Artykuły w czasopismach na temat „Supervised neural networks”
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Yeh, I.-Cheng, i Kuan-Cheng Lin. "Supervised Learning Probabilistic Neural Networks". Neural Processing Letters 34, nr 2 (22.07.2011): 193–208. http://dx.doi.org/10.1007/s11063-011-9191-z.
Pełny tekst źródłaHush, D. R., i B. G. Horne. "Progress in supervised neural networks". IEEE Signal Processing Magazine 10, nr 1 (styczeń 1993): 8–39. http://dx.doi.org/10.1109/79.180705.
Pełny tekst źródłaTomasov, Adrian, Martin Holik, Vaclav Oujezsky, Tomas Horvath i Petr Munster. "GPON PLOAMd Message Analysis Using Supervised Neural Networks". Applied Sciences 10, nr 22 (18.11.2020): 8139. http://dx.doi.org/10.3390/app10228139.
Pełny tekst źródłaHammer, Barbara. "Neural Smithing – Supervised Learning in Feedforward Artificial Neural Networks". Pattern Analysis & Applications 4, nr 1 (marzec 2001): 73–74. http://dx.doi.org/10.1007/s100440170029.
Pełny tekst źródłaSarukkai, Ramesh R. "Supervised Networks That Self-Organize Class Outputs". Neural Computation 9, nr 3 (1.03.1997): 637–48. http://dx.doi.org/10.1162/neco.1997.9.3.637.
Pełny tekst źródłaDoyle, J. R. "Supervised learning in N-tuple neural networks". International Journal of Man-Machine Studies 33, nr 1 (lipiec 1990): 21–40. http://dx.doi.org/10.1016/s0020-7373(05)80113-0.
Pełny tekst źródłaSecco, Jacopo, Mauro Poggio i Fernando Corinto. "Supervised neural networks with memristor binary synapses". International Journal of Circuit Theory and Applications 46, nr 1 (styczeń 2018): 221–33. http://dx.doi.org/10.1002/cta.2429.
Pełny tekst źródłaSporea, Ioana, i André Grüning. "Supervised Learning in Multilayer Spiking Neural Networks". Neural Computation 25, nr 2 (luty 2013): 473–509. http://dx.doi.org/10.1162/neco_a_00396.
Pełny tekst źródłaWang, Juexin, Anjun Ma, Qin Ma, Dong Xu i Trupti Joshi. "Inductive inference of gene regulatory network using supervised and semi-supervised graph neural networks". Computational and Structural Biotechnology Journal 18 (2020): 3335–43. http://dx.doi.org/10.1016/j.csbj.2020.10.022.
Pełny tekst źródłaXu, Jianqiao, Zhaolu Zuo, Danchao Wu, Bing Li, Xiaoni Li i Deyi Kong. "Bearing Defect Detection with Unsupervised Neural Networks". Shock and Vibration 2021 (19.08.2021): 1–11. http://dx.doi.org/10.1155/2021/9544809.
Pełny tekst źródłaZhao, Shijie, Yan Cui, Linwei Huang, Li Xie, Yaowu Chen, Junwei Han, Lei Guo, Shu Zhang, Tianming Liu i Jinglei Lv. "Supervised Brain Network Learning Based on Deep Recurrent Neural Networks". IEEE Access 8 (2020): 69967–78. http://dx.doi.org/10.1109/access.2020.2984948.
Pełny tekst źródłaTan, Junyang, Dan Xia, Shiyun Dong, Honghao Zhu i Binshi Xu. "Research On Pre-Training Method and Generalization Ability of Big Data Recognition Model of the Internet of Things". ACM Transactions on Asian and Low-Resource Language Information Processing 20, nr 5 (20.07.2021): 1–15. http://dx.doi.org/10.1145/3433539.
Pełny tekst źródłaNobukawa, Sou, Haruhiko Nishimura i Teruya Yamanishi. "Pattern Classification by Spiking Neural Networks Combining Self-Organized and Reward-Related Spike-Timing-Dependent Plasticity". Journal of Artificial Intelligence and Soft Computing Research 9, nr 4 (1.10.2019): 283–91. http://dx.doi.org/10.2478/jaiscr-2019-0009.
Pełny tekst źródłaBELATRECHE, AMMAR, LIAM P. MAGUIRE, MARTIN MCGINNITY i QING XIANG WU. "EVOLUTIONARY DESIGN OF SPIKING NEURAL NETWORKS". New Mathematics and Natural Computation 02, nr 03 (listopad 2006): 237–53. http://dx.doi.org/10.1142/s179300570600049x.
Pełny tekst źródłaZenke, Friedemann, i Surya Ganguli. "SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks". Neural Computation 30, nr 6 (czerwiec 2018): 1514–41. http://dx.doi.org/10.1162/neco_a_01086.
Pełny tekst źródłaWettayaprasit, W., C. Lursinsap i C. H. Chu. "Extracting linguistic quantitative rules from supervised neural networks". International Journal of Knowledge-based and Intelligent Engineering Systems 8, nr 3 (10.01.2005): 161–70. http://dx.doi.org/10.3233/kes-2004-8304.
Pełny tekst źródłaSong, Xingguo, Haibo Gao, Liang Ding, Pol D. Spanos, Zongquan Deng i Zhijun Li. "Locally supervised neural networks for approximating terramechanics models". Mechanical Systems and Signal Processing 75 (czerwiec 2016): 57–74. http://dx.doi.org/10.1016/j.ymssp.2015.12.028.
Pełny tekst źródłaAlshehhi, Rasha, Chris S. Hanson, Laurent Gizon i Shravan Hanasoge. "Supervised neural networks for helioseismic ring-diagram inversions". Astronomy & Astrophysics 622 (luty 2019): A124. http://dx.doi.org/10.1051/0004-6361/201834237.
Pełny tekst źródłaCheung, Man-Fung, Kevin M. Passino i Stephen Yurkovich. "Supervised Training of Neural Networks via Ellipsoid Algorithms". Neural Computation 6, nr 4 (lipiec 1994): 748–60. http://dx.doi.org/10.1162/neco.1994.6.4.748.
Pełny tekst źródłaSperduti, A., i A. Starita. "Supervised neural networks for the classification of structures". IEEE Transactions on Neural Networks 8, nr 3 (maj 1997): 714–35. http://dx.doi.org/10.1109/72.572108.
Pełny tekst źródłaMazzatorta, Paolo, Marjan Vračko, Aneta Jezierska i Emilio Benfenati. "Modeling Toxicity by Using Supervised Kohonen Neural Networks". Journal of Chemical Information and Computer Sciences 43, nr 2 (marzec 2003): 485–92. http://dx.doi.org/10.1021/ci0256182.
Pełny tekst źródłaGazula, S., i M. R. Kabuka. "Design of supervised classifiers using Boolean neural networks". IEEE Transactions on Pattern Analysis and Machine Intelligence 17, nr 12 (1995): 1239–46. http://dx.doi.org/10.1109/34.476519.
Pełny tekst źródłaSmith, Alice E., i Cihan H. Dagli. "Controlling industrial processes through supervised, feedforward neural networks". Computers & Industrial Engineering 21, nr 1-4 (styczeń 1991): 247–51. http://dx.doi.org/10.1016/0360-8352(91)90096-o.
Pełny tekst źródłaHu, Yaxian, Senlin Luo, Longfei Han, Limin Pan i Tiemei Zhang. "Deep supervised learning with mixture of neural networks". Artificial Intelligence in Medicine 102 (styczeń 2020): 101764. http://dx.doi.org/10.1016/j.artmed.2019.101764.
Pełny tekst źródłaQin, Shanshan, Nayantara Mudur i Cengiz Pehlevan. "Contrastive Similarity Matching for Supervised Learning". Neural Computation 33, nr 5 (13.04.2021): 1300–1328. http://dx.doi.org/10.1162/neco_a_01374.
Pełny tekst źródłaWu, Wei, Guangmin Hu i Fucai Yu. "Ricci Curvature-Based Semi-Supervised Learning on an Attributed Network". Entropy 23, nr 3 (27.02.2021): 292. http://dx.doi.org/10.3390/e23030292.
Pełny tekst źródłaKulathunga, Nalinda, Nishath Rajiv Ranasinghe, Daniel Vrinceanu, Zackary Kinsman, Lei Huang i Yunjiao Wang. "Effects of Nonlinearity and Network Architecture on the Performance of Supervised Neural Networks". Algorithms 14, nr 2 (5.02.2021): 51. http://dx.doi.org/10.3390/a14020051.
Pełny tekst źródłaMAGOULAS, GEORGE D., i MICHAEL N. VRAHATIS. "ADAPTIVE ALGORITHMS FOR NEURAL NETWORK SUPERVISED LEARNING: A DETERMINISTIC OPTIMIZATION APPROACH". International Journal of Bifurcation and Chaos 16, nr 07 (lipiec 2006): 1929–50. http://dx.doi.org/10.1142/s0218127406015805.
Pełny tekst źródłaShin, Sungho, Jongwon Kim, Yeonguk Yu, Seongju Lee i Kyoobin Lee. "Self-Supervised Transfer Learning from Natural Images for Sound Classification". Applied Sciences 11, nr 7 (29.03.2021): 3043. http://dx.doi.org/10.3390/app11073043.
Pełny tekst źródłaAragon-Calvo, M. A., i J. C. Carvajal. "Self-supervised learning with physics-aware neural networks – I. Galaxy model fitting". Monthly Notices of the Royal Astronomical Society 498, nr 3 (7.09.2020): 3713–19. http://dx.doi.org/10.1093/mnras/staa2228.
Pełny tekst źródłaTang, Zheng, Xu Gang Wang, Hiroki Tamura i Masahiro Ishii. "An Algorithm of Supervised Learning for Multilayer Neural Networks". Neural Computation 15, nr 5 (1.05.2003): 1125–42. http://dx.doi.org/10.1162/089976603765202686.
Pełny tekst źródłaZhang, Pengfei, i Xiaoming Ju. "Adversarial Sample Detection with Gaussian Mixture Conditional Generative Adversarial Networks". Mathematical Problems in Engineering 2021 (13.09.2021): 1–18. http://dx.doi.org/10.1155/2021/8268249.
Pełny tekst źródłaOrukwo, Joy Oyinye, i Ledisi Giok Kabari. "Diagnosing Diabetes Using Artificial Neural Networks". European Journal of Engineering Research and Science 5, nr 2 (27.02.2020): 221–24. http://dx.doi.org/10.24018/ejers.2020.5.2.1774.
Pełny tekst źródłaDapkus, Paulius, Liudas Mažeika i Vytautas Sliesoraitis. "A study of supervised combined neural-network-based ultrasonic method for reconstruction of spatial distribution of material properties". Information Technology And Control 49, nr 3 (23.09.2020): 381–94. http://dx.doi.org/10.5755/j01.itc.49.3.26792.
Pełny tekst źródłaHodges, Jaret, i Soumya Mohan. "Machine Learning in Gifted Education: A Demonstration Using Neural Networks". Gifted Child Quarterly 63, nr 4 (9.09.2019): 243–52. http://dx.doi.org/10.1177/0016986219867483.
Pełny tekst źródłaZhang, Yingxue, Soumyasundar Pal, Mark Coates i Deniz Ustebay. "Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17.07.2019): 5829–36. http://dx.doi.org/10.1609/aaai.v33i01.33015829.
Pełny tekst źródłaBen Boubaker, Ourida. "APPLYING NEURAL NETWORKS FOR SUPERVISED LEARNING OF MEDICAL DATA". International Journal of Data Mining & Knowledge Management Process 09, nr 03 (31.05.2019): 29–38. http://dx.doi.org/10.5121/ijdkp.2019.9303.
Pełny tekst źródłaHu, Yipeng, Marc Modat, Eli Gibson, Wenqi Li, Nooshin Ghavami, Ester Bonmati, Guotai Wang i in. "Weakly-supervised convolutional neural networks for multimodal image registration". Medical Image Analysis 49 (październik 2018): 1–13. http://dx.doi.org/10.1016/j.media.2018.07.002.
Pełny tekst źródłaZhang, Malu, Hong Qu, Xiurui Xie i Jürgen Kurths. "Supervised learning in spiking neural networks with noise-threshold". Neurocomputing 219 (styczeń 2017): 333–49. http://dx.doi.org/10.1016/j.neucom.2016.09.044.
Pełny tekst źródłaDing, Zhengming, Nasser M. Nasrabadi i Yun Fu. "Semi-supervised Deep Domain Adaptation via Coupled Neural Networks". IEEE Transactions on Image Processing 27, nr 11 (listopad 2018): 5214–24. http://dx.doi.org/10.1109/tip.2018.2851067.
Pełny tekst źródłaGyer, M. S. "Adjuncts and alternatives to neural networks for supervised classification". IEEE Transactions on Systems, Man, and Cybernetics 22, nr 1 (1992): 35–46. http://dx.doi.org/10.1109/21.141309.
Pełny tekst źródłaČerná, Lenka, i Milan Chytrý. "Supervised classification of plant communities with artificial neural networks". Journal of Vegetation Science 16, nr 4 (24.02.2005): 407–14. http://dx.doi.org/10.1111/j.1654-1103.2005.tb02380.x.
Pełny tekst źródłaAmorim, Willian Paraguassu, Gustavo Henrique Rosa, Rogério Thomazella, José Eduardo Cogo Castanho, Fábio Romano Lofrano Dotto, Oswaldo Pons Rodrigues Júnior, Aparecido Nilceu Marana i João Paulo Papa. "Semi-supervised learning with connectivity-driven convolutional neural networks". Pattern Recognition Letters 128 (grudzień 2019): 16–22. http://dx.doi.org/10.1016/j.patrec.2019.08.012.
Pełny tekst źródłaLudwig, Oswaldo, i Urbano Nunes. "Novel Maximum-Margin Training Algorithms for Supervised Neural Networks". IEEE Transactions on Neural Networks 21, nr 6 (czerwiec 2010): 972–84. http://dx.doi.org/10.1109/tnn.2010.2046423.
Pełny tekst źródłaLópez-Vázquez, G., M. Ornelas-Rodriguez, A. Espinal, J. A. Soria-Alcaraz, A. Rojas-Domínguez, H. J. Puga-Soberanes, J. M. Carpio i H. Rostro-Gonzalez. "Evolutionary Spiking Neural Networks for Solving Supervised Classification Problems". Computational Intelligence and Neuroscience 2019 (28.03.2019): 1–13. http://dx.doi.org/10.1155/2019/4182639.
Pełny tekst źródłakeyan, M. Karthi. "Semi Supervised Document Classification Model Using Artificial Neural Networks". International Journal of Computer Trends and Technology 34, nr 1 (25.04.2016): 52–58. http://dx.doi.org/10.14445/22312803/ijctt-v34p109.
Pełny tekst źródłaTang, Rongxin, Hualin Liu, Jingbo Wei i Wenchao Tang. "Supervised learning with convolutional neural networks for hyperspectral visualization". Remote Sensing Letters 11, nr 4 (6.02.2020): 363–72. http://dx.doi.org/10.1080/2150704x.2020.1717014.
Pełny tekst źródłaBruzzone, L., i D. Fernández Prieto. "Supervised training technique for radial basis function neural networks". Electronics Letters 34, nr 11 (1998): 1115. http://dx.doi.org/10.1049/el:19980789.
Pełny tekst źródłaPolikar, R., L. Upda, S. S. Upda i V. Honavar. "Learn++: an incremental learning algorithm for supervised neural networks". IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 31, nr 4 (2001): 497–508. http://dx.doi.org/10.1109/5326.983933.
Pełny tekst źródłaJain, Lakhmi C., Manjeevan Seera, Chee Peng Lim i P. Balasubramaniam. "A review of online learning in supervised neural networks". Neural Computing and Applications 25, nr 3-4 (31.12.2013): 491–509. http://dx.doi.org/10.1007/s00521-013-1534-4.
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