Artigos de revistas sobre o 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 (janeiro de 1989): 61–68. http://dx.doi.org/10.1142/s0129065789000475.
Texto completo da fonteEdraki, Marzieh, Nazanin Rahnavard e 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 completo da fonteZhi, Chuan, Ling Hua Guo, Mei Yun Zhang e Yi Shi. "Research on Dynamic Subspace Divided BP Neural Network Identification Method of Color Space Transform Model". Advanced Materials Research 174 (dezembro de 2010): 97–100. http://dx.doi.org/10.4028/www.scientific.net/amr.174.97.
Texto completo da fonteFunabashi, 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 completo da fonteMahomud, V. A., A. S. Hadi, N. K. Wafi e S. M. R. Taha. "DIRECTION OF ARRIVAL USING PCA NEURALNETWORKS". Journal of Engineering 10, n.º 1 (13 de março de 2024): 83–89. http://dx.doi.org/10.31026/j.eng.2004.01.07.
Texto completo da fonteMenghi, Nicholas, Kemal Kacar e Will Penny. "Multitask learning over shared subspaces". PLOS Computational Biology 17, n.º 7 (6 de julho de 2021): e1009092. http://dx.doi.org/10.1371/journal.pcbi.1009092.
Texto completo da fonteCao, Xiang, e A.-long Yu. "Multi-AUV Cooperative Target Search Algorithm in 3-D Underwater Workspace". Journal of Navigation 70, n.º 6 (30 de junho de 2017): 1293–311. http://dx.doi.org/10.1017/s0373463317000376.
Texto completo da fonteLaaksonen, Jorma, e Erkki Oja. "Learning Subspace Classifiers and Error-Corrective Feature Extraction". International Journal of Pattern Recognition and Artificial Intelligence 12, n.º 04 (junho de 1998): 423–36. http://dx.doi.org/10.1142/s0218001498000270.
Texto completo da fonteChandar, Sarath, Mitesh M. Khapra, Hugo Larochelle e Balaraman Ravindran. "Correlational Neural Networks". Neural Computation 28, n.º 2 (fevereiro de 2016): 257–85. http://dx.doi.org/10.1162/neco_a_00801.
Texto completo da fonteKizaric, Ben, e Daniel Pimentel-Alarcón. "Principle Component Trees and Their Persistent Homology". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 12 (24 de março de 2024): 13220–29. http://dx.doi.org/10.1609/aaai.v38i12.29222.
Texto completo da fonteLing, Junyao. "Score Prediction of Sports Events Based on Parallel Self-Organizing Nonlinear Neural Network". Computational Intelligence and Neuroscience 2022 (15 de janeiro de 2022): 1–10. http://dx.doi.org/10.1155/2022/4882309.
Texto completo da fontePehlevan, Cengiz, Tao Hu e 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 (julho de 2015): 1461–95. http://dx.doi.org/10.1162/neco_a_00745.
Texto completo da fonteTituaña, Luis, e 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 completo da fonteChuan, Zhi, Zhou Shi-Sheng e 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 completo da fonteKohonen, 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 completo da fonteXu, Lei, Adam Krzyzak e Erkki Oja. "NEURAL NETS FOR DUAL SUBSPACE PATTERN RECOGNITION METHOD". International Journal of Neural Systems 02, n.º 03 (janeiro de 1991): 169–84. http://dx.doi.org/10.1142/s0129065791000169.
Texto completo da fonteTran, Tich Phuoc, Thi Thanh Sang Nguyen, Poshiang Tsai e Xiaoying Kong. "BSPNN: boosted subspace probabilistic neural network for email security". Artificial Intelligence Review 35, n.º 4 (1 de janeiro de 2011): 369–82. http://dx.doi.org/10.1007/s10462-010-9198-2.
Texto completo da fonteLIU, ZHI-QIANG. "ADAPTIVE SUBSPACE SELF-ORGANIZING MAP AND ITS APPLICATIONS IN FACE RECOGNITION". International Journal of Image and Graphics 02, n.º 04 (outubro de 2002): 519–40. http://dx.doi.org/10.1142/s0219467802000834.
Texto completo da fonteWang, Pin, Shanshan Lv, Yongming Li, Qi Song, Linyu Li, Jiaxin Wang e 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 outubro de 2020): 2289–96. http://dx.doi.org/10.1166/jmihi.2020.3172.
Texto completo da fonteWang, Pin, Shanshan Lv, Yongming Li, Qi Song, Linyu Li, Jiaxin Wang e 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 outubro de 2020): 2289–96. http://dx.doi.org/10.1166/jmihi.2020.31722289.
Texto completo da fonteLi, Tai-fu, Wei Jia, Wei Zhou, Ji-ke Ge, Yu-cheng Liu e 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 completo da fonteWU, JING, HONG YAN e ANDREW CHALMERS. "HANDWRITTEN DIGIT RECOGNITION USING TWO-LAYER SELF-ORGANIZING MAPS". International Journal of Neural Systems 05, n.º 04 (dezembro de 1994): 357–62. http://dx.doi.org/10.1142/s0129065794000347.
Texto completo da fonteLi, Jiamu, Ji Zhang, Mohamed Jaward Bah, Jian Wang, Youwen Zhu, Gaoming Yang, Lingling Li e 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 novembro de 2022): 429. http://dx.doi.org/10.3390/a15110429.
Texto completo da fonteZhang, Long, Nana Wang, Jieli Wei e 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 completo da fontePrakash, M., e M. N. Murty. "Growing subspace pattern recognition methods and their neural-network models". IEEE Transactions on Neural Networks 8, n.º 1 (janeiro de 1997): 161–68. http://dx.doi.org/10.1109/72.554201.
Texto completo da fonteWen Yao, Xiaoqian Chen, Yong Zhao e 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 (fevereiro de 2012): 247–59. http://dx.doi.org/10.1109/tnnls.2011.2178560.
Texto completo da fonteJANKOVIC, MARKO, e HIDEMITSU OGAWA. "TIME-ORIENTED HIERARCHICAL METHOD FOR COMPUTATION OF PRINCIPAL COMPONENTS USING SUBSPACE LEARNING ALGORITHM". International Journal of Neural Systems 14, n.º 05 (outubro de 2004): 313–23. http://dx.doi.org/10.1142/s0129065704002091.
Texto completo da fonteNong, Ji Fu. "A Principal Components Analysis Self-Organizing Neural Network Model and Computational Experiment". Advanced Materials Research 756-759 (setembro de 2013): 3330–35. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.3330.
Texto completo da fonteLiu, 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 junho de 2022): 1–12. http://dx.doi.org/10.1155/2022/4626867.
Texto completo da fonteWen, Hui, Tongbin Li, Deli Chen, Jianlu Yang e Yan Che. "An Optimized Neural Network Classification Method Based on Kernel Holistic Learning and Division". Mathematical Problems in Engineering 2021 (26 de fevereiro de 2021): 1–16. http://dx.doi.org/10.1155/2021/8857818.
Texto completo da fonteMADHYASTHA, PRANAVA, JOSIAH WANG e LUCIA SPECIA. "The role of image representations in vision to language tasks". Natural Language Engineering 24, n.º 3 (21 de março de 2018): 415–39. http://dx.doi.org/10.1017/s1351324918000116.
Texto completo da fonteRosso, Marco Martino, Angelo Aloisio, Giansalvo Cirrincione e Giuseppe Carlo Marano. "Subspace features and statistical indicators for neural network-based damage detection". Structures 56 (outubro de 2023): 104792. http://dx.doi.org/10.1016/j.istruc.2023.06.123.
Texto completo da fonteRingach, D. L., M. Carandini, G. Sapiro e 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 completo da fonteZhao, Baigan, Yingping Huang, Hongjian Wei e Xing Hu. "Ego-Motion Estimation Using Recurrent Convolutional Neural Networks through Optical Flow Learning". Electronics 10, n.º 3 (20 de janeiro de 2021): 222. http://dx.doi.org/10.3390/electronics10030222.
Texto completo da fonteAparicio, Miguel, Tetyana Baydyk, Ernst Kussul, Graciela Velasco e Carlos Vera. "Recognition of Bean Plants in Weeds Using Neural Networks". WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS 21 (1 de março de 2022): 34–39. http://dx.doi.org/10.37394/23201.2022.21.4.
Texto completo da fonteZhi, Chuan, Zhi Jian Li e Yi Shi. "Research on Robustness of Color Device Characteristic Methods Based on Artificial Intelligence". Applied Mechanics and Materials 262 (dezembro de 2012): 65–68. http://dx.doi.org/10.4028/www.scientific.net/amm.262.65.
Texto completo da fonteMa, Zhiheng, Dezheng Gao, Shaolei Yang, Xing Wei e Yihong Gong. "Dataset Condensation via Expert Subspace Projection". Sensors 23, n.º 19 (28 de setembro de 2023): 8148. http://dx.doi.org/10.3390/s23198148.
Texto completo da fonteLi, Changsheng, Chen Yang, Bo Liu, Ye Yuan e Guoren Wang. "LRSC: Learning Representations for Subspace Clustering". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 9 (18 de maio de 2021): 8340–48. http://dx.doi.org/10.1609/aaai.v35i9.17014.
Texto completo da fonteKohonen, Teuvo, Samuel Kaski e 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 completo da fonteLipshutz, David, Yanis Bahroun, Siavash Golkar, Anirvan M. Sengupta e 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 completo da fonteAhmadian, Kushan, e 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 completo da fonteJeong, Sang-Su, Won-Kwang Park e 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 setembro de 2022): 9801. http://dx.doi.org/10.3390/app12199801.
Texto completo da fonteMiao, Y., e Y. Hua. "Fast subspace tracking and neural network learning by a novel information criterion". IEEE Transactions on Signal Processing 46, n.º 7 (julho de 1998): 1967–79. http://dx.doi.org/10.1109/78.700968.
Texto completo da fonteYue, Han, Hangbin Wu, Ville Lehtola, Junyi Wei e Chun Liu. "Indoor functional subspace division from point clouds based on graph neural network". International Journal of Applied Earth Observation and Geoinformation 127 (março de 2024): 103656. http://dx.doi.org/10.1016/j.jag.2024.103656.
Texto completo da fonteZha, Yufei, Min Wu, Zhuling Qiu, Jingxian Sun, Peng Zhang e Wei Huang. "Online Semantic Subspace Learning with Siamese Network for UAV Tracking". Remote Sensing 12, n.º 2 (19 de janeiro de 2020): 325. http://dx.doi.org/10.3390/rs12020325.
Texto completo da fonteFarabbi, Andrea, e 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 novembro de 2023): 9049. http://dx.doi.org/10.3390/s23229049.
Texto completo da fonteMao, Handong, Xiaodan Lin, Zhimao Li, Xiaobin Shen e Wenzhao Zhao. "Anti-Icing System Performance Prediction Using POD and PSO-BP Neural Networks". Aerospace 11, n.º 6 (26 de maio de 2024): 430. http://dx.doi.org/10.3390/aerospace11060430.
Texto completo da fonteKim, Jonghong, WonHee Lee, Sungdae Baek, Jeong-Ho Hong e Minho Lee. "Incremental Learning for Online Data Using QR Factorization on Convolutional Neural Networks". Sensors 23, n.º 19 (27 de setembro de 2023): 8117. http://dx.doi.org/10.3390/s23198117.
Texto completo da fonteDA SILVA, IVAN NUNES, ANDRÉ NUNES DE SOUZA e MÁRIO EDUARDO BORDON. "A NOVEL APPROACH FOR SOLVING CONSTRAINED NONLINEAR OPTIMIZATION PROBLEMS USING NEUROFUZZY SYSTEMS". International Journal of Neural Systems 11, n.º 03 (junho de 2001): 281–86. http://dx.doi.org/10.1142/s0129065701000722.
Texto completo da fonteLiu, Zhoufeng, Baorui Wang, Chunlei Li, Miao Yu e Shumin Ding. "Fabric defect detection based on deep-feature and low-rank decomposition". Journal of Engineered Fibers and Fabrics 15 (janeiro de 2020): 155892502090302. http://dx.doi.org/10.1177/1558925020903026.
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