Artículos de revistas sobre el tema "Neural network subspace"
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Oja, Erkki. "NEURAL NETWORKS, PRINCIPAL COMPONENTS, AND SUBSPACES". International Journal of Neural Systems 01, n.º 01 (enero de 1989): 61–68. http://dx.doi.org/10.1142/s0129065789000475.
Texto completoEdraki, Marzieh, Nazanin Rahnavard y Mubarak Shah. "SubSpace Capsule Network". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 07 (3 de abril de 2020): 10745–53. http://dx.doi.org/10.1609/aaai.v34i07.6703.
Texto completoZhi, Chuan, Ling Hua Guo, Mei Yun Zhang y Yi Shi. "Research on Dynamic Subspace Divided BP Neural Network Identification Method of Color Space Transform Model". Advanced Materials Research 174 (diciembre de 2010): 97–100. http://dx.doi.org/10.4028/www.scientific.net/amr.174.97.
Texto completoFunabashi, Masatoshi. "Synthetic Modeling of Autonomous Learning with a Chaotic Neural Network". International Journal of Bifurcation and Chaos 25, n.º 04 (abril de 2015): 1550054. http://dx.doi.org/10.1142/s0218127415500546.
Texto completoMahomud, V. A., A. S. Hadi, N. K. Wafi y S. M. R. Taha. "DIRECTION OF ARRIVAL USING PCA NEURALNETWORKS". Journal of Engineering 10, n.º 1 (13 de marzo de 2024): 83–89. http://dx.doi.org/10.31026/j.eng.2004.01.07.
Texto completoMenghi, Nicholas, Kemal Kacar y Will Penny. "Multitask learning over shared subspaces". PLOS Computational Biology 17, n.º 7 (6 de julio de 2021): e1009092. http://dx.doi.org/10.1371/journal.pcbi.1009092.
Texto completoCao, Xiang y A.-long Yu. "Multi-AUV Cooperative Target Search Algorithm in 3-D Underwater Workspace". Journal of Navigation 70, n.º 6 (30 de junio de 2017): 1293–311. http://dx.doi.org/10.1017/s0373463317000376.
Texto completoLaaksonen, Jorma y Erkki Oja. "Learning Subspace Classifiers and Error-Corrective Feature Extraction". International Journal of Pattern Recognition and Artificial Intelligence 12, n.º 04 (junio de 1998): 423–36. http://dx.doi.org/10.1142/s0218001498000270.
Texto completoChandar, Sarath, Mitesh M. Khapra, Hugo Larochelle y Balaraman Ravindran. "Correlational Neural Networks". Neural Computation 28, n.º 2 (febrero de 2016): 257–85. http://dx.doi.org/10.1162/neco_a_00801.
Texto completoKizaric, Ben y Daniel Pimentel-Alarcón. "Principle Component Trees and Their Persistent Homology". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 12 (24 de marzo de 2024): 13220–29. http://dx.doi.org/10.1609/aaai.v38i12.29222.
Texto completoLing, Junyao. "Score Prediction of Sports Events Based on Parallel Self-Organizing Nonlinear Neural Network". Computational Intelligence and Neuroscience 2022 (15 de enero de 2022): 1–10. http://dx.doi.org/10.1155/2022/4882309.
Texto completoPehlevan, Cengiz, Tao Hu y Dmitri B. Chklovskii. "A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data". Neural Computation 27, n.º 7 (julio de 2015): 1461–95. http://dx.doi.org/10.1162/neco_a_00745.
Texto completoTituaña, Luis y Yunjun Xu. "Subspace Structured Neural Network for Rapid Trajectory Optimization". IFAC-PapersOnLine 56, n.º 3 (2023): 37–42. http://dx.doi.org/10.1016/j.ifacol.2023.11.007.
Texto completoChuan, Zhi, Zhou Shi-Sheng y Shi Yi. "The Research on Color Space Transfer Model Based on Dynamic Subspace Divided BP Neural Network". International Journal of Engineering and Technology 2, n.º 5 (2010): 447–52. http://dx.doi.org/10.7763/ijet.2010.v2.163.
Texto completoKohonen, T. "The Self-Organising Map, a Possible Model of Brain Maps". Perception 26, n.º 1_suppl (agosto de 1997): 204. http://dx.doi.org/10.1068/v970002.
Texto completoXu, Lei, Adam Krzyzak y Erkki Oja. "NEURAL NETS FOR DUAL SUBSPACE PATTERN RECOGNITION METHOD". International Journal of Neural Systems 02, n.º 03 (enero de 1991): 169–84. http://dx.doi.org/10.1142/s0129065791000169.
Texto completoTran, Tich Phuoc, Thi Thanh Sang Nguyen, Poshiang Tsai y Xiaoying Kong. "BSPNN: boosted subspace probabilistic neural network for email security". Artificial Intelligence Review 35, n.º 4 (1 de enero de 2011): 369–82. http://dx.doi.org/10.1007/s10462-010-9198-2.
Texto completoLIU, ZHI-QIANG. "ADAPTIVE SUBSPACE SELF-ORGANIZING MAP AND ITS APPLICATIONS IN FACE RECOGNITION". International Journal of Image and Graphics 02, n.º 04 (octubre de 2002): 519–40. http://dx.doi.org/10.1142/s0219467802000834.
Texto completoWang, Pin, Shanshan Lv, Yongming Li, Qi Song, Linyu Li, Jiaxin Wang y Hehua Zhang. "Hybrid Deep Transfer Network and Rotational Sample Subspace Ensemble Learning for Early Cancer Detection". Journal of Medical Imaging and Health Informatics 10, n.º 10 (1 de octubre de 2020): 2289–96. http://dx.doi.org/10.1166/jmihi.2020.3172.
Texto completoWang, Pin, Shanshan Lv, Yongming Li, Qi Song, Linyu Li, Jiaxin Wang y Hehua Zhang. "Hybrid Deep Transfer Network and Rotational Sample Subspace Ensemble Learning for Early Cancer Detection". Journal of Medical Imaging and Health Informatics 10, n.º 10 (1 de octubre de 2020): 2289–96. http://dx.doi.org/10.1166/jmihi.2020.31722289.
Texto completoLi, Tai-fu, Wei Jia, Wei Zhou, Ji-ke Ge, Yu-cheng Liu y Li-zhong Yao. "Incomplete Phase Space Reconstruction Method Based on Subspace Adaptive Evolution Approximation". Journal of Applied Mathematics 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/983051.
Texto completoWU, JING, HONG YAN y ANDREW CHALMERS. "HANDWRITTEN DIGIT RECOGNITION USING TWO-LAYER SELF-ORGANIZING MAPS". International Journal of Neural Systems 05, n.º 04 (diciembre de 1994): 357–62. http://dx.doi.org/10.1142/s0129065794000347.
Texto completoLi, Jiamu, Ji Zhang, Mohamed Jaward Bah, Jian Wang, Youwen Zhu, Gaoming Yang, Lingling Li y Kexin Zhang. "An Auto-Encoder with Genetic Algorithm for High Dimensional Data: Towards Accurate and Interpretable Outlier Detection". Algorithms 15, n.º 11 (15 de noviembre de 2022): 429. http://dx.doi.org/10.3390/a15110429.
Texto completoZhang, Long, Nana Wang, Jieli Wei y Zhuyin Ren. "Exploring active subspace for neural network prediction of oscillating combustion". Combustion Theory and Modelling 25, n.º 3 (16 de abril de 2021): 570–87. http://dx.doi.org/10.1080/13647830.2021.1915500.
Texto completoPrakash, M. y M. N. Murty. "Growing subspace pattern recognition methods and their neural-network models". IEEE Transactions on Neural Networks 8, n.º 1 (enero de 1997): 161–68. http://dx.doi.org/10.1109/72.554201.
Texto completoWen Yao, Xiaoqian Chen, Yong Zhao y M. van Tooren. "Concurrent Subspace Width Optimization Method for RBF Neural Network Modeling". IEEE Transactions on Neural Networks and Learning Systems 23, n.º 2 (febrero de 2012): 247–59. http://dx.doi.org/10.1109/tnnls.2011.2178560.
Texto completoJANKOVIC, MARKO y HIDEMITSU OGAWA. "TIME-ORIENTED HIERARCHICAL METHOD FOR COMPUTATION OF PRINCIPAL COMPONENTS USING SUBSPACE LEARNING ALGORITHM". International Journal of Neural Systems 14, n.º 05 (octubre de 2004): 313–23. http://dx.doi.org/10.1142/s0129065704002091.
Texto completoNong, Ji Fu. "A Principal Components Analysis Self-Organizing Neural Network Model and Computational Experiment". Advanced Materials Research 756-759 (septiembre de 2013): 3330–35. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.3330.
Texto completoLiu, Hongxia. "Design of Neural Network Model for Cross-Media Audio and Video Score Recognition Based on Convolutional Neural Network Model". Computational Intelligence and Neuroscience 2022 (13 de junio de 2022): 1–12. http://dx.doi.org/10.1155/2022/4626867.
Texto completoWen, Hui, Tongbin Li, Deli Chen, Jianlu Yang y Yan Che. "An Optimized Neural Network Classification Method Based on Kernel Holistic Learning and Division". Mathematical Problems in Engineering 2021 (26 de febrero de 2021): 1–16. http://dx.doi.org/10.1155/2021/8857818.
Texto completoMADHYASTHA, PRANAVA, JOSIAH WANG y LUCIA SPECIA. "The role of image representations in vision to language tasks". Natural Language Engineering 24, n.º 3 (21 de marzo de 2018): 415–39. http://dx.doi.org/10.1017/s1351324918000116.
Texto completoRosso, Marco Martino, Angelo Aloisio, Giansalvo Cirrincione y Giuseppe Carlo Marano. "Subspace features and statistical indicators for neural network-based damage detection". Structures 56 (octubre de 2023): 104792. http://dx.doi.org/10.1016/j.istruc.2023.06.123.
Texto completoRingach, D. L., M. Carandini, G. Sapiro y R. Shapley. "Cortical Circuitry Revealed by Reverse Correlation in the Orientation Domain". Perception 25, n.º 1_suppl (agosto de 1996): 130. http://dx.doi.org/10.1068/v96l0711.
Texto completoZhao, Baigan, Yingping Huang, Hongjian Wei y Xing Hu. "Ego-Motion Estimation Using Recurrent Convolutional Neural Networks through Optical Flow Learning". Electronics 10, n.º 3 (20 de enero de 2021): 222. http://dx.doi.org/10.3390/electronics10030222.
Texto completoAparicio, Miguel, Tetyana Baydyk, Ernst Kussul, Graciela Velasco y Carlos Vera. "Recognition of Bean Plants in Weeds Using Neural Networks". WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS 21 (1 de marzo de 2022): 34–39. http://dx.doi.org/10.37394/23201.2022.21.4.
Texto completoZhi, Chuan, Zhi Jian Li y Yi Shi. "Research on Robustness of Color Device Characteristic Methods Based on Artificial Intelligence". Applied Mechanics and Materials 262 (diciembre de 2012): 65–68. http://dx.doi.org/10.4028/www.scientific.net/amm.262.65.
Texto completoMa, Zhiheng, Dezheng Gao, Shaolei Yang, Xing Wei y Yihong Gong. "Dataset Condensation via Expert Subspace Projection". Sensors 23, n.º 19 (28 de septiembre de 2023): 8148. http://dx.doi.org/10.3390/s23198148.
Texto completoLi, Changsheng, Chen Yang, Bo Liu, Ye Yuan y Guoren Wang. "LRSC: Learning Representations for Subspace Clustering". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 9 (18 de mayo de 2021): 8340–48. http://dx.doi.org/10.1609/aaai.v35i9.17014.
Texto completoKohonen, Teuvo, Samuel Kaski y Harri Lappalainen. "Self-Organized Formation of Various Invariant-Feature Filters in the Adaptive-Subspace SOM". Neural Computation 9, n.º 6 (1 de agosto de 1997): 1321–44. http://dx.doi.org/10.1162/neco.1997.9.6.1321.
Texto completoLipshutz, David, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta y Dmitri B. Chklovskii. "A Biologically Plausible Neural Network for Multichannel Canonical Correlation Analysis". Neural Computation 33, n.º 9 (19 de agosto de 2021): 2309–52. http://dx.doi.org/10.1162/neco_a_01414.
Texto completoAhmadian, Kushan y Marina Gavrilova. "Chaotic Neural Network for Biometric Pattern Recognition". Advances in Artificial Intelligence 2012 (30 de agosto de 2012): 1–9. http://dx.doi.org/10.1155/2012/124176.
Texto completoJeong, Sang-Su, Won-Kwang Park y Young-Deuk Joh. "Construction of Full-View Data from Limited-View Data Using Artificial Neural Network in the Inverse Scattering Problem". Applied Sciences 12, n.º 19 (29 de septiembre de 2022): 9801. http://dx.doi.org/10.3390/app12199801.
Texto completoMiao, Y. y Y. Hua. "Fast subspace tracking and neural network learning by a novel information criterion". IEEE Transactions on Signal Processing 46, n.º 7 (julio de 1998): 1967–79. http://dx.doi.org/10.1109/78.700968.
Texto completoYue, Han, Hangbin Wu, Ville Lehtola, Junyi Wei y Chun Liu. "Indoor functional subspace division from point clouds based on graph neural network". International Journal of Applied Earth Observation and Geoinformation 127 (marzo de 2024): 103656. http://dx.doi.org/10.1016/j.jag.2024.103656.
Texto completoZha, Yufei, Min Wu, Zhuling Qiu, Jingxian Sun, Peng Zhang y Wei Huang. "Online Semantic Subspace Learning with Siamese Network for UAV Tracking". Remote Sensing 12, n.º 2 (19 de enero de 2020): 325. http://dx.doi.org/10.3390/rs12020325.
Texto completoFarabbi, Andrea y Luca Mainardi. "Domain-Specific Processing Stage for Estimating Single-Trail Evoked Potential Improves CNN Performance in Detecting Error Potential". Sensors 23, n.º 22 (8 de noviembre de 2023): 9049. http://dx.doi.org/10.3390/s23229049.
Texto completoMao, Handong, Xiaodan Lin, Zhimao Li, Xiaobin Shen y Wenzhao Zhao. "Anti-Icing System Performance Prediction Using POD and PSO-BP Neural Networks". Aerospace 11, n.º 6 (26 de mayo de 2024): 430. http://dx.doi.org/10.3390/aerospace11060430.
Texto completoKim, Jonghong, WonHee Lee, Sungdae Baek, Jeong-Ho Hong y Minho Lee. "Incremental Learning for Online Data Using QR Factorization on Convolutional Neural Networks". Sensors 23, n.º 19 (27 de septiembre de 2023): 8117. http://dx.doi.org/10.3390/s23198117.
Texto completoDA SILVA, IVAN NUNES, ANDRÉ NUNES DE SOUZA y MÁRIO EDUARDO BORDON. "A NOVEL APPROACH FOR SOLVING CONSTRAINED NONLINEAR OPTIMIZATION PROBLEMS USING NEUROFUZZY SYSTEMS". International Journal of Neural Systems 11, n.º 03 (junio de 2001): 281–86. http://dx.doi.org/10.1142/s0129065701000722.
Texto completoLiu, Zhoufeng, Baorui Wang, Chunlei Li, Miao Yu y Shumin Ding. "Fabric defect detection based on deep-feature and low-rank decomposition". Journal of Engineered Fibers and Fabrics 15 (enero de 2020): 155892502090302. http://dx.doi.org/10.1177/1558925020903026.
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