Artigos de revistas sobre o tema "Transformeur robuste"
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Yang, Mingze, Hai Zhu, Runzhe Zhu, Fei Wu, Ling Yin e Yuncheng Yang. "WiTransformer: A Novel Robust Gesture Recognition Sensing Model with WiFi". Sensors 23, n.º 5 (27 de fevereiro de 2023): 2612. http://dx.doi.org/10.3390/s23052612.
Texto completo da fonteSantamaria-Bonfil, Guillermo, Gustavo Arroyo-Figueroa, Miguel A. Zuniga-Garcia, Carlos Gustavo Azcarraga Ramos e Ali Bassam. "Power Transformer Fault Detection: A Comparison of Standard Machine Learning and autoML Approaches". Energies 17, n.º 1 (22 de dezembro de 2023): 77. http://dx.doi.org/10.3390/en17010077.
Texto completo da fonteWei, Jiangshu, Jinrong Chen, Yuchao Wang, Hao Luo e Wujie Li. "Improved deep learning image classification algorithm based on Swin Transformer V2". PeerJ Computer Science 9 (30 de outubro de 2023): e1665. http://dx.doi.org/10.7717/peerj-cs.1665.
Texto completo da fonteOttele, Andy, e Rahmat Shoureshi. "Neural Network-Based Adaptive Monitoring System for Power Transformer". Journal of Dynamic Systems, Measurement, and Control 123, n.º 3 (11 de fevereiro de 1999): 512–17. http://dx.doi.org/10.1115/1.1387248.
Texto completo da fonteSai, K. N., A. Galodha, P. Jain e D. Sharma. "DEEP AND MACHINE LEARNING FOR MONITORING GROUNDWATER STORAGE BASINS AND HYDROLOGICAL CHANGES USING THE GRAVITY RECOVERY AND CLIMATE EXPERIMENT (GRACE) SATELLITE MISSION AND SENTINEL-1 DATA FOR THE GANGA RIVER BASIN IN THE INDIAN REGION". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1/W2-2023 (13 de dezembro de 2023): 1265–70. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-w2-2023-1265-2023.
Texto completo da fonteRemigius Obinna Okeke, Akan Ime Ibokette, Onuh Matthew Ijiga, Enyejo, Lawrence Anebi, Godslove Isenyo Ebiega e Odeyemi Michael Olumubo. "THE RELIABILITY ASSESSMENT OF POWER TRANSFORMERS". Engineering Science & Technology Journal 5, n.º 4 (3 de abril de 2024): 1149–72. http://dx.doi.org/10.51594/estj.v5i4.981.
Texto completo da fontePaul, Sayak, e Pin-Yu Chen. "Vision Transformers Are Robust Learners". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 2 (28 de junho de 2022): 2071–81. http://dx.doi.org/10.1609/aaai.v36i2.20103.
Texto completo da fonteJancarczyk, Daniel, Marcin Bernaś e Tomasz Boczar. "Classification of Low Frequency Signals Emitted by Power Transformers Using Sensors and Machine Learning Methods". Sensors 19, n.º 22 (10 de novembro de 2019): 4909. http://dx.doi.org/10.3390/s19224909.
Texto completo da fonteCortés-Caicedo, Brandon, Oscar Danilo Montoya e Andrés Arias-Londoño. "Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures". Computers 11, n.º 4 (11 de abril de 2022): 55. http://dx.doi.org/10.3390/computers11040055.
Texto completo da fonteXie, Fei, Dalong Zhang e Chengming Liu. "Global–Local Self-Attention Based Transformer for Speaker Verification". Applied Sciences 12, n.º 19 (10 de outubro de 2022): 10154. http://dx.doi.org/10.3390/app121910154.
Texto completo da fonteLi, Jiangtao, Wenzhong Chen, Jianhao Li, Weihua Jiang, Xu Zhong e Yang Gou. "Robust Design for Linear Transformer Driver System". IEEE Transactions on Plasma Science 43, n.º 10 (outubro de 2015): 3406–11. http://dx.doi.org/10.1109/tps.2015.2429688.
Texto completo da fonteYang, Zhiqiang, Chong Xu e Lei Li. "Landslide Detection Based on ResU-Net with Transformer and CBAM Embedded: Two Examples with Geologically Different Environments". Remote Sensing 14, n.º 12 (16 de junho de 2022): 2885. http://dx.doi.org/10.3390/rs14122885.
Texto completo da fonteXiong, Lingxin, Jicun Zhang, Xiaojia Zheng e Yuxin Wang. "Context Transformer and Adaptive Method with Visual Transformer for Robust Facial Expression Recognition". Applied Sciences 14, n.º 4 (14 de fevereiro de 2024): 1535. http://dx.doi.org/10.3390/app14041535.
Texto completo da fonteSarraf, Saman, Arman Sarraf, Danielle D. DeSouza, John A. E. Anderson e Milton Kabia. "OViTAD: Optimized Vision Transformer to Predict Various Stages of Alzheimer’s Disease Using Resting-State fMRI and Structural MRI Data". Brain Sciences 13, n.º 2 (3 de fevereiro de 2023): 260. http://dx.doi.org/10.3390/brainsci13020260.
Texto completo da fonteKim, Mintai, e Sungju Lee. "Power Transformer Voltages Classification with Acoustic Signal in Various Noisy Environments". Sensors 22, n.º 3 (7 de fevereiro de 2022): 1248. http://dx.doi.org/10.3390/s22031248.
Texto completo da fonteIKEO, Shigeru, Weidong MA e Kazuhisa ITO. "Robust Position Control of Cylinder Using Hydraulic Transformer". TRANSACTIONS OF THE JAPAN FLUID POWER SYSTEM SOCIETY 36, n.º 2 (2005): 45–50. http://dx.doi.org/10.5739/jfps.36.45.
Texto completo da fonteHuang, Keju, Junan Yang, Hui Liu e Pengjiang Hu. "Channel-Robust Specific Emitter Identification Based on Transformer". Highlights in Science, Engineering and Technology 7 (3 de agosto de 2022): 71–76. http://dx.doi.org/10.54097/hset.v7i.1019.
Texto completo da fonteRao, Bingbing, Ehsan Kazemi, Yifan Ding, Devu M. Shila, Frank M. Tucker e Liqiang Wang. "CTIN: Robust Contextual Transformer Network for Inertial Navigation". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 5 (28 de junho de 2022): 5413–21. http://dx.doi.org/10.1609/aaai.v36i5.20479.
Texto completo da fonteLi, Wei, Zhixin Li, Xiwei Yang e Huifang Ma. "Causal-ViT: Robust Vision Transformer by causal intervention". Engineering Applications of Artificial Intelligence 126 (novembro de 2023): 107123. http://dx.doi.org/10.1016/j.engappai.2023.107123.
Texto completo da fonteWu, Zhiliang, Changchang Sun, Hanyu Xuan, Gaowen Liu e Yan Yan. "WaveFormer: Wavelet Transformer for Noise-Robust Video Inpainting". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 6 (24 de março de 2024): 6180–88. http://dx.doi.org/10.1609/aaai.v38i6.28435.
Texto completo da fonteBRESLIN, J. G., e W. G. HURLEY. "CRITICAL CHOICES IN A SYSTEM FOR OPTIMIZED DESIGN OF ARBITRARY WAVEFORM TRANSFORMERS". Journal of Circuits, Systems and Computers 13, n.º 04 (agosto de 2004): 919–28. http://dx.doi.org/10.1142/s0218126604001751.
Texto completo da fonteShahzad, Ebrahim, Adnan Umar Khan, Muhammad Iqbal, Ahmad Saeed, Ghulam Hafeez, Athar Waseem, Fahad R. Albogamy e Zahid Ullah. "Sensor Fault-Tolerant Control of Microgrid Using Robust Sliding-Mode Observer". Sensors 22, n.º 7 (25 de março de 2022): 2524. http://dx.doi.org/10.3390/s22072524.
Texto completo da fonteHuerta-Rosales, Jose R., David Granados-Lieberman, Juan P. Amezquita-Sanchez, David Camarena-Martinez e Martin Valtierra-Rodriguez. "Vibration Signal Processing-Based Detection of Short-Circuited Turns in Transformers: A Nonlinear Mode Decomposition Approach". Mathematics 8, n.º 4 (13 de abril de 2020): 575. http://dx.doi.org/10.3390/math8040575.
Texto completo da fonteRichardson, Kyle, e Ashish Sabharwal. "Pushing the Limits of Rule Reasoning in Transformers through Natural Language Satisfiability". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 10 (28 de junho de 2022): 11209–19. http://dx.doi.org/10.1609/aaai.v36i10.21371.
Texto completo da fonteZhang, Jie, Fan Li, Xin Zhang, Yue Cheng e Xinhong Hei. "Multi-Task Mean Teacher Medical Image Segmentation Based on Swin Transformer". Applied Sciences 14, n.º 7 (2 de abril de 2024): 2986. http://dx.doi.org/10.3390/app14072986.
Texto completo da fonteLi, Naihan, Yanqing Liu, Yu Wu, Shujie Liu, Sheng Zhao e Ming Liu. "RobuTrans: A Robust Transformer-Based Text-to-Speech Model". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 05 (3 de abril de 2020): 8228–35. http://dx.doi.org/10.1609/aaai.v34i05.6337.
Texto completo da fonteManzari, Omid Nejati, Hossein Kashiani, Hojat Asgarian Dehkordi e Shahriar B. Shokouhi. "Robust transformer with locality inductive bias and feature normalization". Engineering Science and Technology, an International Journal 38 (fevereiro de 2023): 101320. http://dx.doi.org/10.1016/j.jestch.2022.101320.
Texto completo da fonteEnders, Johannes, Warren B. Powell e David M. Egan. "Robust policies for the transformer acquisition and allocation problem". Energy Systems 1, n.º 3 (1 de abril de 2010): 245–72. http://dx.doi.org/10.1007/s12667-010-0011-8.
Texto completo da fonteXie, Yuanlun, Wenhong Tian e Zitong Yu. "Robust facial expression recognition with Transformer Block Enhancement Module". Engineering Applications of Artificial Intelligence 126 (novembro de 2023): 106795. http://dx.doi.org/10.1016/j.engappai.2023.106795.
Texto completo da fonteChen, Zhaohui, Elyas Asadi Shamsabadi, Sheng Jiang, Luming Shen e Daniel Dias-da-Costa. "An average pooling designed Transformer for robust crack segmentation". Automation in Construction 162 (junho de 2024): 105367. http://dx.doi.org/10.1016/j.autcon.2024.105367.
Texto completo da fonteWu, Shibin, Ruxin Zhang, Jiayi Yan, Chengquan Li, Qicai Liu, Liyang Wang e Haoqian Wang. "High-Speed and Accurate Diagnosis of Gastrointestinal Disease: Learning on Endoscopy Images Using Lightweight Transformer with Local Feature Attention". Bioengineering 10, n.º 12 (13 de dezembro de 2023): 1416. http://dx.doi.org/10.3390/bioengineering10121416.
Texto completo da fonteTafur Acenjo, Brenda Xiomara, Martin Alexis Tello Pariona e Edwin Jhonatan Escobedo Cárdenas. "Comparativa entre RESNET-50, VGG-16, Vision Transformer y Swin Transformer para el reconocimiento facial con oclusión de una mascarilla". Interfases, n.º 017 (23 de junho de 2023): e6361. http://dx.doi.org/10.26439/interfases2023.n017.6361.
Texto completo da fonteOlowolafe, Felix, e Kehinde Olukunmi Alawode. "Detection of Incipient Faults in Power Transformers using Fuzzy Logic and Decision Tree Models Based on Dissolved Gas Analysis". ABUAD Journal of Engineering Research and Development (AJERD) 7, n.º 1 (31 de março de 2024): 56–73. http://dx.doi.org/10.53982/ajerd.2024.0701.06-j.
Texto completo da fonteZhou, Qian, Hua Zou e Huanhuan Wu. "LGViT: A Local and Global Vision Transformer with Dynamic Contextual Position Bias Using Overlapping Windows". Applied Sciences 13, n.º 3 (3 de fevereiro de 2023): 1993. http://dx.doi.org/10.3390/app13031993.
Texto completo da fonteKwak, Young-Sang, Jiun Lee e Jaekwang Kim. "A Transformer-based Arrhythmia Detection Model Robust to ECG Noise". Journal of Korean Institute of Intelligent Systems 32, n.º 3 (30 de junho de 2022): 185–92. http://dx.doi.org/10.5391/jkiis.2022.32.3.185.
Texto completo da fonteKasem, Hossam M., Kwok-Wai Hung e Jianmin Jiang. "Spatial Transformer Generative Adversarial Network for Robust Image Super-Resolution". IEEE Access 7 (2019): 182993–3009. http://dx.doi.org/10.1109/access.2019.2959940.
Texto completo da fonteWang, Fei, Dan Guo, Kun Li e Meng Wang. "EulerMormer: Robust Eulerian Motion Magnification via Dynamic Filtering within Transformer". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 6 (24 de março de 2024): 5345–53. http://dx.doi.org/10.1609/aaai.v38i6.28342.
Texto completo da fonteWang, Yingheng, Shufeng Kong, John M. Gregoire e Carla P. Gomes. "Conformal Crystal Graph Transformer with Robust Encoding of Periodic Invariance". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 1 (24 de março de 2024): 283–91. http://dx.doi.org/10.1609/aaai.v38i1.27781.
Texto completo da fonteChen, Hui, Zhenhai Wang, Hongyu Tian, Lutao Yuan, Xing Wang e Peng Leng. "A Robust Visual Tracking Method Based on Reconstruction Patch Transformer Tracking". Sensors 22, n.º 17 (31 de agosto de 2022): 6558. http://dx.doi.org/10.3390/s22176558.
Texto completo da fonteMoghadam, M. Bameni, e M. Amani. "Design Optimization of Current Transformers Using Robust Design Methodology". Quality & Quantity 39, n.º 5 (outubro de 2005): 671–85. http://dx.doi.org/10.1007/s11135-005-1466-x.
Texto completo da fonteMatsuoka, Ryo, Shunsuke Ono e Masahiro Okuda. "Transformed-Domain Robust Multiple-Exposure Blending With Huber Loss". IEEE Access 7 (2019): 162282–96. http://dx.doi.org/10.1109/access.2019.2951817.
Texto completo da fonteScealy, J. L., Patrice de Caritat, Eric C. Grunsky, Michail T. Tsagris e A. H. Welsh. "Robust Principal Component Analysis for Power Transformed Compositional Data". Journal of the American Statistical Association 110, n.º 509 (2 de janeiro de 2015): 136–48. http://dx.doi.org/10.1080/01621459.2014.990563.
Texto completo da fonteAl-Thani, Mansoor G., Ziyu Sheng, Yuting Cao e Yin Yang. "Traffic Transformer: Transformer-based framework for temporal traffic accident prediction". AIMS Mathematics 9, n.º 5 (2024): 12610–29. http://dx.doi.org/10.3934/math.2024617.
Texto completo da fonteYu, Zhongzhi, Yonggan Fu, Sicheng Li, Chaojian Li e Yingyan Lin. "MIA-Former: Efficient and Robust Vision Transformers via Multi-Grained Input-Adaptation". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 8 (28 de junho de 2022): 8962–70. http://dx.doi.org/10.1609/aaai.v36i8.20879.
Texto completo da fonteCamarena-Martinez, David, Jose R. Huerta-Rosales, Juan P. Amezquita-Sanchez, David Granados-Lieberman, Juan C. Olivares-Galvan e Martin Valtierra-Rodriguez. "Variational Mode Decomposition-Based Processing for Detection of Short-Circuited Turns in Transformers Using Vibration Signals and Machine Learning". Electronics 13, n.º 7 (26 de março de 2024): 1215. http://dx.doi.org/10.3390/electronics13071215.
Texto completo da fonteUENO, Tomohiro, Kazuhisa ITO, Weidong MA e Shigeru IKEO. "DESIGN OF ROBUST POSITION/PRESSURE CONTROLLER FOR CYLINDER USING HYDRAULIC TRANSFORMER". Proceedings of the JFPS International Symposium on Fluid Power 2005, n.º 6 (2005): 414–19. http://dx.doi.org/10.5739/isfp.2005.414.
Texto completo da fonteJiang, Jianmin, Hossam M. Kasem e Kwok-Wai Hung. "A Very Deep Spatial Transformer Towards Robust Single Image Super-Resolution". IEEE Access 7 (2019): 45618–31. http://dx.doi.org/10.1109/access.2019.2908996.
Texto completo da fonteGu, Beom W., Jin S. Choi, Ho S. Son, Myoung K. Je, Hyung I. Yun e Chun T. Rim. "Temperature-Robust Air-Gapless EE-Type Transformer Rails for Sliding Doors". IEEE Transactions on Power Electronics 33, n.º 9 (setembro de 2018): 7841–57. http://dx.doi.org/10.1109/tpel.2017.2772926.
Texto completo da fonteUmar, Buhari Ugbede, James Garba Ambafi, Olayemi Mikail Olaniyi, James Agajo e Omeiza Rabiu Isah. "Low-cost and Efficient Fault Detection and Protection System for Distribution Transformer". Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 12 de fevereiro de 2020, 79–86. http://dx.doi.org/10.22219/kinetik.v5i1.987.
Texto completo da fonteZhang, Hao, Yan Piao e Nan Qi. "STFT: Spatial and temporal feature fusion for transformer tracker". IET Computer Vision, 31 de agosto de 2023. http://dx.doi.org/10.1049/cvi2.12233.
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