Artículos de revistas sobre el tema "Data-efficient Deep Learning"
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Chaudhary, Dr Sumit, Ms Neha Singh y Salaiya Pankaj. "Time-Efficient Algorithm for Data Annotation using Deep Learning". Indian Journal of Artificial Intelligence and Neural Networking 2, n.º 5 (30 de agosto de 2022): 8–11. http://dx.doi.org/10.54105/ijainn.e1058.082522.
Texto completoBiswas, Surojit, Grigory Khimulya, Ethan C. Alley, Kevin M. Esvelt y George M. Church. "Low-N protein engineering with data-efficient deep learning". Nature Methods 18, n.º 4 (abril de 2021): 389–96. http://dx.doi.org/10.1038/s41592-021-01100-y.
Texto completoEdstrom, Jonathon, Yifu Gong, Dongliang Chen, Jinhui Wang y Na Gong. "Data-Driven Intelligent Efficient Synaptic Storage for Deep Learning". IEEE Transactions on Circuits and Systems II: Express Briefs 64, n.º 12 (diciembre de 2017): 1412–16. http://dx.doi.org/10.1109/tcsii.2017.2767900.
Texto completoFeng, Wenhui, Chongzhao Han, Feng Lian y Xia Liu. "A Data-Efficient Training Method for Deep Reinforcement Learning". Electronics 11, n.º 24 (16 de diciembre de 2022): 4205. http://dx.doi.org/10.3390/electronics11244205.
Texto completoHu, Wenjin, Feng Liu y Jiebo Peng. "An Efficient Data Classification Decision Based on Multimodel Deep Learning". Computational Intelligence and Neuroscience 2022 (4 de mayo de 2022): 1–10. http://dx.doi.org/10.1155/2022/7636705.
Texto completoMairittha, Nattaya, Tittaya Mairittha y Sozo Inoue. "On-Device Deep Learning Inference for Efficient Activity Data Collection". Sensors 19, n.º 15 (5 de agosto de 2019): 3434. http://dx.doi.org/10.3390/s19153434.
Texto completoDuan, Yanjie, Yisheng Lv, Yu-Liang Liu y Fei-Yue Wang. "An efficient realization of deep learning for traffic data imputation". Transportation Research Part C: Emerging Technologies 72 (noviembre de 2016): 168–81. http://dx.doi.org/10.1016/j.trc.2016.09.015.
Texto completoSashank, Madipally Sai Krishna, Vijay Souri Maddila, Vikas Boddu y Y. Radhika. "Efficient deep learning based data augmentation techniques for enhanced learning on inadequate medical imaging data". ACTA IMEKO 11, n.º 1 (31 de marzo de 2022): 6. http://dx.doi.org/10.21014/acta_imeko.v11i1.1226.
Texto completoPetrovic, Nenad y Djordje Kocic. "Data-driven framework for energy-efficient smart cities". Serbian Journal of Electrical Engineering 17, n.º 1 (2020): 41–63. http://dx.doi.org/10.2298/sjee2001041p.
Texto completoYue, Yang, Bingyi Kang, Zhongwen Xu, Gao Huang y Shuicheng Yan. "Value-Consistent Representation Learning for Data-Efficient Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 9 (26 de junio de 2023): 11069–77. http://dx.doi.org/10.1609/aaai.v37i9.26311.
Texto completoShin, Hyunkyung, Hyeonung Shin, Wonje Choi, Jaesung Park, Minjae Park, Euiyul Koh y Honguk Woo. "Sample-Efficient Deep Learning Techniques for Burn Severity Assessment with Limited Data Conditions". Applied Sciences 12, n.º 14 (21 de julio de 2022): 7317. http://dx.doi.org/10.3390/app12147317.
Texto completoLyu, Daoming, Fangkai Yang, Bo Liu y Steven Gustafson. "SDRL: Interpretable and Data-Efficient Deep Reinforcement Learning Leveraging Symbolic Planning". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 2970–77. http://dx.doi.org/10.1609/aaai.v33i01.33012970.
Texto completoda Silva Lourenço, Catarina, Marleen C. Tjepkema-Cloostermans y Michel J. A. M. van Putten. "Efficient use of clinical EEG data for deep learning in epilepsy". Clinical Neurophysiology 132, n.º 6 (junio de 2021): 1234–40. http://dx.doi.org/10.1016/j.clinph.2021.01.035.
Texto completoCuayáhuitl, Heriberto. "A data-efficient deep learning approach for deployable multimodal social robots". Neurocomputing 396 (julio de 2020): 587–98. http://dx.doi.org/10.1016/j.neucom.2018.09.104.
Texto completoZhao, Junhui, Yiwen Nie, Shanjin Ni y Xiaoke Sun. "Traffic Data Imputation and Prediction: An Efficient Realization of Deep Learning". IEEE Access 8 (2020): 46713–22. http://dx.doi.org/10.1109/access.2020.2978530.
Texto completoTovar, Nathaniel, Sean (Seok-Chul) Kwon y Jinseong Jeong. "Image Upscaling with Deep Machine Learning for Energy-Efficient Data Communications". Electronics 12, n.º 3 (30 de enero de 2023): 689. http://dx.doi.org/10.3390/electronics12030689.
Texto completoLi, Mengkun y Yongjian Wang. "An Energy-Efficient Silicon Photonic-Assisted Deep Learning Accelerator for Big Data". Wireless Communications and Mobile Computing 2020 (16 de diciembre de 2020): 1–11. http://dx.doi.org/10.1155/2020/6661022.
Texto completoYuan, Mu, Lan Zhang, Xiang-Yang Li, Lin-Zhuo Yang y Hui Xiong. "Adaptive Model Scheduling for Resource-efficient Data Labeling". ACM Transactions on Knowledge Discovery from Data 16, n.º 4 (31 de agosto de 2022): 1–22. http://dx.doi.org/10.1145/3494559.
Texto completoOnofrey, John A., Lawrence H. Staib, Xiaojie Huang, Fan Zhang, Xenophon Papademetris, Dimitris Metaxas, Daniel Rueckert y James S. Duncan. "Sparse Data–Driven Learning for Effective and Efficient Biomedical Image Segmentation". Annual Review of Biomedical Engineering 22, n.º 1 (4 de junio de 2020): 127–53. http://dx.doi.org/10.1146/annurev-bioeng-060418-052147.
Texto completoBhat, Sanjit, David Lu, Albert Kwon y Srinivas Devadas. "Var-CNN: A Data-Efficient Website Fingerprinting Attack Based on Deep Learning". Proceedings on Privacy Enhancing Technologies 2019, n.º 4 (1 de octubre de 2019): 292–310. http://dx.doi.org/10.2478/popets-2019-0070.
Texto completoWang, Yang, Yutong Li, Ting Wang y Gang Liu. "Towards an energy-efficient Data Center Network based on deep reinforcement learning". Computer Networks 210 (junio de 2022): 108939. http://dx.doi.org/10.1016/j.comnet.2022.108939.
Texto completoShiloh, Lihi, Avishay Eyal y Raja Giryes. "Efficient Processing of Distributed Acoustic Sensing Data Using a Deep Learning Approach". Journal of Lightwave Technology 37, n.º 18 (15 de septiembre de 2019): 4755–62. http://dx.doi.org/10.1109/jlt.2019.2919713.
Texto completoYi, Deliang, Xin Zhou, Yonggang Wen y Rui Tan. "Efficient Compute-Intensive Job Allocation in Data Centers via Deep Reinforcement Learning". IEEE Transactions on Parallel and Distributed Systems 31, n.º 6 (1 de junio de 2020): 1474–85. http://dx.doi.org/10.1109/tpds.2020.2968427.
Texto completoJeong, Seunghwan, Gwangpyo Yoo, Minjong Yoo, Ikjun Yeom y Honguk Woo. "Resource-Efficient Sensor Data Management for Autonomous Systems Using Deep Reinforcement Learning". Sensors 19, n.º 20 (11 de octubre de 2019): 4410. http://dx.doi.org/10.3390/s19204410.
Texto completoHe, Yan, Bin Fu, Jian Yu, Renfa Li y Rucheng Jiang. "Efficient Learning of Healthcare Data from IoT Devices by Edge Convolution Neural Networks". Applied Sciences 10, n.º 24 (15 de diciembre de 2020): 8934. http://dx.doi.org/10.3390/app10248934.
Texto completoWu, Chunyi y Ya Li. "FLOM: Toward Efficient Task Processing in Big Data with Federated Learning". Security and Communication Networks 2022 (27 de enero de 2022): 1–16. http://dx.doi.org/10.1155/2022/5277362.
Texto completoZhang, Lan, Yu Feng Nie y Zhen Hai Wang. "Image De-Noising Using Deep Learning". Applied Mechanics and Materials 641-642 (septiembre de 2014): 1287–90. http://dx.doi.org/10.4028/www.scientific.net/amm.641-642.1287.
Texto completoSalakhutdinov, Ruslan y Geoffrey Hinton. "An Efficient Learning Procedure for Deep Boltzmann Machines". Neural Computation 24, n.º 8 (agosto de 2012): 1967–2006. http://dx.doi.org/10.1162/neco_a_00311.
Texto completoRen, Jing, Xishi Huang y Raymond N. Huang. "Efficient Deep Reinforcement Learning for Optimal Path Planning". Electronics 11, n.º 21 (7 de noviembre de 2022): 3628. http://dx.doi.org/10.3390/electronics11213628.
Texto completoBlank, Andreas, Lukas Baier, Oguz Kedilioglu, Xuebei Zhu, Maximilian Metzner y Jörg Franke. "Effiziente KI-Adaption durch synthetische Daten/Efficient AI Adaption using Synthetic Data". wt Werkstattstechnik online 111, n.º 10 (2021): 759–62. http://dx.doi.org/10.37544/1436-4980-2021-10-105.
Texto completoHao, Ruqian, Lin Liu, Jing Zhang, Xiangzhou Wang, Juanxiu Liu, Xiaohui Du, Wen He, Jicheng Liao, Lu Liu y Yuanying Mao. "A Data-Efficient Framework for the Identification of Vaginitis Based on Deep Learning". Journal of Healthcare Engineering 2022 (27 de febrero de 2022): 1–11. http://dx.doi.org/10.1155/2022/1929371.
Texto completoEide, Siri S., Michael A. Riegler, Hugo L. Hammer y John Bjørnar Bremnes. "Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources". Sensors 22, n.º 7 (6 de abril de 2022): 2802. http://dx.doi.org/10.3390/s22072802.
Texto completoShin, Tae-Ho y Soo-Hyung Kim. "Utility Analysis about Log Data Anomaly Detection Based on Federated Learning". Applied Sciences 13, n.º 7 (1 de abril de 2023): 4495. http://dx.doi.org/10.3390/app13074495.
Texto completoMoss, Adam. "Accelerated Bayesian inference using deep learning". Monthly Notices of the Royal Astronomical Society 496, n.º 1 (28 de mayo de 2020): 328–38. http://dx.doi.org/10.1093/mnras/staa1469.
Texto completoVengateshwaran, Mr M. "Efficient Deep Learning Approach for Dimensionality Reduction using Micro blogs from Big data". International Journal for Research in Applied Science and Engineering Technology V, n.º III (9 de marzo de 2017): 5–10. http://dx.doi.org/10.22214/ijraset.2017.3002.
Texto completoKhodaparast, Seyed Saeed, Xiao Lu, Ping Wang y Uyen Trang Nguyen. "Deep Reinforcement Learning Based Energy Efficient Multi-UAV Data Collection for IoT Networks". IEEE Open Journal of Vehicular Technology 2 (2021): 249–60. http://dx.doi.org/10.1109/ojvt.2021.3085421.
Texto completoJiang, Rong, Zhipeng Wang, Bin He, Yanmin Zhou, Gang Li y Zhongpan Zhu. "A data-efficient goal-directed deep reinforcement learning method for robot visuomotor skill". Neurocomputing 462 (octubre de 2021): 389–401. http://dx.doi.org/10.1016/j.neucom.2021.08.023.
Texto completoNAMOZOV, A. y Y. I. CHO. "An Efficient Deep Learning Algorithm for Fire and Smoke Detection with Limited Data". Advances in Electrical and Computer Engineering 18, n.º 4 (2018): 121–28. http://dx.doi.org/10.4316/aece.2018.04015.
Texto completoHassan, Mohammad Mehedi, Abdu Gumaei, Ahmed Alsanad, Majed Alrubaian y Giancarlo Fortino. "A hybrid deep learning model for efficient intrusion detection in big data environment". Information Sciences 513 (marzo de 2020): 386–96. http://dx.doi.org/10.1016/j.ins.2019.10.069.
Texto completoEshghi, Mohammad, Alireza Souri, Babak Majidi y Amin Fadaeddini. "Data augmentation using fast converging CIELAB-GAN for efficient deep learning dataset generation". International Journal of Computational Science and Engineering 26, n.º 4 (2023): 459–69. http://dx.doi.org/10.1504/ijcse.2023.10057257.
Texto completoFadaeddini, Amin, Babak Majidi, Alireza Souri y Mohammad Eshghi. "Data augmentation using fast converging CIELAB-GAN for efficient deep learning dataset generation". International Journal of Computational Science and Engineering 26, n.º 4 (2023): 459–69. http://dx.doi.org/10.1504/ijcse.2023.132152.
Texto completoWei, Shengyun, Zhaolong Sun, Zhenyi Wang, Feifan Liao, Zhen Li y Haibo Mi. "An Efficient Data Augmentation Method for Automatic Modulation Recognition from Low-Data Imbalanced-Class Regime". Applied Sciences 13, n.º 5 (1 de marzo de 2023): 3177. http://dx.doi.org/10.3390/app13053177.
Texto completoXu, Wencai. "Efficient Distributed Image Recognition Algorithm of Deep Learning Framework TensorFlow". Journal of Physics: Conference Series 2066, n.º 1 (1 de noviembre de 2021): 012070. http://dx.doi.org/10.1088/1742-6596/2066/1/012070.
Texto completoEltehewy, Rokaya, Ahmed Abouelfarag y Sherine Nagy Saleh. "Efficient Classification of Imbalanced Natural Disasters Data Using Generative Adversarial Networks for Data Augmentation". ISPRS International Journal of Geo-Information 12, n.º 6 (17 de junio de 2023): 245. http://dx.doi.org/10.3390/ijgi12060245.
Texto completoRix, Tom, Kris K. Dreher, Jan-Hinrich Nölke, Melanie Schellenberg, Minu D. Tizabi, Alexander Seitel y Lena Maier-Hein. "Efficient Photoacoustic Image Synthesis with Deep Learning". Sensors 23, n.º 16 (10 de agosto de 2023): 7085. http://dx.doi.org/10.3390/s23167085.
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 completoKumar, Ravinder y Lokesh Kumar Shrivastav. "Gradient Boosting Machine and Deep Learning Approach in Big Data Analysis". Journal of Information Technology Research 15, n.º 1 (enero de 2022): 1–20. http://dx.doi.org/10.4018/jitr.2022010101.
Texto completoPolanski, Jaroslaw. "Unsupervised Learning in Drug Design from Self-Organization to Deep Chemistry". International Journal of Molecular Sciences 23, n.º 5 (3 de marzo de 2022): 2797. http://dx.doi.org/10.3390/ijms23052797.
Texto completoIstiaque, Shah Md, Asif Iqbal Khan y Sajjad Waheed. "Smart Intrusion Detection System Comprised of Machine Learning and Deep Learning". European Journal of Engineering Research and Science 5, n.º 10 (8 de octubre de 2020): 1168–73. http://dx.doi.org/10.24018/ejers.2020.5.10.2128.
Texto completoIstiaque, Shah Md, Asif Iqbal Khan y Sajjad Waheed. "Smart Intrusion Detection System Comprised of Machine Learning and Deep Learning". European Journal of Engineering and Technology Research 5, n.º 10 (8 de octubre de 2020): 1168–73. http://dx.doi.org/10.24018/ejeng.2020.5.10.2128.
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