Journal articles on the topic 'Supervised neural networks'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Supervised neural networks.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
Yeh, I.-Cheng, and Kuan-Cheng Lin. "Supervised Learning Probabilistic Neural Networks." Neural Processing Letters 34, no. 2 (July 22, 2011): 193–208. http://dx.doi.org/10.1007/s11063-011-9191-z.
Full textHush, D. R., and B. G. Horne. "Progress in supervised neural networks." IEEE Signal Processing Magazine 10, no. 1 (January 1993): 8–39. http://dx.doi.org/10.1109/79.180705.
Full textTomasov, Adrian, Martin Holik, Vaclav Oujezsky, Tomas Horvath, and Petr Munster. "GPON PLOAMd Message Analysis Using Supervised Neural Networks." Applied Sciences 10, no. 22 (November 18, 2020): 8139. http://dx.doi.org/10.3390/app10228139.
Full textHammer, Barbara. "Neural Smithing – Supervised Learning in Feedforward Artificial Neural Networks." Pattern Analysis & Applications 4, no. 1 (March 2001): 73–74. http://dx.doi.org/10.1007/s100440170029.
Full textSarukkai, Ramesh R. "Supervised Networks That Self-Organize Class Outputs." Neural Computation 9, no. 3 (March 1, 1997): 637–48. http://dx.doi.org/10.1162/neco.1997.9.3.637.
Full textDoyle, J. R. "Supervised learning in N-tuple neural networks." International Journal of Man-Machine Studies 33, no. 1 (July 1990): 21–40. http://dx.doi.org/10.1016/s0020-7373(05)80113-0.
Full textSecco, Jacopo, Mauro Poggio, and Fernando Corinto. "Supervised neural networks with memristor binary synapses." International Journal of Circuit Theory and Applications 46, no. 1 (January 2018): 221–33. http://dx.doi.org/10.1002/cta.2429.
Full textSporea, Ioana, and André Grüning. "Supervised Learning in Multilayer Spiking Neural Networks." Neural Computation 25, no. 2 (February 2013): 473–509. http://dx.doi.org/10.1162/neco_a_00396.
Full textWang, Juexin, Anjun Ma, Qin Ma, Dong Xu, and 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.
Full textXu, Jianqiao, Zhaolu Zuo, Danchao Wu, Bing Li, Xiaoni Li, and Deyi Kong. "Bearing Defect Detection with Unsupervised Neural Networks." Shock and Vibration 2021 (August 19, 2021): 1–11. http://dx.doi.org/10.1155/2021/9544809.
Full textZhao, Shijie, Yan Cui, Linwei Huang, Li Xie, Yaowu Chen, Junwei Han, Lei Guo, Shu Zhang, Tianming Liu, and 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.
Full textTan, Junyang, Dan Xia, Shiyun Dong, Honghao Zhu, and 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, no. 5 (July 20, 2021): 1–15. http://dx.doi.org/10.1145/3433539.
Full textNobukawa, Sou, Haruhiko Nishimura, and 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, no. 4 (October 1, 2019): 283–91. http://dx.doi.org/10.2478/jaiscr-2019-0009.
Full textBELATRECHE, AMMAR, LIAM P. MAGUIRE, MARTIN MCGINNITY, and QING XIANG WU. "EVOLUTIONARY DESIGN OF SPIKING NEURAL NETWORKS." New Mathematics and Natural Computation 02, no. 03 (November 2006): 237–53. http://dx.doi.org/10.1142/s179300570600049x.
Full textZenke, Friedemann, and Surya Ganguli. "SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks." Neural Computation 30, no. 6 (June 2018): 1514–41. http://dx.doi.org/10.1162/neco_a_01086.
Full textWettayaprasit, W., C. Lursinsap, and C. H. Chu. "Extracting linguistic quantitative rules from supervised neural networks." International Journal of Knowledge-based and Intelligent Engineering Systems 8, no. 3 (January 10, 2005): 161–70. http://dx.doi.org/10.3233/kes-2004-8304.
Full textSong, Xingguo, Haibo Gao, Liang Ding, Pol D. Spanos, Zongquan Deng, and Zhijun Li. "Locally supervised neural networks for approximating terramechanics models." Mechanical Systems and Signal Processing 75 (June 2016): 57–74. http://dx.doi.org/10.1016/j.ymssp.2015.12.028.
Full textAlshehhi, Rasha, Chris S. Hanson, Laurent Gizon, and Shravan Hanasoge. "Supervised neural networks for helioseismic ring-diagram inversions." Astronomy & Astrophysics 622 (February 2019): A124. http://dx.doi.org/10.1051/0004-6361/201834237.
Full textCheung, Man-Fung, Kevin M. Passino, and Stephen Yurkovich. "Supervised Training of Neural Networks via Ellipsoid Algorithms." Neural Computation 6, no. 4 (July 1994): 748–60. http://dx.doi.org/10.1162/neco.1994.6.4.748.
Full textSperduti, A., and A. Starita. "Supervised neural networks for the classification of structures." IEEE Transactions on Neural Networks 8, no. 3 (May 1997): 714–35. http://dx.doi.org/10.1109/72.572108.
Full textMazzatorta, Paolo, Marjan Vračko, Aneta Jezierska, and Emilio Benfenati. "Modeling Toxicity by Using Supervised Kohonen Neural Networks." Journal of Chemical Information and Computer Sciences 43, no. 2 (March 2003): 485–92. http://dx.doi.org/10.1021/ci0256182.
Full textGazula, S., and M. R. Kabuka. "Design of supervised classifiers using Boolean neural networks." IEEE Transactions on Pattern Analysis and Machine Intelligence 17, no. 12 (1995): 1239–46. http://dx.doi.org/10.1109/34.476519.
Full textSmith, Alice E., and Cihan H. Dagli. "Controlling industrial processes through supervised, feedforward neural networks." Computers & Industrial Engineering 21, no. 1-4 (January 1991): 247–51. http://dx.doi.org/10.1016/0360-8352(91)90096-o.
Full textHu, Yaxian, Senlin Luo, Longfei Han, Limin Pan, and Tiemei Zhang. "Deep supervised learning with mixture of neural networks." Artificial Intelligence in Medicine 102 (January 2020): 101764. http://dx.doi.org/10.1016/j.artmed.2019.101764.
Full textQin, Shanshan, Nayantara Mudur, and Cengiz Pehlevan. "Contrastive Similarity Matching for Supervised Learning." Neural Computation 33, no. 5 (April 13, 2021): 1300–1328. http://dx.doi.org/10.1162/neco_a_01374.
Full textWu, Wei, Guangmin Hu, and Fucai Yu. "Ricci Curvature-Based Semi-Supervised Learning on an Attributed Network." Entropy 23, no. 3 (February 27, 2021): 292. http://dx.doi.org/10.3390/e23030292.
Full textKulathunga, Nalinda, Nishath Rajiv Ranasinghe, Daniel Vrinceanu, Zackary Kinsman, Lei Huang, and Yunjiao Wang. "Effects of Nonlinearity and Network Architecture on the Performance of Supervised Neural Networks." Algorithms 14, no. 2 (February 5, 2021): 51. http://dx.doi.org/10.3390/a14020051.
Full textMAGOULAS, GEORGE D., and MICHAEL N. VRAHATIS. "ADAPTIVE ALGORITHMS FOR NEURAL NETWORK SUPERVISED LEARNING: A DETERMINISTIC OPTIMIZATION APPROACH." International Journal of Bifurcation and Chaos 16, no. 07 (July 2006): 1929–50. http://dx.doi.org/10.1142/s0218127406015805.
Full textShin, Sungho, Jongwon Kim, Yeonguk Yu, Seongju Lee, and Kyoobin Lee. "Self-Supervised Transfer Learning from Natural Images for Sound Classification." Applied Sciences 11, no. 7 (March 29, 2021): 3043. http://dx.doi.org/10.3390/app11073043.
Full textAragon-Calvo, M. A., and J. C. Carvajal. "Self-supervised learning with physics-aware neural networks – I. Galaxy model fitting." Monthly Notices of the Royal Astronomical Society 498, no. 3 (September 7, 2020): 3713–19. http://dx.doi.org/10.1093/mnras/staa2228.
Full textTang, Zheng, Xu Gang Wang, Hiroki Tamura, and Masahiro Ishii. "An Algorithm of Supervised Learning for Multilayer Neural Networks." Neural Computation 15, no. 5 (May 1, 2003): 1125–42. http://dx.doi.org/10.1162/089976603765202686.
Full textZhang, Pengfei, and Xiaoming Ju. "Adversarial Sample Detection with Gaussian Mixture Conditional Generative Adversarial Networks." Mathematical Problems in Engineering 2021 (September 13, 2021): 1–18. http://dx.doi.org/10.1155/2021/8268249.
Full textOrukwo, Joy Oyinye, and Ledisi Giok Kabari. "Diagnosing Diabetes Using Artificial Neural Networks." European Journal of Engineering Research and Science 5, no. 2 (February 27, 2020): 221–24. http://dx.doi.org/10.24018/ejers.2020.5.2.1774.
Full textDapkus, Paulius, Liudas Mažeika, and 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, no. 3 (September 23, 2020): 381–94. http://dx.doi.org/10.5755/j01.itc.49.3.26792.
Full textHodges, Jaret, and Soumya Mohan. "Machine Learning in Gifted Education: A Demonstration Using Neural Networks." Gifted Child Quarterly 63, no. 4 (September 9, 2019): 243–52. http://dx.doi.org/10.1177/0016986219867483.
Full textZhang, Yingxue, Soumyasundar Pal, Mark Coates, and Deniz Ustebay. "Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5829–36. http://dx.doi.org/10.1609/aaai.v33i01.33015829.
Full textBen Boubaker, Ourida. "APPLYING NEURAL NETWORKS FOR SUPERVISED LEARNING OF MEDICAL DATA." International Journal of Data Mining & Knowledge Management Process 09, no. 03 (May 31, 2019): 29–38. http://dx.doi.org/10.5121/ijdkp.2019.9303.
Full textHu, Yipeng, Marc Modat, Eli Gibson, Wenqi Li, Nooshin Ghavami, Ester Bonmati, Guotai Wang, et al. "Weakly-supervised convolutional neural networks for multimodal image registration." Medical Image Analysis 49 (October 2018): 1–13. http://dx.doi.org/10.1016/j.media.2018.07.002.
Full textZhang, Malu, Hong Qu, Xiurui Xie, and Jürgen Kurths. "Supervised learning in spiking neural networks with noise-threshold." Neurocomputing 219 (January 2017): 333–49. http://dx.doi.org/10.1016/j.neucom.2016.09.044.
Full textDing, Zhengming, Nasser M. Nasrabadi, and Yun Fu. "Semi-supervised Deep Domain Adaptation via Coupled Neural Networks." IEEE Transactions on Image Processing 27, no. 11 (November 2018): 5214–24. http://dx.doi.org/10.1109/tip.2018.2851067.
Full textGyer, M. S. "Adjuncts and alternatives to neural networks for supervised classification." IEEE Transactions on Systems, Man, and Cybernetics 22, no. 1 (1992): 35–46. http://dx.doi.org/10.1109/21.141309.
Full textČerná, Lenka, and Milan Chytrý. "Supervised classification of plant communities with artificial neural networks." Journal of Vegetation Science 16, no. 4 (February 24, 2005): 407–14. http://dx.doi.org/10.1111/j.1654-1103.2005.tb02380.x.
Full textAmorim, Willian Paraguassu, Gustavo Henrique Rosa, Rogério Thomazella, José Eduardo Cogo Castanho, Fábio Romano Lofrano Dotto, Oswaldo Pons Rodrigues Júnior, Aparecido Nilceu Marana, and João Paulo Papa. "Semi-supervised learning with connectivity-driven convolutional neural networks." Pattern Recognition Letters 128 (December 2019): 16–22. http://dx.doi.org/10.1016/j.patrec.2019.08.012.
Full textLudwig, Oswaldo, and Urbano Nunes. "Novel Maximum-Margin Training Algorithms for Supervised Neural Networks." IEEE Transactions on Neural Networks 21, no. 6 (June 2010): 972–84. http://dx.doi.org/10.1109/tnn.2010.2046423.
Full textLópez-Vázquez, G., M. Ornelas-Rodriguez, A. Espinal, J. A. Soria-Alcaraz, A. Rojas-Domínguez, H. J. Puga-Soberanes, J. M. Carpio, and H. Rostro-Gonzalez. "Evolutionary Spiking Neural Networks for Solving Supervised Classification Problems." Computational Intelligence and Neuroscience 2019 (March 28, 2019): 1–13. http://dx.doi.org/10.1155/2019/4182639.
Full textkeyan, M. Karthi. "Semi Supervised Document Classification Model Using Artificial Neural Networks." International Journal of Computer Trends and Technology 34, no. 1 (April 25, 2016): 52–58. http://dx.doi.org/10.14445/22312803/ijctt-v34p109.
Full textTang, Rongxin, Hualin Liu, Jingbo Wei, and Wenchao Tang. "Supervised learning with convolutional neural networks for hyperspectral visualization." Remote Sensing Letters 11, no. 4 (February 6, 2020): 363–72. http://dx.doi.org/10.1080/2150704x.2020.1717014.
Full textBruzzone, L., and D. Fernández Prieto. "Supervised training technique for radial basis function neural networks." Electronics Letters 34, no. 11 (1998): 1115. http://dx.doi.org/10.1049/el:19980789.
Full textPolikar, R., L. Upda, S. S. Upda, and V. Honavar. "Learn++: an incremental learning algorithm for supervised neural networks." IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 31, no. 4 (2001): 497–508. http://dx.doi.org/10.1109/5326.983933.
Full textJain, Lakhmi C., Manjeevan Seera, Chee Peng Lim, and P. Balasubramaniam. "A review of online learning in supervised neural networks." Neural Computing and Applications 25, no. 3-4 (December 31, 2013): 491–509. http://dx.doi.org/10.1007/s00521-013-1534-4.
Full text