Artigos de revistas sobre o tema "Neural Network Pruning"
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JORGENSEN, THOMAS D., BARRY P. HAYNES e CHARLOTTE C. F. NORLUND. "PRUNING ARTIFICIAL NEURAL NETWORKS USING NEURAL COMPLEXITY MEASURES". International Journal of Neural Systems 18, n.º 05 (outubro de 2008): 389–403. http://dx.doi.org/10.1142/s012906570800166x.
Texto completo da fonteGanguli, Tushar, e Edwin K. P. Chong. "Activation-Based Pruning of Neural Networks". Algorithms 17, n.º 1 (21 de janeiro de 2024): 48. http://dx.doi.org/10.3390/a17010048.
Texto completo da fonteKoene, Randal A., e Yoshio Takane. "Discriminant Component Pruning: Regularization and Interpretation of Multilayered Backpropagation Networks". Neural Computation 11, n.º 3 (1 de abril de 1999): 783–802. http://dx.doi.org/10.1162/089976699300016665.
Texto completo da fonteLing, Xing. "Summary of Deep Neural Network Pruning Algorithms". Applied and Computational Engineering 8, n.º 1 (1 de agosto de 2023): 352–61. http://dx.doi.org/10.54254/2755-2721/8/20230182.
Texto completo da fonteGong, Ziyi, Huifu Zhang, Hao Yang, Fangjun Liu e Fan Luo. "A Review of Neural Network Lightweighting Techniques". Innovation & Technology Advances 1, n.º 2 (16 de janeiro de 2024): 1–16. http://dx.doi.org/10.61187/ita.v1i2.36.
Texto completo da fonteGuo, Changyi, e Ping Li. "Hybrid Pruning Method Based on Convolutional Neural Network Sensitivity and Statistical Threshold". Journal of Physics: Conference Series 2171, n.º 1 (1 de janeiro de 2022): 012055. http://dx.doi.org/10.1088/1742-6596/2171/1/012055.
Texto completo da fonteZou, Yunhuan. "Research On Pruning Methods for Mobilenet Convolutional Neural Network". Highlights in Science, Engineering and Technology 81 (26 de janeiro de 2024): 232–36. http://dx.doi.org/10.54097/a742e326.
Texto completo da fonteLiang, Ling, Lei Deng, Yueling Zeng, Xing Hu, Yu Ji, Xin Ma, Guoqi Li e Yuan Xie. "Crossbar-Aware Neural Network Pruning". IEEE Access 6 (2018): 58324–37. http://dx.doi.org/10.1109/access.2018.2874823.
Texto completo da fonteTsai, Feng-Sheng, Yi-Li Shih, Chin-Tzong Pang e Sheng-Yi Hsu. "Formulation of Pruning Maps with Rhythmic Neural Firing". Mathematics 7, n.º 12 (17 de dezembro de 2019): 1247. http://dx.doi.org/10.3390/math7121247.
Texto completo da fonteWang, Miao, Xu Yang, Yunchong Qian, Yunlin Lei, Jian Cai, Ziyi Huan, Xialv Lin e Hao Dong. "Adaptive Neural Network Structure Optimization Algorithm Based on Dynamic Nodes". Current Issues in Molecular Biology 44, n.º 2 (7 de fevereiro de 2022): 817–32. http://dx.doi.org/10.3390/cimb44020056.
Texto completo da fonteAo, Ren, Zhang Tao, Wang Yuhao, Lin Sheng, Dong Peiyan, Chen Yen-kuang, Xie Yuan e Wang Yanzhi. "DARB: A Density-Adaptive Regular-Block Pruning for Deep Neural Networks". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 5495–502. http://dx.doi.org/10.1609/aaai.v34i04.6000.
Texto completo da fonteLee, Donghyeon, Eunho Lee e Youngbae Hwang. "Lossless Reconstruction of Convolutional Neural Network for Channel-Based Network Pruning". Sensors 23, n.º 4 (13 de fevereiro de 2023): 2102. http://dx.doi.org/10.3390/s23042102.
Texto completo da fontePei, Songwen, Yusheng Wu, Jin Guo e Meikang Qiu. "Neural Network Pruning by Recurrent Weights for Finance Market". ACM Transactions on Internet Technology 22, n.º 3 (31 de agosto de 2022): 1–23. http://dx.doi.org/10.1145/3433547.
Texto completo da fonteScholl, Carolin, Michael E. Rule e Matthias H. Hennig. "The information theory of developmental pruning: Optimizing global network architectures using local synaptic rules". PLOS Computational Biology 17, n.º 10 (11 de outubro de 2021): e1009458. http://dx.doi.org/10.1371/journal.pcbi.1009458.
Texto completo da fonteWu, Tao, Jiao Shi, Deyun Zhou, Xiaolong Zheng e Na Li. "Evolutionary Multi-Objective One-Shot Filter Pruning for Designing Lightweight Convolutional Neural Network". Sensors 21, n.º 17 (2 de setembro de 2021): 5901. http://dx.doi.org/10.3390/s21175901.
Texto completo da fonteWang, Jielei, Zongyong Cui, Zhipeng Zang, Xiangjie Meng e Zongjie Cao. "Absorption Pruning of Deep Neural Network for Object Detection in Remote Sensing Imagery". Remote Sensing 14, n.º 24 (9 de dezembro de 2022): 6245. http://dx.doi.org/10.3390/rs14246245.
Texto completo da fonteXiao, Penghao, Teng Xu, Xiayang Xiao, Weisong Li e Haipeng Wang. "Distillation Sparsity Training Algorithm for Accelerating Convolutional Neural Networks in Embedded Systems". Remote Sensing 15, n.º 10 (17 de maio de 2023): 2609. http://dx.doi.org/10.3390/rs15102609.
Texto completo da fonteWu, Tingting, Chunhe Song, Peng Zeng e Changqing Xia. "Cluster-Based Structural Redundancy Identification for Neural Network Compression". Entropy 25, n.º 1 (21 de dezembro de 2022): 9. http://dx.doi.org/10.3390/e25010009.
Texto completo da fonteDuckro, Donald E., Dennis W. Quinn e Samuel J. Gardner. "Neural Network Pruning with Tukey-Kramer Multiple Comparison Procedure". Neural Computation 14, n.º 5 (1 de maio de 2002): 1149–68. http://dx.doi.org/10.1162/089976602753633420.
Texto completo da fonteQin, Tian, Jiang Zhang e Xihua Zhu. "Analysis of Pruning Optimization Technology Based on Deep Learning". Highlights in Science, Engineering and Technology 4 (26 de julho de 2022): 332–38. http://dx.doi.org/10.54097/hset.v4i.921.
Texto completo da fonteWang, Jiajun. "Research on pruning optimization techniques for neural networks". Applied and Computational Engineering 19, n.º 1 (23 de outubro de 2023): 152–58. http://dx.doi.org/10.54254/2755-2721/19/20231025.
Texto completo da fonteWang, Shuang, e Zhaogong Zhang. "ScoringNet: A Neural Network Based Pruning Criteria for Structured Pruning". Scientific Programming 2023 (14 de abril de 2023): 1–9. http://dx.doi.org/10.1155/2023/9983781.
Texto completo da fonteThodberg, Hans Henrik. "IMPROVING GENERALIZATION OF NEURAL NETWORKS THROUGH PRUNING". International Journal of Neural Systems 01, n.º 04 (janeiro de 1991): 317–26. http://dx.doi.org/10.1142/s0129065791000352.
Texto completo da fonteLu, Sheng. "Study on pruning optimization based on HRank pruning method". Applied and Computational Engineering 6, n.º 1 (14 de junho de 2023): 1204–11. http://dx.doi.org/10.54254/2755-2721/6/20230600.
Texto completo da fonteJeczmionek, Ernest, e Piotr A. Kowalski. "Flattening Layer Pruning in Convolutional Neural Networks". Symmetry 13, n.º 7 (27 de junho de 2021): 1147. http://dx.doi.org/10.3390/sym13071147.
Texto completo da fonteKAMMA, Koji, Yuki ISODA, Sarimu INOUE e Toshikazu WADA. "Neural Behavior-Based Approach for Neural Network Pruning". IEICE Transactions on Information and Systems E103.D, n.º 5 (1 de maio de 2020): 1135–43. http://dx.doi.org/10.1587/transinf.2019edp7177.
Texto completo da fonteCheng, Hanjing, Zidong Wang, Lifeng Ma, Xiaohui Liu e Zhihui Wei. "Multi-task Pruning via Filter Index Sharing: A Many-Objective Optimization Approach". Cognitive Computation 13, n.º 4 (25 de junho de 2021): 1070–84. http://dx.doi.org/10.1007/s12559-021-09894-x.
Texto completo da fonteLiu, Yu, Yong Wang, Haojin Qi e Xiaoming Ju. "SuperPruner: Automatic Neural Network Pruning via Super Network". Scientific Programming 2021 (13 de setembro de 2021): 1–11. http://dx.doi.org/10.1155/2021/9971669.
Texto completo da fonteGou, Longxiang, Ziyi Han e Zhimeng Yuan. "An analysis of different methods for deep neural network pruning". Applied and Computational Engineering 52, n.º 1 (27 de março de 2024): 81–86. http://dx.doi.org/10.54254/2755-2721/52/20241292.
Texto completo da fonteDing, Yunlong, e Di-Rong Chen. "Optimization Based Layer-Wise Pruning Threshold Method for Accelerating Convolutional Neural Networks". Mathematics 11, n.º 15 (27 de julho de 2023): 3311. http://dx.doi.org/10.3390/math11153311.
Texto completo da fonteTessier, Hugo, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, Thomas Hannagan e David Bertrand. "Rethinking Weight Decay for Efficient Neural Network Pruning". Journal of Imaging 8, n.º 3 (4 de março de 2022): 64. http://dx.doi.org/10.3390/jimaging8030064.
Texto completo da fonteGangopadhyay, Briti, Pallab Dasgupta e Soumyajit Dey. "Safety Aware Neural Pruning for Deep Reinforcement Learning (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 13 (26 de junho de 2023): 16212–13. http://dx.doi.org/10.1609/aaai.v37i13.26966.
Texto completo da fonteJakob Krzyston, Rajib Bhattacharjea e Andrew Stark. "Neural network compression with feedback magnitude pruning for automatic modulation classification". ITU Journal on Future and Evolving Technologies 3, n.º 2 (13 de julho de 2022): 157–64. http://dx.doi.org/10.52953/eujf4214.
Texto completo da fonteGong, Wei. "A Neural Networks Pruning and Data Fusion Based Intrusion Detection Model". Applied Mechanics and Materials 651-653 (setembro de 2014): 1772–75. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.1772.
Texto completo da fonteLei, Yu, Dayu Wang, Shenghui Yang, Jiao Shi, Dayong Tian e Lingtong Min. "Network Collaborative Pruning Method for Hyperspectral Image Classification Based on Evolutionary Multi-Task Optimization". Remote Sensing 15, n.º 12 (13 de junho de 2023): 3084. http://dx.doi.org/10.3390/rs15123084.
Texto completo da fonteAi, Fang Ju. "An Improved Pruning Algorithm for Fuzzy Neural Network". Applied Mechanics and Materials 411-414 (setembro de 2013): 2031–36. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.2031.
Texto completo da fonteCamacho, Jose David, Carlos Villaseñor, Carlos Lopez-Franco e Nancy Arana-Daniel. "Neuroplasticity-Based Pruning Method for Deep Convolutional Neural Networks". Applied Sciences 12, n.º 10 (13 de maio de 2022): 4945. http://dx.doi.org/10.3390/app12104945.
Texto completo da fonteGe, Yisu, Shufang Lu e Fei Gao. "Small Network for Lightweight Task in Computer Vision: A Pruning Method Based on Feature Representation". Computational Intelligence and Neuroscience 2021 (17 de abril de 2021): 1–12. http://dx.doi.org/10.1155/2021/5531023.
Texto completo da fonteGrau, M. Mar Abad, e L. Daniel Hernandez Molinero. "Local Representation Neural Networks for Feature Selection". Journal of Advanced Computational Intelligence and Intelligent Informatics 3, n.º 4 (20 de agosto de 1999): 326–31. http://dx.doi.org/10.20965/jaciii.1999.p0326.
Texto completo da fonteZhang, Chaoyan, Cheng Li, Baolong Guo e Nannan Liao. "Neural Network Compression via Low Frequency Preference". Remote Sensing 15, n.º 12 (16 de junho de 2023): 3144. http://dx.doi.org/10.3390/rs15123144.
Texto completo da fonteBondarenko, Andrey, Arkady Borisov e Ludmila Alekseeva. "Neurons vs Weights Pruning in Artificial Neural Networks". Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 3 (16 de junho de 2015): 22. http://dx.doi.org/10.17770/etr2015vol3.166.
Texto completo da fonteGuo, Wenzhe, Hasan Erdem Yantır, Mohammed E. Fouda, Ahmed M. Eltawil e Khaled Nabil Salama. "Towards Efficient Neuromorphic Hardware: Unsupervised Adaptive Neuron Pruning". Electronics 9, n.º 7 (27 de junho de 2020): 1059. http://dx.doi.org/10.3390/electronics9071059.
Texto completo da fonteAlshahrani, Mona, Othman Soufan, Arturo Magana-Mora e Vladimir B. Bajic. "DANNP: an efficient artificial neural network pruning tool". PeerJ Computer Science 3 (6 de novembro de 2017): e137. http://dx.doi.org/10.7717/peerj-cs.137.
Texto completo da fonteNaeem, Saad, Noreen Jamil, Habib Ullah Khan e Shah Nazir. "Complexity of Deep Convolutional Neural Networks in Mobile Computing". Complexity 2020 (17 de setembro de 2020): 1–8. http://dx.doi.org/10.1155/2020/3853780.
Texto completo da fonteJEARANAITANAKIJ, KIETIKUL, e OUEN PINNGERN. "SPARTAN SIMPLICITY: A PRUNING ALGORITHM FOR NEURAL NETS". Journal of Circuits, Systems and Computers 17, n.º 04 (agosto de 2008): 569–96. http://dx.doi.org/10.1142/s0218126608004514.
Texto completo da fonteHuang, Junhao, Weize Sun e Lei Huang. "Joint Structure and Parameter Optimization of Multiobjective Sparse Neural Network". Neural Computation 33, n.º 4 (2021): 1113–43. http://dx.doi.org/10.1162/neco_a_01368.
Texto completo da fonteМельниченко, А. В., e К. А. Здор. "INCORPORATING ATTENTION SCORE TO IMPROVE FORESIGHT PRUNING ON TRANSFORMER MODELS". Visnyk of Zaporizhzhya National University Physical and Mathematical Sciences, n.º 2 (19 de dezembro de 2023): 22–28. http://dx.doi.org/10.26661/2786-6254-2023-2-03.
Texto completo da fonteAmeen, Salem, e Sunil Vadera. "Pruning Neural Networks Using Multi-Armed Bandits". Computer Journal 63, n.º 7 (26 de setembro de 2019): 1099–108. http://dx.doi.org/10.1093/comjnl/bxz078.
Texto completo da fonteCai, Mingzhuo, Yihong Su, Binyu Wang e Tianyu Zhang. "Research on compression pruning methods based on deep learning". Journal of Physics: Conference Series 2580, n.º 1 (1 de setembro de 2023): 012060. http://dx.doi.org/10.1088/1742-6596/2580/1/012060.
Texto completo da fonteZhong, Xudong. "Convolutional Neural Network Structure Optimization based on Network Pruning". Highlights in Science, Engineering and Technology 24 (27 de dezembro de 2022): 125–30. http://dx.doi.org/10.54097/hset.v24i.3904.
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