang, Yuan, Regina Barzilay, and Tommi Jaakkola. "Aspect-augmented Adversarial Networks for Domain Adaptation." Transactions of the Association for Computational Linguistics 5 (December 2017): 515–28. http://dx.doi.org/10.1162/tacl_a_00077.
Повний текст джерелаHasan, S. M. Kamrul, and Cristian A. Linte. "Learning Deep Representations of Cardiac Structures for 4D Cine MRI Image Segmentation through Semi-Supervised Learning." Applied Sciences 12, no. 23 (November 28, 2022): 12163. http://dx.doi.org/10.3390/app122312163.
Повний текст джерелаCao, Yu, Meng Fang, Baosheng Yu, and Joey Tianyi Zhou. "Unsupervised Domain Adaptation on Reading Comprehension." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 7480–87. http://dx.doi.org/10.1609/aaai.v34i05.6245.
Повний текст джерелаWang, Xingmei, Boxuan Sun, and Hongbin Dong. "Domain-invariant adversarial learning with conditional distribution alignment for unsupervised domain adaptation." IET Computer Vision 14, no. 8 (December 1, 2020): 642–49. http://dx.doi.org/10.1049/iet-cvi.2019.0514.
Повний текст джерелаYuan, Yumeng, Yuhua Li, Zhenlong Zhu, Ruixuan Li, and Xiwu Gu. "Joint Domain Adaptation Based on Adversarial Dynamic Parameter Learning." IEEE Transactions on Emerging Topics in Computational Intelligence 5, no. 4 (August 2021): 714–23. http://dx.doi.org/10.1109/tetci.2021.3055873.
Повний текст джерелаYu, Hao, and Mengqi Hu. "Epilepsy SEEG Data Classification Based On Domain Adversarial Learning." IEEE Access 9 (2021): 82000–82009. http://dx.doi.org/10.1109/access.2021.3086885.
Повний текст джерелаDing, Xiao, Qiankun Shi, Bibo Cai, Ting Liu, Yanyan Zhao, and Qiang Ye. "Learning Multi-Domain Adversarial Neural Networks for Text Classification." IEEE Access 7 (2019): 40323–32. http://dx.doi.org/10.1109/access.2019.2904858.
Повний текст джерелаZhao, Xin, and Shengsheng Wang. "Adversarial Learning and Interpolation Consistency for Unsupervised Domain Adaptation." IEEE Access 7 (2019): 170448–56. http://dx.doi.org/10.1109/access.2019.2956103.
Повний текст джерелаQian, Qi, Shenghuo Zhu, Jiasheng Tang, Rong Jin, Baigui Sun, and Hao Li. "Robust Optimization over Multiple Domains." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 4739–46. http://dx.doi.org/10.1609/aaai.v33i01.33014739.
Повний текст джерелаKwon, Hyun, and Sanghyun Lee. "Textual Adversarial Training of Machine Learning Model for Resistance to Adversarial Examples." Security and Communication Networks 2022 (April 7, 2022): 1–12. http://dx.doi.org/10.1155/2022/4511510.
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