Auswahl der wissenschaftlichen Literatur zum Thema „Transformer network“
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Zeitschriftenartikel zum Thema "Transformer network"
S., S., Thulasi Bikku, P. Muthukumar, K. Sandeep, Jampani Chandra Sekhar und V. Krishna Pratap. „Enhanced Intrusion Detection Using Stacked FT-Transformer Architecture“. Journal of Cybersecurity and Information Management 8, Nr. 2 (2024): 19–29. http://dx.doi.org/10.54216/jcim.130202.
Der volle Inhalt der QuelleKrupa, Tadeusz. „Elements of Theory of the Correct Operations of Logistics Transforming Networks“. Foundations of Management 9, Nr. 1 (20.12.2017): 347–60. http://dx.doi.org/10.1515/fman-2017-0026.
Der volle Inhalt der QuelleZhang, Fuping, Pengcheng Zhao und Jianming Wei. „Channel Transformer Network“. IEEE Access 8 (2020): 220762–78. http://dx.doi.org/10.1109/access.2020.3042644.
Der volle Inhalt der QuelleAlharthi, Musleh, und Ausif Mahmood. „Enhanced Linear and Vision Transformer-Based Architectures for Time Series Forecasting“. Big Data and Cognitive Computing 8, Nr. 5 (16.05.2024): 48. http://dx.doi.org/10.3390/bdcc8050048.
Der volle Inhalt der QuelleOttele, Andy, und Rahmat Shoureshi. „Neural Network-Based Adaptive Monitoring System for Power Transformer“. Journal of Dynamic Systems, Measurement, and Control 123, Nr. 3 (11.02.1999): 512–17. http://dx.doi.org/10.1115/1.1387248.
Der volle Inhalt der QuelleMajeed, Issah Babatunde, und Nnamdi I. Nwulu. „Impact of Reverse Power Flow on Distributed Transformers in a Solar-Photovoltaic-Integrated Low-Voltage Network“. Energies 15, Nr. 23 (06.12.2022): 9238. http://dx.doi.org/10.3390/en15239238.
Der volle Inhalt der QuelleAdegboye, B. A. „Power Quality Assessment in a Distribution Network“. Advanced Materials Research 62-64 (Februar 2009): 53–59. http://dx.doi.org/10.4028/www.scientific.net/amr.62-64.53.
Der volle Inhalt der QuelleKumari, Rekha, Gurpreet Kaur, Aditya Rawat, Harshit Chauhan, Kartik Singh Negi und Rishi Mishra. „ANALYSIS OF TRANSFORMER-DEEP NEURAL NETWORK USING DEEP LEARNING“. International Journal of Engineering Applied Sciences and Technology 8, Nr. 2 (01.06.2023): 313–19. http://dx.doi.org/10.33564/ijeast.2023.v08i02.048.
Der volle Inhalt der QuelleSun, 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, Nr. 1 (01.04.2024): 012006. http://dx.doi.org/10.1088/1742-6596/2758/1/012006.
Der volle Inhalt der QuelleAl-Yahya, Maha, Hend Al-Khalifa, Heyam Al-Baity, Duaa AlSaeed und Amr Essam. „Arabic Fake News Detection: Comparative Study of Neural Networks and Transformer-Based Approaches“. Complexity 2021 (16.04.2021): 1–10. http://dx.doi.org/10.1155/2021/5516945.
Der volle Inhalt der QuelleDissertationen zum Thema "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.
Der volle Inhalt der QuelleZhang, 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/.
Der volle Inhalt der QuelleHardie, Stewart Ramon. „A Prototype Transformer Partial Discharge Detection System“. Thesis, University of Canterbury. Electrical and Computer Engineering, 2006. http://hdl.handle.net/10092/1114.
Der volle Inhalt der QuelleSun, Renfei. „Attention Network for Video Based Freezing of Gait Detection“. Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/28908.
Der volle Inhalt der QuelleTuan, 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.
Der volle Inhalt der QuelleZheng, 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.
Der volle Inhalt der QuellePh. 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.
Der volle Inhalt der QuelleDuring 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.
Der volle Inhalt der QuelleMousavi, 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.
Der volle Inhalt der QuelleQC 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.
Der volle Inhalt der QuelleBücher zum Thema "Transformer network"
IEEE Power Engineering Society. Power Systems Relaying Committee., IEEE Standards Board und American National Standards Institute, Hrsg. IEEE guide for the protection of network transformers. New York, N.Y., USA: The Institute of Electrical and Electronics Engineers, 1989.
Den vollen Inhalt der Quelle findenJarvis, Cheryl. The necklace: Thirteen women and the experiment that transformed their lives. New York: Ballantine Books, 2008.
Den vollen Inhalt der Quelle findenLi, Charlene. Groundswell: Winning in a world transformed by social technologies. Boston, Mass: Harvard Business Review Press, 2011.
Den vollen Inhalt der Quelle findenJosh, Bernoff, Hrsg. Groundswell: Winning in a world transformed by social technologies. Boston, Mass: Harvard Business Review Press, 2011.
Den vollen Inhalt der Quelle findenLi, Charlene. Groundswell: Winning in a world transformed by social technologies. Boston, Mass: Harvard Business Press, 2008.
Den vollen Inhalt der Quelle findenI, Watson C., Paek Eung Gi und National Institute of Standards and Technology (U.S.), Hrsg. 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.
Den vollen Inhalt der Quelle findenSpectrum and network measurements. Atlanta, Ga: Noble Pub. Corp., 2001.
Den vollen Inhalt der Quelle findenWitte, Robert A. Spectrum and network measurements. Englewood Cliffs, N.J: Prentice Hall, 1993.
Den vollen Inhalt der Quelle findenJarvis, Cheryl. The necklace: Thirteen women and the experiment that transformed their lives. New York: Ballantine Books, 2008.
Den vollen Inhalt der Quelle findenCheryl, Jarvis, und Women of Jewelia, Hrsg. The necklace: Thirteen women and the experiment that transformed their lives. Waterville, Me: Thorndike Press, 2009.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Transformer network"
Shu, Chang, Xi Chen, Chong Yu und 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.
Der volle Inhalt der QuelleTan, Ruxin, Jiahui Sun, Bo Su und 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.
Der volle Inhalt der QuelleWang, Zehong, Qi Li, Donghua Yu und 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.
Der volle Inhalt der QuelleSarasua, Ignacio, Sebastian Pölsterl und 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.
Der volle Inhalt der QuelleChen, Dong, Gang Hua, Fang Wen und 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.
Der volle Inhalt der QuelleWang, Tuo, Meng Jian, Ge Shi, Xin Fu und 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.
Der volle Inhalt der QuelleAzad, Reza, Moein Heidari, Yuli Wu und 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.
Der volle Inhalt der QuelleLiu, Zhongqiang, Li Zhang, Chunxiao Zhang, Xiangfei Kong und 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.
Der volle Inhalt der QuelleChiam, Dar Hung, und 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.
Der volle Inhalt der QuelleZhang, Yungeng, Yuru Pei und 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.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Transformer network"
Ottele, Andy, Rahmat Shoureshi, Duane Torgerson und 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.
Der volle Inhalt der QuelleNeimark, Daniel, Omri Bar, Maya Zohar und 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.
Der volle Inhalt der QuelleGirdhar, Rohit, Joao Joao Carreira, Carl Doersch und 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.
Der volle Inhalt der QuelleSeong, Hongje, Junhyuk Hyun und 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.
Der volle Inhalt der QuelleMishra, Naman, Avinash Yadav, Arzoo Yadav, Pritam Yadav und 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.
Der volle Inhalt der QuelleLiu, Ruolan, Xiao Chen und 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.
Der volle Inhalt der QuelleGao, Jiarui, Yanwei Fu, Yu-Gang Jiang und 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.
Der volle Inhalt der QuelleShahid, Mohammad, und 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.
Der volle Inhalt der QuelleEscher, Rafael Molossi, Rodrigo Andrade de Bem und 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.
Der volle Inhalt der QuelleNechikkat, Mubashira I., Bhagyasree V. Pattilikattil, Soumya Varma und 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.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Transformer network"
Shi, Jimeng, Vitalii Stebliankin, Zhaonan Wang, Shaowen Wang und Giri Narasimhan. Graph Transformer Network for Flood Forecasting with Heterogeneous Covariates. Purdue University, Oktober 2023. http://dx.doi.org/10.5703/1288284317672.
Der volle Inhalt der QuelleRaghavan, 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), April 2020. http://dx.doi.org/10.2172/1615666.
Der volle Inhalt der QuelleDu, Daqiao. Neural network character recognition with a 2-D Fourier transform preprocessor. Portland State University Library, Januar 2000. http://dx.doi.org/10.15760/etd.6084.
Der volle Inhalt der QuelleGoreczky, 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.
Der volle Inhalt der QuelleFitch, J. The radon transform for data reduction, line detection, and artificial neural network preprocessing. Office of Scientific and Technical Information (OSTI), Mai 1990. http://dx.doi.org/10.2172/6874873.
Der volle Inhalt der QuelleСоловйов, В. М., und В. В. Соловйова. Моделювання мультиплексних мереж. Видавець Ткачук О.В., 2016. http://dx.doi.org/10.31812/0564/1253.
Der volle Inhalt der QuelleEnria, Luisa. Citizen Ethnography in Outbreak Response: Guidance for Establishing Networks of Researchers. SSHAP, Mai 2022. http://dx.doi.org/10.19088/sshap.2022.001.
Der volle Inhalt der QuelleDiDonato, 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, November 2008. http://dx.doi.org/10.21236/ada509798.
Der volle Inhalt der QuelleNechaev, V., Володимир Миколайович Соловйов und A. Nagibas. Complex economic systems structural organization modelling. Politecnico di Torino, 2006. http://dx.doi.org/10.31812/0564/1118.
Der volle Inhalt der QuelleBedoya-Maya, Felipe, Lynn Scholl, Orlando Sabogal-Cardona und Daniel Oviedo. Who uses Transport Network Companies?: Characterization of Demand and its Relationship with Public Transit in Medellín. Inter-American Development Bank, September 2021. http://dx.doi.org/10.18235/0003621.
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