Статті в журналах з теми "Gated Recurrent Units (GRUs)"
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Dangovski, Rumen, Li Jing, Preslav Nakov, Mićo Tatalović, and Marin Soljačić. "Rotational Unit of Memory: A Novel Representation Unit for RNNs with Scalable Applications." Transactions of the Association for Computational Linguistics 7 (November 2019): 121–38. http://dx.doi.org/10.1162/tacl_a_00258.
Khadka, Shauharda, Jen Jen Chung, and Kagan Tumer. "Neuroevolution of a Modular Memory-Augmented Neural Network for Deep Memory Problems." Evolutionary Computation 27, no. 4 (December 2019): 639–64. http://dx.doi.org/10.1162/evco_a_00239.
Akpudo, Ugochukwu Ejike, and Jang-Wook Hur. "A CEEMDAN-Assisted Deep Learning Model for the RUL Estimation of Solenoid Pumps." Electronics 10, no. 17 (August 25, 2021): 2054. http://dx.doi.org/10.3390/electronics10172054.
Shen, Wenjuan, and Xiaoling Li. "Facial expression recognition based on bidirectional gated recurrent units within deep residual network." International Journal of Intelligent Computing and Cybernetics 13, no. 4 (October 12, 2020): 527–43. http://dx.doi.org/10.1108/ijicc-07-2020-0088.
Ding, Chen, Zhouyi Zheng, Sirui Zheng, Xuke Wang, Xiaoyan Xie, Dushi Wen, Lei Zhang, and Yanning Zhang. "Accurate Air-Quality Prediction Using Genetic-Optimized Gated-Recurrent-Unit Architecture." Information 13, no. 5 (April 26, 2022): 223. http://dx.doi.org/10.3390/info13050223.
Ding, Chen, Zhouyi Zheng, Sirui Zheng, Xuke Wang, Xiaoyan Xie, Dushi Wen, Lei Zhang, and Yanning Zhang. "Accurate Air-Quality Prediction Using Genetic-Optimized Gated-Recurrent-Unit Architecture." Information 13, no. 5 (April 26, 2022): 223. http://dx.doi.org/10.3390/info13050223.
ArunKumar, K. E., Dinesh V. Kalaga, Ch Mohan Sai Kumar, Masahiro Kawaji, and Timothy M. Brenza. "Forecasting of COVID-19 using deep layer Recurrent Neural Networks (RNNs) with Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) cells." Chaos, Solitons & Fractals 146 (May 2021): 110861. http://dx.doi.org/10.1016/j.chaos.2021.110861.
Oliveira, Pedro, Bruno Fernandes, Cesar Analide, and Paulo Novais. "Forecasting Energy Consumption of Wastewater Treatment Plants with a Transfer Learning Approach for Sustainable Cities." Electronics 10, no. 10 (May 12, 2021): 1149. http://dx.doi.org/10.3390/electronics10101149.
Fang, Weiguang, Yu Guo, Wenhe Liao, Shaohua Huang, Nengjun Yang, and Jinshan Liu. "A Parallel Gated Recurrent Units (P-GRUs) network for the shifting lateness bottleneck prediction in make-to-order production system." Computers & Industrial Engineering 140 (February 2020): 106246. http://dx.doi.org/10.1016/j.cie.2019.106246.
Fang, Qiang, and Xavier Maldague. "A Method of Defect Depth Estimation for Simulated Infrared Thermography Data with Deep Learning." Applied Sciences 10, no. 19 (September 29, 2020): 6819. http://dx.doi.org/10.3390/app10196819.
Chui, Kwok Tai, Brij B. Gupta, Ryan Wen Liu, Xinyu Zhang, Pandian Vasant, and J. Joshua Thomas. "Extended-Range Prediction Model Using NSGA-III Optimized RNN-GRU-LSTM for Driver Stress and Drowsiness." Sensors 21, no. 19 (September 25, 2021): 6412. http://dx.doi.org/10.3390/s21196412.
Noh, Seol-Hyun. "Analysis of Gradient Vanishing of RNNs and Performance Comparison." Information 12, no. 11 (October 25, 2021): 442. http://dx.doi.org/10.3390/info12110442.
Jiao, Wenxiang, Michael Lyu, and Irwin King. "Real-Time Emotion Recognition via Attention Gated Hierarchical Memory Network." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 8002–9. http://dx.doi.org/10.1609/aaai.v34i05.6309.
Sattari, Mohammad Taghi, Halit Apaydin, and Shahaboddin Shamshirband. "Performance Evaluation of Deep Learning-Based Gated Recurrent Units (GRUs) and Tree-Based Models for Estimating ETo by Using Limited Meteorological Variables." Mathematics 8, no. 6 (June 13, 2020): 972. http://dx.doi.org/10.3390/math8060972.
Aldallal, Ammar. "Toward Efficient Intrusion Detection System Using Hybrid Deep Learning Approach." Symmetry 14, no. 9 (September 13, 2022): 1916. http://dx.doi.org/10.3390/sym14091916.
Gim, Juhui, Wansik Choi, and Changsun Ahn. "Design of Unscented Kalman Filter with Gated Recurrent Units-based Battery Model for SOC Estimation." Transaction of the Korean Society of Automotive Engineers 30, no. 1 (January 1, 2022): 61–68. http://dx.doi.org/10.7467/ksae.2022.30.1.061.
Khan, Muhammad Almas, Muazzam A. Khan, Sana Ullah Jan, Jawad Ahmad, Sajjad Shaukat Jamal, Awais Aziz Shah, Nikolaos Pitropakis, and William J. Buchanan. "A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT." Sensors 21, no. 21 (October 22, 2021): 7016. http://dx.doi.org/10.3390/s21217016.
Aslam, Muhammad, Jae-Myeong Lee, Hyung-Seung Kim, Seung-Jae Lee, and Sugwon Hong. "Deep Learning Models for Long-Term Solar Radiation Forecasting Considering Microgrid Installation: A Comparative Study." Energies 13, no. 1 (December 27, 2019): 147. http://dx.doi.org/10.3390/en13010147.
Gupta, Manish, and Puneet Agrawal. "Compression of Deep Learning Models for Text: A Survey." ACM Transactions on Knowledge Discovery from Data 16, no. 4 (August 31, 2022): 1–55. http://dx.doi.org/10.1145/3487045.
Choi, Edward, Andy Schuetz, Walter F. Stewart, and Jimeng Sun. "Using recurrent neural network models for early detection of heart failure onset." Journal of the American Medical Informatics Association 24, no. 2 (August 13, 2016): 361–70. http://dx.doi.org/10.1093/jamia/ocw112.
Cowton, Jake, Ilias Kyriazakis, Thomas Plötz, and Jaume Bacardit. "A Combined Deep Learning GRU-Autoencoder for the Early Detection of Respiratory Disease in Pigs Using Multiple Environmental Sensors." Sensors 18, no. 8 (August 2, 2018): 2521. http://dx.doi.org/10.3390/s18082521.
Lanera, Corrado, Ileana Baldi, Andrea Francavilla, Elisa Barbieri, Lara Tramontan, Antonio Scamarcia, Luigi Cantarutti, Carlo Giaquinto, and Dario Gregori. "A Deep Learning Approach to Estimate the Incidence of Infectious Disease Cases for Routinely Collected Ambulatory Records: The Example of Varicella-Zoster." International Journal of Environmental Research and Public Health 19, no. 10 (May 13, 2022): 5959. http://dx.doi.org/10.3390/ijerph19105959.
Meng, Zhaorui, and Xianze Xu. "A Hybrid Short-Term Load Forecasting Framework with an Attention-Based Encoder–Decoder Network Based on Seasonal and Trend Adjustment." Energies 12, no. 24 (December 4, 2019): 4612. http://dx.doi.org/10.3390/en12244612.
Wei, Minghua, and Feng Lin. "A novel multi-dimensional features fusion algorithm for the EEG signal recognition of brain's sensorimotor region activated tasks." International Journal of Intelligent Computing and Cybernetics 13, no. 2 (June 8, 2020): 239–60. http://dx.doi.org/10.1108/ijicc-02-2020-0019.
Lv, Yafei, Xiaohan Zhang, Wei Xiong, Yaqi Cui, and Mi Cai. "An End-to-End Local-Global-Fusion Feature Extraction Network for Remote Sensing Image Scene Classification." Remote Sensing 11, no. 24 (December 13, 2019): 3006. http://dx.doi.org/10.3390/rs11243006.
Mohsenimanesh, Ahmad, Evgueniy Entchev, and Filip Bosnjak. "Hybrid Model Based on an SD Selection, CEEMDAN, and Deep Learning for Short-Term Load Forecasting of an Electric Vehicle Fleet." Applied Sciences 12, no. 18 (September 16, 2022): 9288. http://dx.doi.org/10.3390/app12189288.
Harrou, Fouzi, Abdelkader Dairi, Abdelhafid Zeroual, and Ying Sun. "Forecasting of Bicycle and Pedestrian Traffic Using Flexible and Efficient Hybrid Deep Learning Approach." Applied Sciences 12, no. 9 (April 28, 2022): 4482. http://dx.doi.org/10.3390/app12094482.
Ahanger, Tariq Ahamed, Abdulaziz Aldaej, Mohammed Atiquzzaman, Imdad Ullah, and Muhammad Yousufudin. "Federated Learning-Inspired Technique for Attack Classification in IoT Networks." Mathematics 10, no. 12 (June 20, 2022): 2141. http://dx.doi.org/10.3390/math10122141.
Reich, Thilo, David Hulbert, and Marcin Budka. "A Model Architecture for Public Transport Networks Using a Combination of a Recurrent Neural Network Encoder Library and a Attention Mechanism." Algorithms 15, no. 9 (September 14, 2022): 328. http://dx.doi.org/10.3390/a15090328.
Reza, Selim, Marta Campos Ferreira, José J. M. Machado, and João Manuel R. S. Tavares. "Traffic State Prediction Using One-Dimensional Convolution Neural Networks and Long Short-Term Memory." Applied Sciences 12, no. 10 (May 19, 2022): 5149. http://dx.doi.org/10.3390/app12105149.
Chen, Zengshun, Chenfeng Yuan, Haofan Wu, Likai Zhang, Ke Li, Xuanyi Xue, and Lei Wu. "An Improved Method Based on EEMD-LSTM to Predict Missing Measured Data of Structural Sensors." Applied Sciences 12, no. 18 (September 8, 2022): 9027. http://dx.doi.org/10.3390/app12189027.
Chen, Yuren, Yu Chen, and Bo Yu. "Speed Distribution Prediction of Freight Vehicles on Mountainous Freeway Using Deep Learning Methods." Journal of Advanced Transportation 2020 (January 10, 2020): 1–14. http://dx.doi.org/10.1155/2020/8953182.
Ravanelli, Mirco, Philemon Brakel, Maurizio Omologo, and Yoshua Bengio. "Light Gated Recurrent Units for Speech Recognition." IEEE Transactions on Emerging Topics in Computational Intelligence 2, no. 2 (April 2018): 92–102. http://dx.doi.org/10.1109/tetci.2017.2762739.
Zhang, Yaquan, Qi Wu, Nanbo Peng, Min Dai, Jing Zhang, and Hu Wang. "Memory-Gated Recurrent Networks." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 12 (May 18, 2021): 10956–63. http://dx.doi.org/10.1609/aaai.v35i12.17308.
Mateus, Balduíno César, Mateus Mendes, José Torres Farinha, Rui Assis, and António Marques Cardoso. "Comparing LSTM and GRU Models to Predict the Condition of a Pulp Paper Press." Energies 14, no. 21 (October 22, 2021): 6958. http://dx.doi.org/10.3390/en14216958.
Li, Xuelong, Aihong Yuan, and Xiaoqiang Lu. "Multi-modal gated recurrent units for image description." Multimedia Tools and Applications 77, no. 22 (March 15, 2018): 29847–69. http://dx.doi.org/10.1007/s11042-018-5856-1.
Jing, Li, Caglar Gulcehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, and Yoshua Bengio. "Gated Orthogonal Recurrent Units: On Learning to Forget." Neural Computation 31, no. 4 (April 2019): 765–83. http://dx.doi.org/10.1162/neco_a_01174.
PARDEDE, JASMAN, and MUHAMMAD FAUZAN RASPATI. "Gated Recurrent Units dalam Mendeteksi Obstructive Sleep Apnea." MIND Journal 6, no. 2 (December 12, 2021): 221–35. http://dx.doi.org/10.26760/mindjournal.v6i2.221-235.
Tan, Yi-Fei, Xiaoning Guo, and Soon-Chang Poh. "Time series activity classification using gated recurrent units." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 4 (August 1, 2021): 3551. http://dx.doi.org/10.11591/ijece.v11i4.pp3551-3558.
Onyekpe, Uche, Vasile Palade, Stratis Kanarachos, and Stavros-Richard G. Christopoulos. "A Quaternion Gated Recurrent Unit Neural Network for Sensor Fusion." Information 12, no. 3 (March 9, 2021): 117. http://dx.doi.org/10.3390/info12030117.
Hosseini, Majid, Satya Katragadda, Jessica Wojtkiewicz, Raju Gottumukkala, Anthony Maida, and Terrence Lynn Chambers. "Direct Normal Irradiance Forecasting Using Multivariate Gated Recurrent Units." Energies 13, no. 15 (July 31, 2020): 3914. http://dx.doi.org/10.3390/en13153914.
Zeeshan Ansari, Mohd, Tanvir Ahmad, Mirza Mohd Sufyan Beg, and Faiyaz Ahmad. "Hindi to English transliteration using multilayer gated recurrent units." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 2 (August 1, 2022): 1083. http://dx.doi.org/10.11591/ijeecs.v27.i2.pp1083-1090.
Wojtkiewicz, Jessica, Matin Hosseini, Raju Gottumukkala, and Terrence Lynn Chambers. "Hour-Ahead Solar Irradiance Forecasting Using Multivariate Gated Recurrent Units." Energies 12, no. 21 (October 24, 2019): 4055. http://dx.doi.org/10.3390/en12214055.
Bonassi, Fabio, Marcello Farina, and Riccardo Scattolini. "On the stability properties of Gated Recurrent Units neural networks." Systems & Control Letters 157 (November 2021): 105049. http://dx.doi.org/10.1016/j.sysconle.2021.105049.
Lobacheva, Ekaterina, Nadezhda Chirkova, Alexander Markovich, and Dmitry Vetrov. "Structured Sparsification of Gated Recurrent Neural Networks." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 4989–96. http://dx.doi.org/10.1609/aaai.v34i04.5938.
Jangir, Mahendra Kumar, and Karan Singh. "HARGRURNN: Human activity recognition using inertial body sensor gated recurrent units recurrent neural network." Journal of Discrete Mathematical Sciences and Cryptography 22, no. 8 (November 17, 2019): 1577–87. http://dx.doi.org/10.1080/09720529.2019.1696552.
Liu, Juntao, Caihua Wu, and Junwei Wang. "Gated recurrent units based neural network for time heterogeneous feedback recommendation." Information Sciences 423 (January 2018): 50–65. http://dx.doi.org/10.1016/j.ins.2017.09.048.
do Carmo Nogueira, Tiago, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, and Matheus Rudolfo Diedrich Ullmann. "Reference-based model using multimodal gated recurrent units for image captioning." Multimedia Tools and Applications 79, no. 41-42 (August 15, 2020): 30615–35. http://dx.doi.org/10.1007/s11042-020-09539-5.
Rehmer, Alexander, and Andreas Kroll. "On the vanishing and exploding gradient problem in Gated Recurrent Units." IFAC-PapersOnLine 53, no. 2 (2020): 1243–48. http://dx.doi.org/10.1016/j.ifacol.2020.12.1342.
Soliman, Hatem, Izhar Ahmed Khan, and Yasir Hussain. "Learning to transfer knowledge from RDF Graphs with gated recurrent units." Intelligent Data Analysis 26, no. 3 (April 18, 2022): 679–94. http://dx.doi.org/10.3233/ida-215919.