Artículos de revistas sobre el tema "DEEP LEARNING MODEL"
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Wang, Yating, Siu Wun Cheung, Eric T. Chung, Yalchin Efendiev y Min Wang. "Deep multiscale model learning". Journal of Computational Physics 406 (abril de 2020): 109071. http://dx.doi.org/10.1016/j.jcp.2019.109071.
Texto completoXu, Zongben y Jian Sun. "Model-driven deep-learning". National Science Review 5, n.º 1 (25 de agosto de 2017): 22–24. http://dx.doi.org/10.1093/nsr/nwx099.
Texto completoShlezinger, Nir y Yonina C. Eldar. "Model-Based Deep Learning". Foundations and Trends® in Signal Processing 17, n.º 4 (2023): 291–416. http://dx.doi.org/10.1561/2000000113.
Texto completoBakhtiari, Shahab. "Can Deep Learning Model Perceptual Learning?" Journal of Neuroscience 39, n.º 2 (9 de enero de 2019): 194–96. http://dx.doi.org/10.1523/jneurosci.2209-18.2018.
Texto completoWu, Chong. "A Credit Risk Predicting Hybrid Model Based on Deep Learning Technology". International Journal of Machine Learning and Computing 11, n.º 3 (mayo de 2021): 182–87. http://dx.doi.org/10.18178/ijmlc.2021.11.3.1033.
Texto completoSrinivas, Dr Kalyanapu y Reddy Dr.B.R.S. "Deep Learning based CNN Optimization Model for MR Braing Image Segmentation". Journal of Advanced Research in Dynamical and Control Systems 11, n.º 11 (20 de noviembre de 2019): 213–20. http://dx.doi.org/10.5373/jardcs/v11i11/20193190.
Texto completoEvseenko, Alla y Dmitrii Romannikov. "Application of Deep Q-learning and double Deep Q-learning algorithms to the task of control an inverted pendulum". Transaction of Scientific Papers of the Novosibirsk State Technical University, n.º 1-2 (26 de agosto de 2020): 7–25. http://dx.doi.org/10.17212/2307-6879-2020-1-2-7-25.
Texto completo白家納, 白家納 y 黃崇能 Pachara Opattrakarnkul. "以深度學習模式估測控制之駕駛輔助系統的研發". 理工研究國際期刊 12, n.º 1 (abril de 2022): 015–24. http://dx.doi.org/10.53106/222344892022041201002.
Texto completoHao, Xing, Guigang Zhang y Shang Ma. "Deep Learning". International Journal of Semantic Computing 10, n.º 03 (septiembre de 2016): 417–39. http://dx.doi.org/10.1142/s1793351x16500045.
Texto completoDjellali, Choukri y Mehdi adda. "An Enhanced Deep Learning Model to Network Attack Detection, by using Parameter Tuning, Hidden Markov Model and Neural Network". Journal of Ubiquitous Systems and Pervasive Networks 15, n.º 01 (1 de marzo de 2021): 35–41. http://dx.doi.org/10.5383/juspn.15.01.005.
Texto completoBunrit, Supaporn, Thuttaphol Inkian, Nittaya Kerdprasop y Kittisak Kerdprasop. "Text-Independent Speaker Identification Using Deep Learning Model of Convolution Neural Network". International Journal of Machine Learning and Computing 9, n.º 2 (abril de 2019): 143–48. http://dx.doi.org/10.18178/ijmlc.2019.9.2.778.
Texto completoSiddanna, S. R. y Y. C. Kiran. "Two Stage Multi Modal Deep Learning Kannada Character Recognition Model Adaptive to Discriminative Patterns of Kannada Characters". Indian Journal Of Science And Technology 16, n.º 3 (22 de enero de 2023): 155–66. http://dx.doi.org/10.17485/ijst/v16i3.1904.
Texto completoZhihua Chen, Zhihua Chen, Xiaolin Ju Zhihua Chen, Haochen Wang Xiaolin Ju y Xiang Chen Haochen Wang. "Hybrid Multiple Deep Learning Models to Boost Blocking Bug Prediction". 網際網路技術學刊 23, n.º 5 (septiembre de 2022): 1099–107. http://dx.doi.org/10.53106/160792642022092305018.
Texto completoTamboli, Mohasin B. y Dr Nageswara Rao Moparthi. "Deep Learning Model for Intrusion Identification". Journal of Advanced Research in Dynamical and Control Systems 12, n.º 5 (30 de mayo de 2020): 388–95. http://dx.doi.org/10.5373/jardcs/v12i5/20201726.
Texto completoSantos Silva, Jose Vitor, Leonardo Matos Matos, Flavio Santos, Helisson Oliveira Magalhaes Cerqueira, Hendrik Macedo, Bruno Otavio Piedade Prado, Gilton Jose Ferreira da Silva y Kalil Araujo Bispo. "Combining deep learning model compression techniques". IEEE Latin America Transactions 20, n.º 3 (marzo de 2022): 458–64. http://dx.doi.org/10.1109/tla.2022.9667144.
Texto completoYang, Fan y Yutai Rao. "Practice and Research of Blended Learning Model Guided by Deep Learning Model". Mathematical Problems in Engineering 2022 (26 de mayo de 2022): 1–6. http://dx.doi.org/10.1155/2022/8915162.
Texto completoYuan, Zhen y Jinfeng Liu. "A Hybrid Deep Learning Model for Trash Classification Based on Deep Trasnsfer Learning". Journal of Electrical and Computer Engineering 2022 (23 de junio de 2022): 1–9. http://dx.doi.org/10.1155/2022/7608794.
Texto completoLv, Qing, Suzhen Zhang y Yuechun Wang. "Deep Learning Model of Image Classification Using Machine Learning". Advances in Multimedia 2022 (19 de julio de 2022): 1–12. http://dx.doi.org/10.1155/2022/3351256.
Texto completoFang, Qiqing, Gen Liu, Yamin Hu, Yahui Hu y Jingjing Wang. "A blended collaborative learning model aiming to deep learning". SHS Web of Conferences 140 (2022): 01017. http://dx.doi.org/10.1051/shsconf/202214001017.
Texto completoSilpa, C., A. Vani y K. Rama Naidu. "Deep Learning Based Channel Estimation for MIMO-OFDM System with Modified ResNet Model". Indian Journal Of Science And Technology 16, n.º 2 (15 de enero de 2023): 97–108. http://dx.doi.org/10.17485/ijst/v16i2.2154.
Texto completoFang, Lidong, Pei Ge, Lei Zhang, Weinan E. null y Huan Lei. "DeePN$^2$: A Deep Learning-Based Non-Newtonian Hydrodynamic Model". Journal of Machine Learning 1, n.º 1 (junio de 2022): 114–40. http://dx.doi.org/10.4208/jml.220115.
Texto completoDoke, Yash. "Deep fake Detection Through Deep Learning". International Journal for Research in Applied Science and Engineering Technology 11, n.º 5 (31 de mayo de 2023): 861–66. http://dx.doi.org/10.22214/ijraset.2023.51630.
Texto completoChoiriyati, Nur, Yandra Arkeman y Wisnu Ananta Kusuma. "Deep learning model for metagenome fragment classification using spaced k-mers feature extraction". Jurnal Teknologi dan Sistem Komputer 8, n.º 3 (25 de mayo de 2020): 234–38. http://dx.doi.org/10.14710/jtsiskom.2020.13407.
Texto completoST, Suganthi, Mohamed Uvaze Ahamed Ayoobkhan, Krishna Kumar V, Nebojsa Bacanin, Venkatachalam K, Hubálovský Štěpán y Trojovský Pavel. "Deep learning model for deep fake face recognition and detection". PeerJ Computer Science 8 (22 de febrero de 2022): e881. http://dx.doi.org/10.7717/peerj-cs.881.
Texto completoYang, Dong y Jian Sun. "A Model-Driven Deep Dehazing Approach by Learning Deep Priors". IEEE Access 9 (2021): 108542–56. http://dx.doi.org/10.1109/access.2021.3101319.
Texto completoNoori, Amani Y., Dr Shaimaa H. Shaker y Dr Raghad Abdulaali Azeez. "Semantic Segmentation of Urban Street Scenes Using Deep Learning". Webology 19, n.º 1 (20 de enero de 2022): 2294–306. http://dx.doi.org/10.14704/web/v19i1/web19156.
Texto completoLee, S., J. Banzon, K. Le y D. Kim. "Estimating animal pose using deep learning: a trained deep learning model outperforms morphological analysis". EAI Endorsed Transactions on Bioengineering and Bioinformatics 1, n.º 4 (22 de abril de 2022): 173951. http://dx.doi.org/10.4108/eai.22-4-2022.173951.
Texto completoGhoniem, Rania M., Abeer D. Algarni, Basel Refky y Ahmed A. Ewees. "Multi-Modal Evolutionary Deep Learning Model for Ovarian Cancer Diagnosis". Symmetry 13, n.º 4 (10 de abril de 2021): 643. http://dx.doi.org/10.3390/sym13040643.
Texto completoP, Sanjeevi. "Social Distancing Detection with Deep Learning Model". International Journal for Research in Applied Science and Engineering Technology 9, n.º 4 (30 de abril de 2021): 1683–85. http://dx.doi.org/10.22214/ijraset.2021.33996.
Texto completoPyo, Jongcheol, Sanghun Park, Kyung-Hwa Cho y Sang-Soo Baek. "Deep learning model in water-environment field". Journal of the Korean Society of Water and Wastewater 34, n.º 6 (30 de diciembre de 2020): 481–93. http://dx.doi.org/10.11001/jksww.2020.34.6.481.
Texto completoZhou, Xingchen, Ming Xu, Yiming Wu y Ning Zheng. "Deep Model Poisoning Attack on Federated Learning". Future Internet 13, n.º 3 (14 de marzo de 2021): 73. http://dx.doi.org/10.3390/fi13030073.
Texto completoLee, A.-Hyun, Hyeongho Bae, Young-Ky Kim y Chong-kwon Kim. "Deep Reinforcement Learning based MCS Decision Model". Journal of KIISE 49, n.º 8 (31 de agosto de 2022): 663–68. http://dx.doi.org/10.5626/jok.2022.49.8.663.
Texto completoMohammed, Amal Ahmed Hasan y Jiazhou Chen. "Cleanup Sketched Drawings: Deep Learning-Based Model". Applied Bionics and Biomechanics 2022 (6 de mayo de 2022): 1–17. http://dx.doi.org/10.1155/2022/2238077.
Texto completoAnnam, Sangeetha y Anshu Singla. "Hyperspectral Image Classification Using Deep Learning Model". ECS Transactions 107, n.º 1 (24 de abril de 2022): 6427–33. http://dx.doi.org/10.1149/10701.6427ecst.
Texto completoZhao, Ming, Meng Li, Sheng-Lung Peng y Jie Li. "A Novel Deep Learning Model Compression Algorithm". Electronics 11, n.º 7 (28 de marzo de 2022): 1066. http://dx.doi.org/10.3390/electronics11071066.
Texto completoSophiya, E. y S. Jothilakshmi. "Audio event detection using deep learning model". International Journal of Computer Aided Engineering and Technology 16, n.º 3 (2022): 328. http://dx.doi.org/10.1504/ijcaet.2022.10046064.
Texto completoJing, Jing. "Deep Learning-Based Music Quality Analysis Model". Applied Bionics and Biomechanics 2022 (13 de junio de 2022): 1–6. http://dx.doi.org/10.1155/2022/6213115.
Texto completoSophiya, E. y S. Jothilakshmi. "Audio event detection using deep learning model". International Journal of Computer Aided Engineering and Technology 16, n.º 3 (2022): 328. http://dx.doi.org/10.1504/ijcaet.2022.122149.
Texto completoAbdin, Osama y Philip M. Kim. "Rapid protein model refinement by deep learning". Nature Computational Science 1, n.º 7 (julio de 2021): 456–57. http://dx.doi.org/10.1038/s43588-021-00104-0.
Texto completoGanapriya, K., N. Uma Maheswari y R. Venkatesh. "Deep Learning Model for Epileptic Seizure Prediction". Journal of Medical Imaging and Health Informatics 11, n.º 12 (1 de diciembre de 2021): 3199–208. http://dx.doi.org/10.1166/jmihi.2021.3916.
Texto completoE, Yugesh. "Deep Learning Model for Motion Video Processing". International Journal for Research in Applied Science and Engineering Technology 7, n.º 3 (31 de marzo de 2019): 2158–61. http://dx.doi.org/10.22214/ijraset.2019.3398.
Texto completoShadeed, Ghada A., Mohammed A. Tawfeeq y Sawsan M. Mahmoud. "Deep learning model for thorax diseases detection". TELKOMNIKA (Telecommunication Computing Electronics and Control) 18, n.º 1 (1 de febrero de 2020): 441. http://dx.doi.org/10.12928/telkomnika.v18i1.12997.
Texto completoBakhteev, O. Yu y V. V. Strijov. "Deep Learning Model Selection of Suboptimal Complexity". Automation and Remote Control 79, n.º 8 (agosto de 2018): 1474–88. http://dx.doi.org/10.1134/s000511791808009x.
Texto completoNigri, Andrea, Susanna Levantesi, Mario Marino, Salvatore Scognamiglio y Francesca Perla. "A Deep Learning Integrated Lee–Carter Model". Risks 7, n.º 1 (16 de marzo de 2019): 33. http://dx.doi.org/10.3390/risks7010033.
Texto completoWu, Guoxing, Wenjie Lu, Guangwei Gao, Chunxia Zhao y Jiayin Liu. "Regional deep learning model for visual tracking". Neurocomputing 175 (enero de 2016): 310–23. http://dx.doi.org/10.1016/j.neucom.2015.10.064.
Texto completoLee, Miran, Jong Wook Kim y Beakcheol Jang. "Chicken pox Prediction Using Deep Learning Model". Transactions of The Korean Institute of Electrical Engineers 69, n.º 1 (31 de enero de 2020): 127–37. http://dx.doi.org/10.5370/kiee.2020.69.1.127.
Texto completoAraya-Polo, Mauricio, Stuart Farris y Manuel Florez. "Deep learning-driven velocity model building workflow". Leading Edge 38, n.º 11 (noviembre de 2019): 872a1–872a9. http://dx.doi.org/10.1190/tle38110872a1.1.
Texto completoBakhteev, Oleg y Vadim Strijov. "Deep Learning Model Selection of Suboptimal Complexity". Автоматика и телемеханика, n.º 8 (2018): 129–47. http://dx.doi.org/10.31857/s000523100001252-1.
Texto completoHe, Hengtao, Chao-Kai Wen, Shi Jin y Geoffrey Ye Li. "Model-Driven Deep Learning for MIMO Detection". IEEE Transactions on Signal Processing 68 (2020): 1702–15. http://dx.doi.org/10.1109/tsp.2020.2976585.
Texto completoMatiisen, Tambet, Aqeel Labash, Daniel Majoral, Jaan Aru y Raul Vicente. "Do Deep Reinforcement Learning Agents Model Intentions?" Stats 6, n.º 1 (28 de diciembre de 2022): 50–66. http://dx.doi.org/10.3390/stats6010004.
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