Artykuły w czasopismach na temat „Ensemble neural noise”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Sprawdź 50 najlepszych artykułów w czasopismach naukowych na temat „Ensemble neural noise”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Przeglądaj artykuły w czasopismach z różnych dziedzin i twórz odpowiednie bibliografie.
Timme, Nicholas M., David Linsenbardt i Christopher C. Lapish. "A Method to Present and Analyze Ensembles of Information Sources". Entropy 22, nr 5 (21.05.2020): 580. http://dx.doi.org/10.3390/e22050580.
Pełny tekst źródłaNanni, Loris, Gianluca Maguolo, Sheryl Brahnam i Michelangelo Paci. "An Ensemble of Convolutional Neural Networks for Audio Classification". Applied Sciences 11, nr 13 (22.06.2021): 5796. http://dx.doi.org/10.3390/app11135796.
Pełny tekst źródłaSheng, Chunyang, Haixia Wang, Xiao Lu, Zhiguo Zhang, Wei Cui i Yuxia Li. "Distributed Gaussian Granular Neural Networks Ensemble for Prediction Intervals Construction". Complexity 2019 (3.07.2019): 1–17. http://dx.doi.org/10.1155/2019/2379584.
Pełny tekst źródłaChaouachi, Aymen, Rashad M. Kamel i Ken Nagasaka. "Neural Network Ensemble-Based Solar Power Generation Short-Term Forecasting". Journal of Advanced Computational Intelligence and Intelligent Informatics 14, nr 1 (20.01.2010): 69–75. http://dx.doi.org/10.20965/jaciii.2010.p0069.
Pełny tekst źródłaNoh, Kyoungjin, i Joon-Hyuk Chang. "Deep neural network ensemble for reducing artificial noise in bandwidth extension". Digital Signal Processing 102 (lipiec 2020): 102760. http://dx.doi.org/10.1016/j.dsp.2020.102760.
Pełny tekst źródłaHe, Lei, Xiaohong Shen, Muhang Zhang i Haiyan Wang. "Discriminative Ensemble Loss for Deep Neural Network on Classification of Ship-Radiated Noise". IEEE Signal Processing Letters 28 (2021): 449–53. http://dx.doi.org/10.1109/lsp.2021.3057539.
Pełny tekst źródłaDai, Feng Yan, Zhao Yao Shi i Jia Chun Lin. "Research of Defect Detection Method Noise for Bevel Gear". Advanced Materials Research 889-890 (luty 2014): 722–25. http://dx.doi.org/10.4028/www.scientific.net/amr.889-890.722.
Pełny tekst źródłaEt. al., Rajesh Birok,. "ECG Denoising Using Artificial Neural Networks and Complete Ensemble Empirical Mode Decomposition". Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, nr 2 (10.04.2021): 2382–89. http://dx.doi.org/10.17762/turcomat.v12i2.2033.
Pełny tekst źródłaJin, Dequan, Jigen Peng i Bin Li. "A New Clustering Approach on the Basis of Dynamical Neural Field". Neural Computation 23, nr 8 (sierpień 2011): 2032–57. http://dx.doi.org/10.1162/neco_a_00153.
Pełny tekst źródłaChen, Kai, Kai Xie, Chang Wen i Xin-Gong Tang. "Weak Signal Enhance Based on the Neural Network Assisted Empirical Mode Decomposition". Sensors 20, nr 12 (15.06.2020): 3373. http://dx.doi.org/10.3390/s20123373.
Pełny tekst źródłaZahid, Saadia, Fawad Hussain, Muhammad Rashid, Muhammad Haroon Yousaf i Hafiz Adnan Habib. "Optimized Audio Classification and Segmentation Algorithm by Using Ensemble Methods". Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/209814.
Pełny tekst źródłaHARTONO, PITOYO, i SHUJI HASHIMOTO. "EXTRACTING THE PRINCIPAL BEHAVIOR OF A PROBABILISTIC SUPERVISOR THROUGH NEURAL NETWORKS ENSEMBLE". International Journal of Neural Systems 12, nr 03n04 (czerwiec 2002): 291–301. http://dx.doi.org/10.1142/s0129065702001126.
Pełny tekst źródłaDey, Subhrajit, Rajdeep Bhattacharya, Friedhelm Schwenker i Ram Sarkar. "Median Filter Aided CNN Based Image Denoising: An Ensemble Approach". Algorithms 14, nr 4 (28.03.2021): 109. http://dx.doi.org/10.3390/a14040109.
Pełny tekst źródłaHu, Sile, Qiaosheng Zhang, Jing Wang i Zhe Chen. "Real-time particle filtering and smoothing algorithms for detecting abrupt changes in neural ensemble spike activity". Journal of Neurophysiology 119, nr 4 (1.04.2018): 1394–410. http://dx.doi.org/10.1152/jn.00684.2017.
Pełny tekst źródłaAhn, J., L. J. Kreeger, S. T. Lubejko, D. A. Butts i K. M. MacLeod. "Heterogeneity of intrinsic biophysical properties among cochlear nucleus neurons improves the population coding of temporal information". Journal of Neurophysiology 111, nr 11 (1.06.2014): 2320–31. http://dx.doi.org/10.1152/jn.00836.2013.
Pełny tekst źródłaAhn, Byeongyong, Gu Yong Park, Yoonsik Kim i Nam Ik Cho. "A Self-ensemble Approach for Noise and Compression Artifacts Removal using Convolutional Neural Network". IEIE Transactions on Smart Processing & Computing 7, nr 4 (31.08.2018): 296–304. http://dx.doi.org/10.5573/ieiespc.2018.7.4.296.
Pełny tekst źródłaWu, Jianfeng, Yongzhu Hua, Shengying Yang, Hongshuai Qin i Huibin Qin. "Speech Enhancement Using Generative Adversarial Network by Distilling Knowledge from Statistical Method". Applied Sciences 9, nr 16 (18.08.2019): 3396. http://dx.doi.org/10.3390/app9163396.
Pełny tekst źródłaMężyk, Miłosz, Michał Chamarczuk i Michał Malinowski. "Automatic Image-Based Event Detection for Large-N Seismic Arrays Using a Convolutional Neural Network". Remote Sensing 13, nr 3 (23.01.2021): 389. http://dx.doi.org/10.3390/rs13030389.
Pełny tekst źródłaMashhadi, Peyman Sheikholharam, Sławomir Nowaczyk i Sepideh Pashami. "Stacked Ensemble of Recurrent Neural Networks for Predicting Turbocharger Remaining Useful Life". Applied Sciences 10, nr 1 (20.12.2019): 69. http://dx.doi.org/10.3390/app10010069.
Pełny tekst źródłaRajaraman, Sivaramakrishnan, Sudhir Sornapudi, Philip O. Alderson, Les R. Folio i Sameer K. Antani. "Analyzing inter-reader variability affecting deep ensemble learning for COVID-19 detection in chest radiographs". PLOS ONE 15, nr 11 (12.11.2020): e0242301. http://dx.doi.org/10.1371/journal.pone.0242301.
Pełny tekst źródłaKwon, Jihoon, i Nojun Kwak. "Radar Application: Stacking Multiple Classifiers for Human Walking Detection Using Micro-Doppler Signals". Applied Sciences 9, nr 17 (28.08.2019): 3534. http://dx.doi.org/10.3390/app9173534.
Pełny tekst źródłaScheuerer, Michael, Matthew B. Switanek, Rochelle P. Worsnop i Thomas M. Hamill. "Using Artificial Neural Networks for Generating Probabilistic Subseasonal Precipitation Forecasts over California". Monthly Weather Review 148, nr 8 (31.07.2020): 3489–506. http://dx.doi.org/10.1175/mwr-d-20-0096.1.
Pełny tekst źródłaFallahian, Milad, Faramarz Khoshnoudian i Viviana Meruane. "Ensemble classification method for structural damage assessment under varying temperature". Structural Health Monitoring 17, nr 4 (7.07.2017): 747–62. http://dx.doi.org/10.1177/1475921717717311.
Pełny tekst źródłaHou, Sizu, i Wei Guo. "Faulty Line Selection Based on Modified CEEMDAN Optimal Denoising Smooth Model and Duffing Oscillator for Un-Effectively Grounded System". Mathematical Problems in Engineering 2020 (6.04.2020): 1–21. http://dx.doi.org/10.1155/2020/5761642.
Pełny tekst źródłaFishman, Yonatan I., i Mitchell Steinschneider. "Spectral Resolution of Monkey Primary Auditory Cortex (A1) Revealed With Two-Noise Masking". Journal of Neurophysiology 96, nr 3 (wrzesień 2006): 1105–15. http://dx.doi.org/10.1152/jn.00124.2006.
Pełny tekst źródłaKim, Sungil, Baehyun Min, Seoyoon Kwon i Min-gon Chu. "History Matching of a Channelized Reservoir Using a Serial Denoising Autoencoder Integrated with ES-MDA". Geofluids 2019 (16.04.2019): 1–22. http://dx.doi.org/10.1155/2019/3280961.
Pełny tekst źródłaTian, Juan, i Yingxiang Li. "Convolutional Neural Networks for Steganalysis via Transfer Learning". International Journal of Pattern Recognition and Artificial Intelligence 33, nr 02 (24.10.2018): 1959006. http://dx.doi.org/10.1142/s0218001419590067.
Pełny tekst źródłaJiang, Zhencun, Zhengxin Dong, Lingyang Wang i Wenping Jiang. "Method for Diagnosis of Acute Lymphoblastic Leukemia Based on ViT-CNN Ensemble Model". Computational Intelligence and Neuroscience 2021 (21.08.2021): 1–12. http://dx.doi.org/10.1155/2021/7529893.
Pełny tekst źródłaKnuth, Kevin H., Ankoor S. Shah, Wilson A. Truccolo, Mingzhou Ding, Steven L. Bressler i Charles E. Schroeder. "Differentially Variable Component Analysis: Identifying Multiple Evoked Components Using Trial-to-Trial Variability". Journal of Neurophysiology 95, nr 5 (maj 2006): 3257–76. http://dx.doi.org/10.1152/jn.00663.2005.
Pełny tekst źródłaMa, Jianpeng, Zhenghui Li, Chengwei Li, Liwei Zhan i Guang-Zhu Zhang. "Rolling Bearing Fault Diagnosis Based on Refined Composite Multi-Scale Approximate Entropy and Optimized Probabilistic Neural Network". Entropy 23, nr 2 (23.02.2021): 259. http://dx.doi.org/10.3390/e23020259.
Pełny tekst źródłaXie, Yingchun, Yucheng Xiao, Xuyan Liu, Guijie Liu, Weixiong Jiang i Jin Qin. "Time-Frequency Distribution Map-Based Convolutional Neural Network (CNN) Model for Underwater Pipeline Leakage Detection Using Acoustic Signals". Sensors 20, nr 18 (4.09.2020): 5040. http://dx.doi.org/10.3390/s20185040.
Pełny tekst źródłaAntoniades, Andreas, Loukianos Spyrou, David Martin-Lopez, Antonio Valentin, Gonzalo Alarcon, Saeid Sanei i Clive Cheong Took. "Deep Neural Architectures for Mapping Scalp to Intracranial EEG". International Journal of Neural Systems 28, nr 08 (26.08.2018): 1850009. http://dx.doi.org/10.1142/s0129065718500090.
Pełny tekst źródłaWang, Jing, Guigen Nie, Shengjun Gao, Shuguang Wu, Haiyang Li i Xiaobing Ren. "Landslide Deformation Prediction Based on a GNSS Time Series Analysis and Recurrent Neural Network Model". Remote Sensing 13, nr 6 (10.03.2021): 1055. http://dx.doi.org/10.3390/rs13061055.
Pełny tekst źródłaAltuve, Miguel, Paula Lizarazo i Javier Villamizar. "Human activity recognition using improved complete ensemble EMD with adaptive noise and long short-term memory neural networks". Biocybernetics and Biomedical Engineering 40, nr 3 (lipiec 2020): 901–9. http://dx.doi.org/10.1016/j.bbe.2020.04.007.
Pełny tekst źródłaCao, Yang, Xiaokang Zhou i Ke Yan. "Deep Learning Neural Network Model for Tunnel Ground Surface Settlement Prediction Based on Sensor Data". Mathematical Problems in Engineering 2021 (27.08.2021): 1–14. http://dx.doi.org/10.1155/2021/9488892.
Pełny tekst źródłaAkpudo, Ugochukwu Ejike, i Jang-Wook Hur. "A CEEMDAN-Assisted Deep Learning Model for the RUL Estimation of Solenoid Pumps". Electronics 10, nr 17 (25.08.2021): 2054. http://dx.doi.org/10.3390/electronics10172054.
Pełny tekst źródłaRudd, Michael E., i Lawrence G. Brown. "Noise Adaptation in Integrate-and-Fire Neurons". Neural Computation 9, nr 5 (1.07.1997): 1047–69. http://dx.doi.org/10.1162/neco.1997.9.5.1047.
Pełny tekst źródłaWu, Jiang, Feng Miu i Taiyong Li. "Daily Crude Oil Price Forecasting Based on Improved CEEMDAN, SCA, and RVFL: A Case Study in WTI Oil Market". Energies 13, nr 7 (10.04.2020): 1852. http://dx.doi.org/10.3390/en13071852.
Pełny tekst źródłaNti, Isaac Kofi, Adebayo Felix Adekoya i Benjamin Asubam Weyori. "Efficient Stock-Market Prediction Using Ensemble Support Vector Machine". Open Computer Science 10, nr 1 (4.07.2020): 153–63. http://dx.doi.org/10.1515/comp-2020-0199.
Pełny tekst źródłaMousavi, Asma Alsadat, Chunwei Zhang, Sami F. Masri i Gholamreza Gholipour. "Structural Damage Localization and Quantification Based on a CEEMDAN Hilbert Transform Neural Network Approach: A Model Steel Truss Bridge Case Study". Sensors 20, nr 5 (26.02.2020): 1271. http://dx.doi.org/10.3390/s20051271.
Pełny tekst źródłaGeorges, Hassana Maigary, Dong Wang i Zhu Xiao. "GNSS/Low-Cost MEMS-INS Integration Using Variational Bayesian Adaptive Cubature Kalman Smoother and Ensemble Regularized ELM". Mathematical Problems in Engineering 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/682907.
Pełny tekst źródłaWu, Jiang, Tengfei Zhou i Taiyong Li. "A Hybrid Approach Integrating Multiple ICEEMDANs, WOA, and RVFL Networks for Economic and Financial Time Series Forecasting". Complexity 2020 (22.10.2020): 1–17. http://dx.doi.org/10.1155/2020/9318308.
Pełny tekst źródłaKrasnopolsky, Vladimir, Sudhir Nadiga, Avichal Mehra, Eric Bayler i David Behringer. "Neural Networks Technique for Filling Gaps in Satellite Measurements: Application to Ocean Color Observations". Computational Intelligence and Neuroscience 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/6156513.
Pełny tekst źródłaOpitz, D., i R. Maclin. "Popular Ensemble Methods: An Empirical Study". Journal of Artificial Intelligence Research 11 (1.08.1999): 169–98. http://dx.doi.org/10.1613/jair.614.
Pełny tekst źródłaHan, Te, Dongxiang Jiang, Qi Zhao, Lei Wang i Kai Yin. "Comparison of random forest, artificial neural networks and support vector machine for intelligent diagnosis of rotating machinery". Transactions of the Institute of Measurement and Control 40, nr 8 (1.06.2017): 2681–93. http://dx.doi.org/10.1177/0142331217708242.
Pełny tekst źródłaSaghi, Faramarz, i Mustafa Jahangoshai Rezaee. "An ensemble approach based on transformation functions for natural gas price forecasting considering optimal time delays". PeerJ Computer Science 7 (7.04.2021): e409. http://dx.doi.org/10.7717/peerj-cs.409.
Pełny tekst źródłaSarmiento, Carlos, i Jesus Savage. "Comparison of Two Objects Classification Techniques using Hidden Markov Models and Convolutional Neural Networks". Informatics and Automation 19, nr 6 (11.12.2020): 1222–54. http://dx.doi.org/10.15622/ia.2020.19.6.4.
Pełny tekst źródłaDeweese, Michael R., i Anthony M. Zador. "Shared and Private Variability in the Auditory Cortex". Journal of Neurophysiology 92, nr 3 (wrzesień 2004): 1840–55. http://dx.doi.org/10.1152/jn.00197.2004.
Pełny tekst źródłaЖарикова, Е. П., Я. Ю. Григорьев i А. Л. Григорьева. "Application of neural networks for water area analysis". MORSKIE INTELLEKTUAL`NYE TEHNOLOGII), nr 2(52) (20.06.2021): 129–33. http://dx.doi.org/10.37220/mit.2021.52.2.063.
Pełny tekst źródłaRedlich, A. Norman. "Redundancy Reduction as a Strategy for Unsupervised Learning". Neural Computation 5, nr 2 (marzec 1993): 289–304. http://dx.doi.org/10.1162/neco.1993.5.2.289.
Pełny tekst źródła