Artículos de revistas sobre el tema "Continuous and distributed machine learning"
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Stan, Ioan-Mihail, Siarhei Padolski y Christopher Jon Lee. "Exploring the self-service model to visualize the results of the ATLAS Machine Learning analysis jobs in BigPanDA with Openshift OKD3". EPJ Web of Conferences 251 (2021): 02009. http://dx.doi.org/10.1051/epjconf/202125102009.
Texto completoYin, Zhongdong, Jingjing Tu y Yonghai Xu. "Development of a Kernel Extreme Learning Machine Model for Capacity Selection of Distributed Generation Considering the Characteristics of Electric Vehicles". Applied Sciences 9, n.º 12 (13 de junio de 2019): 2401. http://dx.doi.org/10.3390/app9122401.
Texto completoBrophy, Eoin, Maarten De Vos, Geraldine Boylan y Tomás Ward. "Estimation of Continuous Blood Pressure from PPG via a Federated Learning Approach". Sensors 21, n.º 18 (21 de septiembre de 2021): 6311. http://dx.doi.org/10.3390/s21186311.
Texto completoVrachimis, Andreas, Stella Gkegka y Kostas Kolomvatsos. "Resilient edge machine learning in smart city environments". Journal of Smart Cities and Society 2, n.º 1 (7 de julio de 2023): 3–24. http://dx.doi.org/10.3233/scs-230005.
Texto completoMusa, M. O. y E. E. Odokuma. "A framework for the detection of distributed denial of service attacks on network logs using ML and DL classifiers". Scientia Africana 22, n.º 3 (25 de enero de 2024): 153–64. http://dx.doi.org/10.4314/sa.v22i3.14.
Texto completoOliveri, Giorgio, Lucas C. van Laake, Cesare Carissimo, Clara Miette y Johannes T. B. Overvelde. "Continuous learning of emergent behavior in robotic matter". Proceedings of the National Academy of Sciences 118, n.º 21 (10 de mayo de 2021): e2017015118. http://dx.doi.org/10.1073/pnas.2017015118.
Texto completoKodaira, Daisuke, Kazuki Tsukazaki, Taiki Kure y Junji Kondoh. "Improving Forecast Reliability for Geographically Distributed Photovoltaic Generations". Energies 14, n.º 21 (4 de noviembre de 2021): 7340. http://dx.doi.org/10.3390/en14217340.
Texto completoHua, Xia y Lei Han. "Design and Practical Application of Sports Visualization Platform Based on Tracking Algorithm". Computational Intelligence and Neuroscience 2022 (16 de agosto de 2022): 1–9. http://dx.doi.org/10.1155/2022/4744939.
Texto completoRustam, Furqan, Muhammad Faheem Mushtaq, Ameer Hamza, Muhammad Shoaib Farooq, Anca Delia Jurcut y Imran Ashraf. "Denial of Service Attack Classification Using Machine Learning with Multi-Features". Electronics 11, n.º 22 (20 de noviembre de 2022): 3817. http://dx.doi.org/10.3390/electronics11223817.
Texto completoHuang, Leqi. "Problems, solutions and improvements on federated learning model". Applied and Computational Engineering 22, n.º 1 (23 de octubre de 2023): 183–86. http://dx.doi.org/10.54254/2755-2721/22/20231215.
Texto completoJohnson, Paul A. y Chris W. Johnson. "Earthquake fault slip and nonlinear dynamics". Journal of the Acoustical Society of America 153, n.º 3_supplement (1 de marzo de 2023): A203. http://dx.doi.org/10.1121/10.0018661.
Texto completoT V, Bhuvana. "AI ENABLED WATER CONSERVATION FOR IRRIGATION USING IOT". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, n.º 05 (14 de mayo de 2024): 1–5. http://dx.doi.org/10.55041/ijsrem33920.
Texto completoXie, Anze, Anders Carlsson, Jason Mohoney, Roger Waleffe, Shanan Peters, Theodoros Rekatsinas y Shivaram Venkataraman. "Demo of marius". Proceedings of the VLDB Endowment 14, n.º 12 (julio de 2021): 2759–62. http://dx.doi.org/10.14778/3476311.3476338.
Texto completoChang, Wanjun, Yangbo Li y Qidong Du. "Microblog Emotion Analysis Using Improved DBN Under Spark Platform". International Journal of Information Technologies and Systems Approach 16, n.º 2 (16 de febrero de 2023): 1–16. http://dx.doi.org/10.4018/ijitsa.318141.
Texto completoGómez, Jairo A., Jorge E. Patiño, Juan C. Duque y Santiago Passos. "Spatiotemporal Modeling of Urban Growth Using Machine Learning". Remote Sensing 12, n.º 1 (28 de diciembre de 2019): 109. http://dx.doi.org/10.3390/rs12010109.
Texto completoBehera, Ranjan, Sushree Das, Santanu Rath, Sanjay Misra y Robertas Damasevicius. "Comparative Study of Real Time Machine Learning Models for Stock Prediction through Streaming Data". JUCS - Journal of Universal Computer Science 26, n.º 9 (28 de septiembre de 2020): 1128–47. http://dx.doi.org/10.3897/jucs.2020.059.
Texto completoLiu, Bowen y Qiang Tang. "Secure Data Sharing in Federated Learning through Blockchain-Based Aggregation". Future Internet 16, n.º 4 (15 de abril de 2024): 133. http://dx.doi.org/10.3390/fi16040133.
Texto completoAvcı, İsa y Murat Koca. "Predicting DDoS Attacks Using Machine Learning Algorithms in Building Management Systems". Electronics 12, n.º 19 (5 de octubre de 2023): 4142. http://dx.doi.org/10.3390/electronics12194142.
Texto completoBattaglia, Elena, Simone Celano y Ruggero G. Pensa. "Differentially Private Distance Learning in Categorical Data". Data Mining and Knowledge Discovery 35, n.º 5 (13 de julio de 2021): 2050–88. http://dx.doi.org/10.1007/s10618-021-00778-0.
Texto completoKim, Bockjoo y Dimitri Bourilkov. "Automatic Monitoring of Large-Scale Computing Infrastructure". EPJ Web of Conferences 295 (2024): 07007. http://dx.doi.org/10.1051/epjconf/202429507007.
Texto completoPaul, Baltescu, Blunsom Phil y Hoang Hieu. "OxLM: A Neural Language Modelling Framework for Machine Translation". Prague Bulletin of Mathematical Linguistics 102, n.º 1 (11 de septiembre de 2014): 81–92. http://dx.doi.org/10.2478/pralin-2014-0016.
Texto completoSánchez-Reolid, Roberto, Arturo S. García, Miguel A. Vicente-Querol, Beatriz García-Martinez y Antonio Fernández-Caballero. "Distributed Architecture for Acquisition and Processing of Physiological Signals". Proceedings 31, n.º 1 (20 de noviembre de 2019): 30. http://dx.doi.org/10.3390/proceedings2019031030.
Texto completoOjugo, Arnold y Andrew Okonji Eboka. "An Empirical Evaluation On Comparative Machine Learning Techniques For Detection of The Distributed Denial of Service (DDoS) Attacks". Journal of Applied Science, Engineering, Technology, and Education 2, n.º 1 (13 de junio de 2020): 18–27. http://dx.doi.org/10.35877/454ri.asci2192.
Texto completoKareem, Amer, Haiming Liu y Vladan Velisavljevic. "A Privacy-Preserving Approach to Effectively Utilize Distributed Data for Malaria Image Detection". Bioengineering 11, n.º 4 (30 de marzo de 2024): 340. http://dx.doi.org/10.3390/bioengineering11040340.
Texto completoMelton, Joe R., Ed Chan, Koreen Millard, Matthew Fortier, R. Scott Winton, Javier M. Martín-López, Hinsby Cadillo-Quiroz, Darren Kidd y Louis V. Verchot. "A map of global peatland extent created using machine learning (Peat-ML)". Geoscientific Model Development 15, n.º 12 (20 de junio de 2022): 4709–38. http://dx.doi.org/10.5194/gmd-15-4709-2022.
Texto completoLi, Boyuan, Shengbo Chen y Zihao Peng. "New Generation Federated Learning". Sensors 22, n.º 21 (3 de noviembre de 2022): 8475. http://dx.doi.org/10.3390/s22218475.
Texto completoSitokonstantinou, Vasileios, Alkiviadis Koukos, Thanassis Drivas, Charalampos Kontoes, Ioannis Papoutsis y Vassilia Karathanassi. "A Scalable Machine Learning Pipeline for Paddy Rice Classification Using Multi-Temporal Sentinel Data". Remote Sensing 13, n.º 9 (1 de mayo de 2021): 1769. http://dx.doi.org/10.3390/rs13091769.
Texto completoZeng, Liang, Wenxin Wang y Wei Zuo. "A Federated Learning Latency Minimization Method for UAV Swarms Aided by Communication Compression and Energy Allocation". Sensors 23, n.º 13 (21 de junio de 2023): 5787. http://dx.doi.org/10.3390/s23135787.
Texto completoKawabata, Kuniaki, Zhi-Wei Luo y Jie Huang. "Special Issue on Machine Intelligence for Robotics and Mechatronics". Journal of Robotics and Mechatronics 22, n.º 4 (20 de agosto de 2010): 417. http://dx.doi.org/10.20965/jrm.2010.p0417.
Texto completoGreifeneder, Felix, Claudia Notarnicola y Wolfgang Wagner. "A Machine Learning-Based Approach for Surface Soil Moisture Estimations with Google Earth Engine". Remote Sensing 13, n.º 11 (27 de mayo de 2021): 2099. http://dx.doi.org/10.3390/rs13112099.
Texto completoHao, Yixue, Yiming Miao, Min Chen, Hamid Gharavi y Victor Leung. "6G Cognitive Information Theory: A Mailbox Perspective". Big Data and Cognitive Computing 5, n.º 4 (16 de octubre de 2021): 56. http://dx.doi.org/10.3390/bdcc5040056.
Texto completoSun, Hanqi, Wanquan Zhu, Ziyu Sun, Mingsheng Cao y Wenbin Liu. "FMDL: Federated Mutual Distillation Learning for Defending Backdoor Attacks". Electronics 12, n.º 23 (30 de noviembre de 2023): 4838. http://dx.doi.org/10.3390/electronics12234838.
Texto completoKarlgren, Jussi y Pentti Kanerva. "High-dimensional distributed semantic spaces for utterances". Natural Language Engineering 25, n.º 4 (julio de 2019): 503–17. http://dx.doi.org/10.1017/s1351324919000226.
Texto completoAshush, Nerya, Shlomo Greenberg, Erez Manor y Yehuda Ben-Shimol. "Unsupervised Drones Swarm Characterization Using RF Signals Analysis and Machine Learning Methods". Sensors 23, n.º 3 (1 de febrero de 2023): 1589. http://dx.doi.org/10.3390/s23031589.
Texto completoNaqvi, Sardar Shan Ali, Yuancheng Li y Muhammad Uzair. "DDoS attack detection in smart grid network using reconstructive machine learning models". PeerJ Computer Science 10 (9 de enero de 2024): e1784. http://dx.doi.org/10.7717/peerj-cs.1784.
Texto completoFlores, Juan J., Jose L. Garcia-Nava, Jose R. Cedeno Gonzalez, Victor M. Tellez, Felix Calderon y Arturo Medrano. "A Machine-Learning Pipeline for Large-Scale Power-Quality Forecasting in the Mexican Distribution Grid". Applied Sciences 12, n.º 17 (24 de agosto de 2022): 8423. http://dx.doi.org/10.3390/app12178423.
Texto completoManavalan, Mani. "Intersection of Artificial Intelligence, Machine Learning, and Internet of Things – An Economic Overview". Global Disclosure of Economics and Business 9, n.º 2 (25 de diciembre de 2020): 119–28. http://dx.doi.org/10.18034/gdeb.v9i2.584.
Texto completoRashid, Kanwal, Yousaf Saeed, Abid Ali, Faisal Jamil, Reem Alkanhel y Ammar Muthanna. "An Adaptive Real-Time Malicious Node Detection Framework Using Machine Learning in Vehicular Ad-Hoc Networks (VANETs)". Sensors 23, n.º 5 (26 de febrero de 2023): 2594. http://dx.doi.org/10.3390/s23052594.
Texto completoZhang, Nan, Mingjie Chen, Fan Yang, Cancan Yang, Penghui Yang, Yushan Gao, Yue Shang y Daoli Peng. "Forest Height Mapping Using Feature Selection and Machine Learning by Integrating Multi-Source Satellite Data in Baoding City, North China". Remote Sensing 14, n.º 18 (6 de septiembre de 2022): 4434. http://dx.doi.org/10.3390/rs14184434.
Texto completoRajab Asaad, Renas y Subhi R. M. Zeebaree. "Enhancing Security and Privacy in Distributed Cloud Environments: A Review of Protocols and Mechanisms". Academic Journal of Nawroz University 13, n.º 1 (31 de marzo de 2024): 476–88. http://dx.doi.org/10.25007/ajnu.v13n1a2010.
Texto completoNaeem, Muhammad, Jian Yu, Muhammad Aamir, Sajjad Ahmad Khan, Olayinka Adeleye y Zardad Khan. "Comparative analysis of machine learning approaches to analyze and predict the COVID-19 outbreak". PeerJ Computer Science 7 (16 de diciembre de 2021): e746. http://dx.doi.org/10.7717/peerj-cs.746.
Texto completoBonilla-Garzón, Andrea, Shyam Madhusudhana, Robert P. Dziak y Holger Klinck. "Assessing vocal activity patterns of leopard seals (Hydrurga leptonyx) In the Bransfield Strait, Antarctica using machine learning". Journal of the Acoustical Society of America 152, n.º 4 (octubre de 2022): A106. http://dx.doi.org/10.1121/10.0015696.
Texto completoPriya, Harshitha. "A Cloud Approach for Melanoma Detection Based On Deep Learning Networks". International Journal for Research in Applied Science and Engineering Technology 11, n.º 5 (31 de mayo de 2023): 3983–88. http://dx.doi.org/10.22214/ijraset.2023.52571.
Texto completoAnand, Dubey y Choubey Siddhartha. "Blockchain and machine learning for data analytics, privacy preserving, and security in fraud detection". i-manager’s Journal on Software Engineering 18, n.º 1 (2023): 45. http://dx.doi.org/10.26634/jse.18.1.20091.
Texto completoChen, Shaomin, Jiachen Gao, Fangchuan Lou, Yunfei Tuo, Shuai Tan, Yuyang Shan, Lihua Luo, Zhilin Xu, Zhengfu Zhang y Xiangyu Huang. "Rapid estimation of soil water content based on hyperspectral reflectance combined with continuous wavelet transform, feature extraction, and extreme learning machine". PeerJ 12 (22 de agosto de 2024): e17954. http://dx.doi.org/10.7717/peerj.17954.
Texto completoAhmed, Mehreen, Rafia Mumtaz, Syed Mohammad Hassan Zaidi, Maryam Hafeez, Syed Ali Raza Zaidi y Muneer Ahmad. "Distributed Fog Computing for Internet of Things (IoT) Based Ambient Data Processing and Analysis". Electronics 9, n.º 11 (22 de octubre de 2020): 1756. http://dx.doi.org/10.3390/electronics9111756.
Texto completoBakurov, Illya, Marco Buzzelli, Mauro Castelli, Leonardo Vanneschi y Raimondo Schettini. "General Purpose Optimization Library (GPOL): A Flexible and Efficient Multi-Purpose Optimization Library in Python". Applied Sciences 11, n.º 11 (23 de mayo de 2021): 4774. http://dx.doi.org/10.3390/app11114774.
Texto completoBarron, Alfredo, Dante D. Sanchez-Gallegos, Diana Carrizales-Espinoza, J. L. Gonzalez-Compean y Miguel Morales-Sandoval. "On the Efficient Delivery and Storage of IoT Data in Edge–Fog–Cloud Environments". Sensors 22, n.º 18 (16 de septiembre de 2022): 7016. http://dx.doi.org/10.3390/s22187016.
Texto completoSamuel Olaoluwa Folorunsho, Olubunmi Adeolu Adenekan, Chinedu Ezeigweneme, Ike Chidiebere Somadina y Patrick Azuka Okeleke. "Ensuring Cybersecurity in telecommunications: Strategies to protect digital infrastructure and sensitive data". Computer Science & IT Research Journal 5, n.º 8 (23 de agosto de 2024): 1855–83. http://dx.doi.org/10.51594/csitrj.v5i8.1448.
Texto completoDudeja, Deepak, Sabeena Yasmin Hera, Nitika Vats Doohan, Nilesh Dubey, R. Mahaveerakannan, Tariq Ahamed Ahanger y Simon Karanja Hinga. "Energy Efficient and Secure Information Dissemination in Heterogeneous Wireless Sensor Networks Using Machine Learning Techniques". Wireless Communications and Mobile Computing 2022 (7 de junio de 2022): 1–14. http://dx.doi.org/10.1155/2022/2206530.
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