Literatura científica selecionada sobre o tema "Transformer network"
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Artigos de revistas sobre o assunto "Transformer network"
S., S., Thulasi Bikku, P. Muthukumar, K. Sandeep, Jampani Chandra Sekhar e V. Krishna Pratap. "Enhanced Intrusion Detection Using Stacked FT-Transformer Architecture". Journal of Cybersecurity and Information Management 8, n.º 2 (2024): 19–29. http://dx.doi.org/10.54216/jcim.130202.
Texto completo da fonteKrupa, Tadeusz. "Elements of Theory of the Correct Operations of Logistics Transforming Networks". Foundations of Management 9, n.º 1 (20 de dezembro de 2017): 347–60. http://dx.doi.org/10.1515/fman-2017-0026.
Texto completo da fonteZhang, Fuping, Pengcheng Zhao e Jianming Wei. "Channel Transformer Network". IEEE Access 8 (2020): 220762–78. http://dx.doi.org/10.1109/access.2020.3042644.
Texto completo da fonteAlharthi, Musleh, e Ausif Mahmood. "Enhanced Linear and Vision Transformer-Based Architectures for Time Series Forecasting". Big Data and Cognitive Computing 8, n.º 5 (16 de maio de 2024): 48. http://dx.doi.org/10.3390/bdcc8050048.
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 fonteMajeed, Issah Babatunde, e Nnamdi I. Nwulu. "Impact of Reverse Power Flow on Distributed Transformers in a Solar-Photovoltaic-Integrated Low-Voltage Network". Energies 15, n.º 23 (6 de dezembro de 2022): 9238. http://dx.doi.org/10.3390/en15239238.
Texto completo da fonteAdegboye, B. A. "Power Quality Assessment in a Distribution Network". Advanced Materials Research 62-64 (fevereiro de 2009): 53–59. http://dx.doi.org/10.4028/www.scientific.net/amr.62-64.53.
Texto completo da fonteKumari, Rekha, Gurpreet Kaur, Aditya Rawat, Harshit Chauhan, Kartik Singh Negi e Rishi Mishra. "ANALYSIS OF TRANSFORMER-DEEP NEURAL NETWORK USING DEEP LEARNING". International Journal of Engineering Applied Sciences and Technology 8, n.º 2 (1 de junho de 2023): 313–19. http://dx.doi.org/10.33564/ijeast.2023.v08i02.048.
Texto completo da fonteSun, Zhiqing, Yi Xuan, ZikaiCao, Jian Liu, Tiechao Dai, Weihao Liu, Gangjin Ye et al. "Transformer parameter estimation in distribution network based on deformable transformer". Journal of Physics: Conference Series 2758, n.º 1 (1 de abril de 2024): 012006. http://dx.doi.org/10.1088/1742-6596/2758/1/012006.
Texto completo da fonteAl-Yahya, Maha, Hend Al-Khalifa, Heyam Al-Baity, Duaa AlSaeed e Amr Essam. "Arabic Fake News Detection: Comparative Study of Neural Networks and Transformer-Based Approaches". Complexity 2021 (16 de abril de 2021): 1–10. http://dx.doi.org/10.1155/2021/5516945.
Texto completo da fonteTeses / dissertações sobre o assunto "Transformer network"
Mao, Peilin. "Power transformer fault diagnosis based on wavelet transform and artificial neural network". Thesis, University of Bath, 2000. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.760740.
Texto completo da fonteZhang, Yuwen. "An artificial neural network approach to transformer fault diagnosis". Thesis, This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-08222008-063051/.
Texto completo da fonteHardie, Stewart Ramon. "A Prototype Transformer Partial Discharge Detection System". Thesis, University of Canterbury. Electrical and Computer Engineering, 2006. http://hdl.handle.net/10092/1114.
Texto completo da fonteSun, Renfei. "Attention Network for Video Based Freezing of Gait Detection". Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/28908.
Texto completo da fonteTuan, Abdullah Tuan Ab Rashid Bin. "Optimal management of failures, spare parts and transformer reconnections in an electrical distribution network". Thesis, University of Strathclyde, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.501838.
Texto completo da fonteZheng, Cong. "Loosely Coupled Transformer and Tuning Network Design for High-Efficiency Inductive Power Transfer Systems". Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/52893.
Texto completo da fontePh. D.
Конденко, Віктор Анатолійович. "Електропостачання станційного виробничо-побутового приміщення залізничої станції". Bachelor's thesis, КПІ ім. Ігоря Сікорського, 2021. https://ela.kpi.ua/handle/123456789/43036.
Texto completo da fonteDuring the implementation of the diploma project, the load calculations of the railway station shop were calculated. Supply networks up to 1 kV and above 1 kV, power transformers, protection devices and automation are selected. The calculation of short-circuit currents is carried out. As a special issue, the problems of quality and reliability of power supply of the shop were analyzed, the most accessible possible technical solution was selected and electrical installations with the necessary characteristics were selected.
Singh, Arvind. "A multi-layer neural network approach to identification of mechanical damage in power transformer windings". Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/5677.
Texto completo da fonteMousavi, Seyed Ali. "Electromagnetic Modelling of Power Transformers with DC Magnetization". Licentiate thesis, KTH, Elektroteknisk teori och konstruktion, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-105395.
Texto completo da fonteQC 20121121
Dronzeková, Michaela. "Analýza polygonálních modelů pomocí neuronových sítí". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417253.
Texto completo da fonteLivros sobre o assunto "Transformer network"
IEEE Power Engineering Society. Power Systems Relaying Committee., IEEE Standards Board e American National Standards Institute, eds. IEEE guide for the protection of network transformers. New York, N.Y., USA: The Institute of Electrical and Electronics Engineers, 1989.
Encontre o texto completo da fonteJarvis, Cheryl. The necklace: Thirteen women and the experiment that transformed their lives. New York: Ballantine Books, 2008.
Encontre o texto completo da fonteLi, Charlene. Groundswell: Winning in a world transformed by social technologies. Boston, Mass: Harvard Business Review Press, 2011.
Encontre o texto completo da fonteJosh, Bernoff, ed. Groundswell: Winning in a world transformed by social technologies. Boston, Mass: Harvard Business Review Press, 2011.
Encontre o texto completo da fonteLi, Charlene. Groundswell: Winning in a world transformed by social technologies. Boston, Mass: Harvard Business Press, 2008.
Encontre o texto completo da fonteI, Watson C., Paek Eung Gi e National Institute of Standards and Technology (U.S.), eds. Effect of resolution and image quality on combined optical and neural network fingerprint matching. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1998.
Encontre o texto completo da fonteSpectrum and network measurements. Atlanta, Ga: Noble Pub. Corp., 2001.
Encontre o texto completo da fonteWitte, Robert A. Spectrum and network measurements. Englewood Cliffs, N.J: Prentice Hall, 1993.
Encontre o texto completo da fonteJarvis, Cheryl. The necklace: Thirteen women and the experiment that transformed their lives. New York: Ballantine Books, 2008.
Encontre o texto completo da fonteCheryl, Jarvis, e Women of Jewelia, eds. The necklace: Thirteen women and the experiment that transformed their lives. Waterville, Me: Thorndike Press, 2009.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Transformer network"
Shu, Chang, Xi Chen, Chong Yu e Hua Han. "A Refined Spatial Transformer Network". In Neural Information Processing, 151–61. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04182-3_14.
Texto completo da fonteTan, Ruxin, Jiahui Sun, Bo Su e Gongshen Liu. "Transformer-DW: A Transformer Network with Dynamic and Weighted Head". In Neural Information Processing, 504–15. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36711-4_42.
Texto completo da fonteWang, Zehong, Qi Li, Donghua Yu e Xiaolong Han. "Temporal Graph Transformer for Dynamic Network". In Lecture Notes in Computer Science, 694–705. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-15931-2_57.
Texto completo da fonteSarasua, Ignacio, Sebastian Pölsterl e Christian Wachinger. "TransforMesh: A Transformer Network for Longitudinal Modeling of Anatomical Meshes". In Machine Learning in Medical Imaging, 209–18. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87589-3_22.
Texto completo da fonteChen, Dong, Gang Hua, Fang Wen e Jian Sun. "Supervised Transformer Network for Efficient Face Detection". In Computer Vision – ECCV 2016, 122–38. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46454-1_8.
Texto completo da fonteWang, Tuo, Meng Jian, Ge Shi, Xin Fu e Lifang Wu. "Multi-intent Compatible Transformer Network for Recommendation". In Pattern Recognition and Computer Vision, 344–55. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18907-4_27.
Texto completo da fonteAzad, Reza, Moein Heidari, Yuli Wu e Dorit Merhof. "Contextual Attention Network: Transformer Meets U-Net". In Machine Learning in Medical Imaging, 377–86. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-21014-3_39.
Texto completo da fonteLiu, Zhongqiang, Li Zhang, Chunxiao Zhang, Xiangfei Kong e Anan Shen. "Transformer Fault Diagnosis Based on Elman Network". In Advances in Intelligent Systems and Computing, 479–86. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25128-4_60.
Texto completo da fonteChiam, Dar Hung, e King Hann Lim. "Power Quality Disturbance Classification Using Transformer Network". In Communications in Computer and Information Science, 272–82. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15784-4_21.
Texto completo da fonteZhang, Yungeng, Yuru Pei e Hongbin Zha. "Learning Dual Transformer Network for Diffeomorphic Registration". In Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, 129–38. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87202-1_13.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Transformer network"
Ottele, Andy, Rahmat Shoureshi, Duane Torgerson e John Work. "Neural Network-Based Adaptive Monitoring System for Power Transformer". In ASME 1999 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/imece1999-0069.
Texto completo da fonteNeimark, Daniel, Omri Bar, Maya Zohar e Dotan Asselmann. "Video Transformer Network". In 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). IEEE, 2021. http://dx.doi.org/10.1109/iccvw54120.2021.00355.
Texto completo da fonteGirdhar, Rohit, Joao Joao Carreira, Carl Doersch e Andrew Zisserman. "Video Action Transformer Network". In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2019. http://dx.doi.org/10.1109/cvpr.2019.00033.
Texto completo da fonteSeong, Hongje, Junhyuk Hyun e Euntai Kim. "Video Multitask Transformer Network". In 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW). IEEE, 2019. http://dx.doi.org/10.1109/iccvw.2019.00194.
Texto completo da fonteMishra, Naman, Avinash Yadav, Arzoo Yadav, Pritam Yadav e Pinki Yadav. "Transformer: Health Monitoring System Based on IoT". In International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-d7mojr.
Texto completo da fonteLiu, Ruolan, Xiao Chen e Xue Wen. "Voice Conversion with Transformer Network". In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9054523.
Texto completo da fonteGao, Jiarui, Yanwei Fu, Yu-Gang Jiang e Xiangyang Xue. "Frame-Transformer Emotion Classification Network". In ICMR '17: International Conference on Multimedia Retrieval. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3078971.3079030.
Texto completo da fonteShahid, Mohammad, e Kai-lung Hua. "Fire Detection using Transformer Network". In ICMR '21: International Conference on Multimedia Retrieval. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3460426.3463665.
Texto completo da fonteEscher, Rafael Molossi, Rodrigo Andrade de Bem e Paulo Lilles Jorge Drews. "Fast Spatial-Temporal Transformer Network". In 2021 34th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI). IEEE, 2021. http://dx.doi.org/10.1109/sibgrapi54419.2021.00018.
Texto completo da fonteNechikkat, Mubashira I., Bhagyasree V. Pattilikattil, Soumya Varma e Ajay James. "Video captioning using transformer network". In THE 2ND UNIVERSITAS LAMPUNG INTERNATIONAL CONFERENCE ON SCIENCE, TECHNOLOGY, AND ENVIRONMENT (ULICoSTE) 2021. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0107029.
Texto completo da fonteRelatórios de organizações sobre o assunto "Transformer network"
Shi, Jimeng, Vitalii Stebliankin, Zhaonan Wang, Shaowen Wang e Giri Narasimhan. Graph Transformer Network for Flood Forecasting with Heterogeneous Covariates. Purdue University, outubro de 2023. http://dx.doi.org/10.5703/1288284317672.
Texto completo da fonteRaghavan, Ajay. TRANSENSOR: Transformer Real-time Assessment INtelligent System with Embedded Network of Sensors and Optical Readout. Final Report. Office of Scientific and Technical Information (OSTI), abril de 2020. http://dx.doi.org/10.2172/1615666.
Texto completo da fonteDu, Daqiao. Neural network character recognition with a 2-D Fourier transform preprocessor. Portland State University Library, janeiro de 2000. http://dx.doi.org/10.15760/etd.6084.
Texto completo da fonteGoreczky, Péter. 5G Network Rollout: a Contest of Countries or Companies? Külügyi és Külgazdasági Intézet, 2021. http://dx.doi.org/10.47683/kkielemzesek.e-2021.14.
Texto completo da fonteFitch, J. The radon transform for data reduction, line detection, and artificial neural network preprocessing. Office of Scientific and Technical Information (OSTI), maio de 1990. http://dx.doi.org/10.2172/6874873.
Texto completo da fonteСоловйов, В. М., e В. В. Соловйова. Моделювання мультиплексних мереж. Видавець Ткачук О.В., 2016. http://dx.doi.org/10.31812/0564/1253.
Texto completo da fonteEnria, Luisa. Citizen Ethnography in Outbreak Response: Guidance for Establishing Networks of Researchers. SSHAP, maio de 2022. http://dx.doi.org/10.19088/sshap.2022.001.
Texto completo da fonteDiDonato, Armido. Target Location and ID From a Passive Multistatic Sensor Network Using Time Differences of Arrival (TDOAs) and the Hough Transform. Fort Belvoir, VA: Defense Technical Information Center, novembro de 2008. http://dx.doi.org/10.21236/ada509798.
Texto completo da fonteNechaev, V., Володимир Миколайович Соловйов e A. Nagibas. Complex economic systems structural organization modelling. Politecnico di Torino, 2006. http://dx.doi.org/10.31812/0564/1118.
Texto completo da fonteBedoya-Maya, Felipe, Lynn Scholl, Orlando Sabogal-Cardona e Daniel Oviedo. Who uses Transport Network Companies?: Characterization of Demand and its Relationship with Public Transit in Medellín. Inter-American Development Bank, setembro de 2021. http://dx.doi.org/10.18235/0003621.
Texto completo da fonte