Artículos de revistas sobre el tema "Deep learning architecture"
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Munir, Khushboo, Fabrizio Frezza y Antonello Rizzi. "Deep Learning Hybrid Techniques for Brain Tumor Segmentation". Sensors 22, n.º 21 (26 de octubre de 2022): 8201. http://dx.doi.org/10.3390/s22218201.
Texto completoAlvarez-Gonzalez, Ruben y Andres Mendez-Vazquez. "Deep Learning Architecture Reduction for fMRI Data". Brain Sciences 12, n.º 2 (8 de febrero de 2022): 235. http://dx.doi.org/10.3390/brainsci12020235.
Texto completoKumar, Bhavesh Shri, Naren J, Vithya G y Prahathish K. "A Novel Architecture based on Deep Learning for Scene Image Recognition". International Journal of Psychosocial Rehabilitation 23, n.º 1 (20 de febrero de 2019): 400–404. http://dx.doi.org/10.37200/ijpr/v23i1/pr190251.
Texto completoHyunhee Park, Hyunhee Park. "Edge Based Lightweight Authentication Architecture Using Deep Learning for Vehicular Networks". 網際網路技術學刊 23, n.º 1 (enero de 2022): 195–202. http://dx.doi.org/10.53106/160792642022012301020.
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 completoZou, Han, Jing Ge, Ruichao Liu y Lin He. "Feature Recognition of Regional Architecture Forms Based on Machine Learning: A Case Study of Architecture Heritage in Hubei Province, China". Sustainability 15, n.º 4 (14 de febrero de 2023): 3504. http://dx.doi.org/10.3390/su15043504.
Texto completoMa, Rui, Jia-Ching Hsu, Tian Tan, Eriko Nurvitadhi, David Sheffield, Rob Pelt, Martin Langhammer, Jaewoong Sim, Aravind Dasu y Derek Chiou. "Specializing FGPU for Persistent Deep Learning". ACM Transactions on Reconfigurable Technology and Systems 14, n.º 2 (8 de julio de 2021): 1–23. http://dx.doi.org/10.1145/3457886.
Texto completoSewak, Mohit, Sanjay K. Sahay y Hemant Rathore. "An Overview of Deep Learning Architecture of Deep Neural Networks and Autoencoders". Journal of Computational and Theoretical Nanoscience 17, n.º 1 (1 de enero de 2020): 182–88. http://dx.doi.org/10.1166/jctn.2020.8648.
Texto completoHartanto, Cahyo Adhi y Laksmita Rahadianti. "Single Image Dehazing Using Deep Learning". JOIV : International Journal on Informatics Visualization 5, n.º 1 (22 de marzo de 2021): 76. http://dx.doi.org/10.30630/joiv.5.1.431.
Texto completoGhimire, Deepak, Dayoung Kil y Seong-heum Kim. "A Survey on Efficient Convolutional Neural Networks and Hardware Acceleration". Electronics 11, n.º 6 (18 de marzo de 2022): 945. http://dx.doi.org/10.3390/electronics11060945.
Texto completoZhong, Guoqiang, Kang Zhang, Hongxu Wei, Yuchen Zheng y Junyu Dong. "Marginal Deep Architecture: Stacking Feature Learning Modules to Build Deep Learning Models". IEEE Access 7 (2019): 30220–33. http://dx.doi.org/10.1109/access.2019.2902631.
Texto completoSushma, Prof Ksn, Nishant Upadhyay, Ajeet Singh, Prasenjeet Kr Singh y Tanzeelah Firdaus. "Plant Disease Detection Using Deep Learning". International Journal for Research in Applied Science and Engineering Technology 10, n.º 4 (30 de abril de 2022): 1099–101. http://dx.doi.org/10.22214/ijraset.2022.41451.
Texto completoLattari, Francesco, Borja Gonzalez Leon, Francesco Asaro, Alessio Rucci, Claudio Prati y Matteo Matteucci. "Deep Learning for SAR Image Despeckling". Remote Sensing 11, n.º 13 (28 de junio de 2019): 1532. http://dx.doi.org/10.3390/rs11131532.
Texto completoChen, Xihui, Aimin Ji y Gang Cheng. "A Novel Deep Feature Learning Method Based on the Fused-Stacked AEs for Planetary Gear Fault Diagnosis". Energies 12, n.º 23 (27 de noviembre de 2019): 4522. http://dx.doi.org/10.3390/en12234522.
Texto completoSegura-Bedmar, Isabel y Pablo Raez. "Cohort selection for clinical trials using deep learning models". Journal of the American Medical Informatics Association 26, n.º 11 (17 de septiembre de 2019): 1181–88. http://dx.doi.org/10.1093/jamia/ocz139.
Texto completoKhrisat, Mohammad S., Anwar Alabadi, Saleh Khawatreh, Majed Omar Al-Dwairi y Ziad A. Alqadi. "Autoregressive prediction analysis using machine deep learning". Indonesian Journal of Electrical Engineering and Computer Science 27, n.º 3 (1 de septiembre de 2022): 1509. http://dx.doi.org/10.11591/ijeecs.v27.i3.pp1509-1516.
Texto completoAlsaadi, Zaran, Easa Alshamani, Mohammed Alrehaili, Abdulmajeed Ayesh D. Alrashdi, Saleh Albelwi y Abdelrahman Osman Elfaki. "A Real Time Arabic Sign Language Alphabets (ArSLA) Recognition Model Using Deep Learning Architecture". Computers 11, n.º 5 (10 de mayo de 2022): 78. http://dx.doi.org/10.3390/computers11050078.
Texto completoAbtahi, Mansour, David Le, Jennifer I. Lim y Xincheng Yao. "MF-AV-Net: an open-source deep learning network with multimodal fusion options for artery-vein segmentation in OCT angiography". Biomedical Optics Express 13, n.º 9 (22 de agosto de 2022): 4870. http://dx.doi.org/10.1364/boe.468483.
Texto completoPachón, César G., Dora M. Ballesteros y Diego Renza. "Fake Banknote Recognition Using Deep Learning". Applied Sciences 11, n.º 3 (30 de enero de 2021): 1281. http://dx.doi.org/10.3390/app11031281.
Texto completoCheng, Anda, Jiaxing Wang, Xi Sheryl Zhang, Qiang Chen, Peisong Wang y Jian Cheng. "DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 6 (28 de junio de 2022): 6358–66. http://dx.doi.org/10.1609/aaai.v36i6.20586.
Texto completoPollok, Stefan y Rasmus Bjørk. "Deep learning for magnetism". Europhysics News 53, n.º 2 (2022): 18–21. http://dx.doi.org/10.1051/epn/2022204.
Texto completoBelhaouari, Samir Brahim y Hafsa Raissouli. "MADL: A Multilevel Architecture of Deep Learning". International Journal of Computational Intelligence Systems 14, n.º 1 (2021): 693. http://dx.doi.org/10.2991/ijcis.d.201216.003.
Texto completoLee, Soo-Hwan, Jong-Chan Kim y Dong-Hoan Seo. "Image reconstruction technique using deep learning architecture". Journal of the Korean Society of Marine Engineering 42, n.º 2 (28 de febrero de 2018): 121–26. http://dx.doi.org/10.5916/jkosme.2018.42.2.121.
Texto completoAyad, Hayder, Ikhlas Watan Ghindawi y Mustafa Salam Kadhm. "Lung Segmentation Using Proposed Deep Learning Architecture". International Journal of Online and Biomedical Engineering (iJOE) 16, n.º 15 (15 de diciembre de 2020): 141. http://dx.doi.org/10.3991/ijoe.v16i15.17115.
Texto completoChen, Xi-liang, Lei Cao, Chen-xi Li, Zhi-xiong Xu y Jun Lai. "Ensemble Network Architecture for Deep Reinforcement Learning". Mathematical Problems in Engineering 2018 (2018): 1–6. http://dx.doi.org/10.1155/2018/2129393.
Texto completoVerma, Arnav, Devesh Samaiya y Karunesh K. Gupta. "Nonlinear Motion Tracking by Deep Learning Architecture". IOP Conference Series: Materials Science and Engineering 331 (marzo de 2018): 012020. http://dx.doi.org/10.1088/1757-899x/331/1/012020.
Texto completoPon Kumar, Steven Spielberg, Aditya Tulsyan, Bhushan Gopaluni y Philip Loewen. "A Deep Learning Architecture for Predictive Control". IFAC-PapersOnLine 51, n.º 18 (2018): 512–17. http://dx.doi.org/10.1016/j.ifacol.2018.09.373.
Texto completoLi, Xiang, Ling Peng, Yuan Hu, Jing Shao y Tianhe Chi. "Deep learning architecture for air quality predictions". Environmental Science and Pollution Research 23, n.º 22 (13 de octubre de 2016): 22408–17. http://dx.doi.org/10.1007/s11356-016-7812-9.
Texto completoSiłka, Wojciech, Michał Wieczorek, Jakub Siłka y Marcin Woźniak. "Malaria Detection Using Advanced Deep Learning Architecture". Sensors 23, n.º 3 (29 de enero de 2023): 1501. http://dx.doi.org/10.3390/s23031501.
Texto completoP, Shanmugavadivu, Mary Shanthi Rani M, Chitra P, Lakshmanan S, Nagaraja P y Vignesh U. "Bio-Optimization of Deep Learning Network Architectures". Security and Communication Networks 2022 (20 de septiembre de 2022): 1–11. http://dx.doi.org/10.1155/2022/3718340.
Texto completoKarypidis, Efstathios, Stylianos G. Mouslech, Kassiani Skoulariki y Alexandros Gazis. "Comparison Analysis of Traditional Machine Learning and Deep Learning Techniques for Data and Image Classification". WSEAS TRANSACTIONS ON MATHEMATICS 21 (23 de marzo de 2022): 122–30. http://dx.doi.org/10.37394/23206.2022.21.19.
Texto completoVelankar, Makarand, Sneha Thombre y Harshad Wadkar. "EVALUATING DEEP LEARNING MODELS FOR MUSIC EMOTION RECOGNITION". International Journal of Engineering Applied Sciences and Technology 7, n.º 6 (1 de octubre de 2022): 252–59. http://dx.doi.org/10.33564/ijeast.2022.v07i06.026.
Texto completoBillah, Umme Hafsa, Hung Manh La y Alireza Tavakkoli. "Deep Learning-Based Feature Silencing for Accurate Concrete Crack Detection". Sensors 20, n.º 16 (7 de agosto de 2020): 4403. http://dx.doi.org/10.3390/s20164403.
Texto completoJavaid, Sameena, Safdar Rizvi, Muhammad Talha Ubaid, Abdou Darboe y Shakir Mahmood Mayo. "Interpretation of Expressions through Hand Signs Using Deep Learning Techniques". Vol 4 Issue 2 4, n.º 2 (25 de junio de 2022): 596–611. http://dx.doi.org/10.33411/ijist/2022040225.
Texto completoAkbani, Sufiyan Salim, Adeeba Naaz, Nazish Kausar y Prof Abdul Razzaque. "Brain Tumor Detection Using Deep Learning". International Journal for Research in Applied Science and Engineering Technology 10, n.º 4 (30 de abril de 2022): 573–77. http://dx.doi.org/10.22214/ijraset.2022.41321.
Texto completoFarhi, Lubna, Saadia Mansoor Kazmi, Hassan Imam, Mejdal Alqahtani y Farhan Ur Rehman. "Dermoscopic Image Classification Using Deep Belief Learning Network Architecture". Wireless Communications and Mobile Computing 2022 (25 de mayo de 2022): 1–13. http://dx.doi.org/10.1155/2022/2415726.
Texto completoDefresne, Marianne, Sophie Barbe y Thomas Schiex. "Protein Design with Deep Learning". International Journal of Molecular Sciences 22, n.º 21 (29 de octubre de 2021): 11741. http://dx.doi.org/10.3390/ijms222111741.
Texto completoFielding, Ben y Li Zhang. "Evolving Deep DenseBlock Architecture Ensembles for Image Classification". Electronics 9, n.º 11 (9 de noviembre de 2020): 1880. http://dx.doi.org/10.3390/electronics9111880.
Texto completoSen, Gabriel, Albert Adeboye y Oluwole Alagbe. "The Influence of Architecture Students’ Learning Approaches on their Academic Performance in Two Nigeria Universities". International Journal of Learning, Teaching and Educational Research 20, n.º 2 (28 de febrero de 2021): 137–51. http://dx.doi.org/10.26803/ijlter.20.2.8.
Texto completoRuder, Sebastian, Joachim Bingel, Isabelle Augenstein y Anders Søgaard. "Latent Multi-Task Architecture Learning". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 4822–29. http://dx.doi.org/10.1609/aaai.v33i01.33014822.
Texto completoHernandez-Leal, Pablo, Bilal Kartal y Matthew E. Taylor. "Agent Modeling as Auxiliary Task for Deep Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 15, n.º 1 (8 de octubre de 2019): 31–37. http://dx.doi.org/10.1609/aiide.v15i1.5221.
Texto completoAhamad, Afaroj, Chi-Chia Sun y Wen-Kai Kuo. "Quantized Semantic Segmentation Deep Architecture for Deployment on an Edge Computing Device for Image Segmentation". Electronics 11, n.º 21 (31 de octubre de 2022): 3561. http://dx.doi.org/10.3390/electronics11213561.
Texto completoNguyen, Chi Cuong, Giang Son Tran, Thi Phuong Nghiem, Jean-Christophe Burie y Chi Mai Luong. "Real-Time Smile Detection using Deep Learning". Journal of Computer Science and Cybernetics 35, n.º 2 (3 de junio de 2019): 135–45. http://dx.doi.org/10.15625/1813-9663/35/2/13315.
Texto completoLiu, Xiaobo, Chaochao Zhang, Zhihua Cai, Jianfeng Yang, Zhilang Zhou y Xin Gong. "Continuous Particle Swarm Optimization-Based Deep Learning Architecture Search for Hyperspectral Image Classification". Remote Sensing 13, n.º 6 (12 de marzo de 2021): 1082. http://dx.doi.org/10.3390/rs13061082.
Texto completoNistor, Sergiu Cosmin, Tudor Alexandru Ileni y Adrian Sergiu Dărăbant. "Automatic Development of Deep Learning Architectures for Image Segmentation". Sustainability 12, n.º 22 (20 de noviembre de 2020): 9707. http://dx.doi.org/10.3390/su12229707.
Texto completoRathnam, S. Muni y G. Siva Koteswara Rao. "A Novel Deep Learning Architecture for Image Hiding". WSEAS TRANSACTIONS ON SIGNAL PROCESSING 16 (26 de febrero de 2021): 206–10. http://dx.doi.org/10.37394/232014.2020.16.23.
Texto completoBobadilla, Jesus, Santiago Alonso y Antonio Hernando. "Deep Learning Architecture for Collaborative Filtering Recommender Systems". Applied Sciences 10, n.º 7 (3 de abril de 2020): 2441. http://dx.doi.org/10.3390/app10072441.
Texto completoSun, Maoran, Fan Zhang, Fabio Duarte y Carlo Ratti. "Understanding architecture age and style through deep learning". Cities 128 (septiembre de 2022): 103787. http://dx.doi.org/10.1016/j.cities.2022.103787.
Texto completoChakravarthy, Arnav. "HYBRID ARCHITECTURE FOR SENTIMENT ANALYSIS USING DEEP LEARNING". International Journal of Advanced Research in Computer Science 9, n.º 1 (20 de febrero de 2018): 735–38. http://dx.doi.org/10.26483/ijarcs.v9i1.5388.
Texto completoBui, Trong-An, Pei-Jun Lee, Kai-Yew Lum, Clarissa Loh y Kyo Tan. "Deep Learning for Landslide Recognition in Satellite Architecture". IEEE Access 8 (2020): 143665–78. http://dx.doi.org/10.1109/access.2020.3014305.
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