Artykuły w czasopismach na temat „Sparse deep neural networks”
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Scardapane, Simone, Danilo Comminiello, Amir Hussain i Aurelio Uncini. "Group sparse regularization for deep neural networks". Neurocomputing 241 (czerwiec 2017): 81–89. http://dx.doi.org/10.1016/j.neucom.2017.02.029.
Pełny tekst źródłaZang, Ke, Wenqi Wu i Wei Luo. "Deep Sparse Learning for Automatic Modulation Classification Using Recurrent Neural Networks". Sensors 21, nr 19 (25.09.2021): 6410. http://dx.doi.org/10.3390/s21196410.
Pełny tekst źródłaWu, Kailun, Yiwen Guo i Changshui Zhang. "Compressing Deep Neural Networks With Sparse Matrix Factorization". IEEE Transactions on Neural Networks and Learning Systems 31, nr 10 (październik 2020): 3828–38. http://dx.doi.org/10.1109/tnnls.2019.2946636.
Pełny tekst źródłaGangopadhyay, Briti, Pallab Dasgupta i Soumyajit Dey. "Safety Aware Neural Pruning for Deep Reinforcement Learning (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 13 (26.06.2023): 16212–13. http://dx.doi.org/10.1609/aaai.v37i13.26966.
Pełny tekst źródłaPetschenig, Horst, i Robert Legenstein. "Quantized rewiring: hardware-aware training of sparse deep neural networks". Neuromorphic Computing and Engineering 3, nr 2 (26.05.2023): 024006. http://dx.doi.org/10.1088/2634-4386/accd8f.
Pełny tekst źródłaBelay, Kaleab. "Gradient and Mangitude Based Pruning for Sparse Deep Neural Networks". Proceedings of the AAAI Conference on Artificial Intelligence 36, nr 11 (28.06.2022): 13126–27. http://dx.doi.org/10.1609/aaai.v36i11.21699.
Pełny tekst źródłaKaur, Mandeep, i Pradip Kumar Yadava. "A Review on Classification of Images with Convolutional Neural Networks". International Journal for Research in Applied Science and Engineering Technology 11, nr 7 (31.07.2023): 658–63. http://dx.doi.org/10.22214/ijraset.2023.54704.
Pełny tekst źródłaBi, Jia, i Steve R. Gunn. "Sparse Deep Neural Network Optimization for Embedded Intelligence". International Journal on Artificial Intelligence Tools 29, nr 03n04 (czerwiec 2020): 2060002. http://dx.doi.org/10.1142/s0218213020600027.
Pełny tekst źródłaGallicchio, Claudio, i Alessio Micheli. "Fast and Deep Graph Neural Networks". Proceedings of the AAAI Conference on Artificial Intelligence 34, nr 04 (3.04.2020): 3898–905. http://dx.doi.org/10.1609/aaai.v34i04.5803.
Pełny tekst źródłaTartaglione, Enzo, Andrea Bragagnolo, Attilio Fiandrotti i Marco Grangetto. "LOss-Based SensiTivity rEgulaRization: Towards deep sparse neural networks". Neural Networks 146 (luty 2022): 230–37. http://dx.doi.org/10.1016/j.neunet.2021.11.029.
Pełny tekst źródłaMa, Rongrong, Jianyu Miao, Lingfeng Niu i Peng Zhang. "Transformed ℓ1 regularization for learning sparse deep neural networks". Neural Networks 119 (listopad 2019): 286–98. http://dx.doi.org/10.1016/j.neunet.2019.08.015.
Pełny tekst źródłaZhao, Jin, i Licheng Jiao. "Fast Sparse Deep Neural Networks: Theory and Performance Analysis". IEEE Access 7 (2019): 74040–55. http://dx.doi.org/10.1109/access.2019.2920688.
Pełny tekst źródłaKarim, Ahmad M., Mehmet S. Güzel, Mehmet R. Tolun, Hilal Kaya i Fatih V. Çelebi. "A New Generalized Deep Learning Framework Combining Sparse Autoencoder and Taguchi Method for Novel Data Classification and Processing". Mathematical Problems in Engineering 2018 (7.06.2018): 1–13. http://dx.doi.org/10.1155/2018/3145947.
Pełny tekst źródłaLi, Yihang. "Sparse-Aware Deep Learning Accelerator". Highlights in Science, Engineering and Technology 39 (1.04.2023): 305–10. http://dx.doi.org/10.54097/hset.v39i.6544.
Pełny tekst źródłaOhn, Ilsang, i Yongdai Kim. "Nonconvex Sparse Regularization for Deep Neural Networks and Its Optimality". Neural Computation 34, nr 2 (14.01.2022): 476–517. http://dx.doi.org/10.1162/neco_a_01457.
Pełny tekst źródłaAvgerinos, Christos, Nicholas Vretos i Petros Daras. "Less Is More: Adaptive Trainable Gradient Dropout for Deep Neural Networks". Sensors 23, nr 3 (24.01.2023): 1325. http://dx.doi.org/10.3390/s23031325.
Pełny tekst źródłaHao, Yutong, Yunpeng Liu, Jinmiao Zhao i Chuang Yu. "Dual-Domain Prior-Driven Deep Network for Infrared Small-Target Detection". Remote Sensing 15, nr 15 (31.07.2023): 3827. http://dx.doi.org/10.3390/rs15153827.
Pełny tekst źródłaLee, Sangkyun, i Jeonghyun Lee. "Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems". Applied Sciences 9, nr 8 (23.04.2019): 1669. http://dx.doi.org/10.3390/app9081669.
Pełny tekst źródłaMousavi, Hamid, Mohammad Loni, Mina Alibeigi i Masoud Daneshtalab. "DASS: Differentiable Architecture Search for Sparse Neural Networks". ACM Transactions on Embedded Computing Systems 22, nr 5s (9.09.2023): 1–21. http://dx.doi.org/10.1145/3609385.
Pełny tekst źródłaAo, Ren, Zhang Tao, Wang Yuhao, Lin Sheng, Dong Peiyan, Chen Yen-kuang, Xie Yuan i Wang Yanzhi. "DARB: A Density-Adaptive Regular-Block Pruning for Deep Neural Networks". Proceedings of the AAAI Conference on Artificial Intelligence 34, nr 04 (3.04.2020): 5495–502. http://dx.doi.org/10.1609/aaai.v34i04.6000.
Pełny tekst źródłaÖstling, Robert. "Part of Speech Tagging: Shallow or Deep Learning?" Northern European Journal of Language Technology 5 (19.06.2018): 1–15. http://dx.doi.org/10.3384/nejlt.2000-1533.1851.
Pełny tekst źródłaGong, Maoguo, Jia Liu, Hao Li, Qing Cai i Linzhi Su. "A Multiobjective Sparse Feature Learning Model for Deep Neural Networks". IEEE Transactions on Neural Networks and Learning Systems 26, nr 12 (grudzień 2015): 3263–77. http://dx.doi.org/10.1109/tnnls.2015.2469673.
Pełny tekst źródłaBoo, Yoonho, i Wonyong Sung. "Compression of Deep Neural Networks with Structured Sparse Ternary Coding". Journal of Signal Processing Systems 91, nr 9 (6.11.2018): 1009–19. http://dx.doi.org/10.1007/s11265-018-1418-z.
Pełny tekst źródłaZhao, Yao, Qingsong Liu, He Tian, Bingo Wing-Kuen Ling i Zhe Zhang. "DeepRED Based Sparse SAR Imaging". Remote Sensing 16, nr 2 (5.01.2024): 212. http://dx.doi.org/10.3390/rs16020212.
Pełny tekst źródłaWan, Xinyue, Bofeng Zhang, Guobing Zou i Furong Chang. "Sparse Data Recommendation by Fusing Continuous Imputation Denoising Autoencoder and Neural Matrix Factorization". Applied Sciences 9, nr 1 (24.12.2018): 54. http://dx.doi.org/10.3390/app9010054.
Pełny tekst źródłaEl-Yabroudi, Mohammad Z., Ikhlas Abdel-Qader, Bradley J. Bazuin, Osama Abudayyeh i Rakan C. Chabaan. "Guided Depth Completion with Instance Segmentation Fusion in Autonomous Driving Applications". Sensors 22, nr 24 (7.12.2022): 9578. http://dx.doi.org/10.3390/s22249578.
Pełny tekst źródłaQiao, Chen, Yan Shi, Yu-Xian Diao, Vince D. Calhoun i Yu-Ping Wang. "Log-sum enhanced sparse deep neural network". Neurocomputing 407 (wrzesień 2020): 206–20. http://dx.doi.org/10.1016/j.neucom.2020.04.118.
Pełny tekst źródłaMorotti, Elena, Davide Evangelista i Elena Loli Piccolomini. "A Green Prospective for Learned Post-Processing in Sparse-View Tomographic Reconstruction". Journal of Imaging 7, nr 8 (7.08.2021): 139. http://dx.doi.org/10.3390/jimaging7080139.
Pełny tekst źródłaWan, Lulu, Tao Chen, Antonio Plaza i Haojie Cai. "Hyperspectral Unmixing Based on Spectral and Sparse Deep Convolutional Neural Networks". IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14 (2021): 11669–82. http://dx.doi.org/10.1109/jstars.2021.3126755.
Pełny tekst źródłaKhattak, Muhammad Irfan, Nasir Saleem, Jiechao Gao, Elena Verdu i Javier Parra Fuente. "Regularized sparse features for noisy speech enhancement using deep neural networks". Computers and Electrical Engineering 100 (maj 2022): 107887. http://dx.doi.org/10.1016/j.compeleceng.2022.107887.
Pełny tekst źródłaXie, Zhihua, Yi Li, Jieyi Niu, Ling Shi, Zhipeng Wang i Guoyu Lu. "Hyperspectral face recognition based on sparse spectral attention deep neural networks". Optics Express 28, nr 24 (16.11.2020): 36286. http://dx.doi.org/10.1364/oe.404793.
Pełny tekst źródłaLiu, Wei, Yue Yang i Longsheng Wei. "Weather Recognition of Street Scene Based on Sparse Deep Neural Networks". Journal of Advanced Computational Intelligence and Intelligent Informatics 21, nr 3 (19.05.2017): 403–8. http://dx.doi.org/10.20965/jaciii.2017.p0403.
Pełny tekst źródłaSchwab, Johannes, Stephan Antholzer i Markus Haltmeier. "Big in Japan: Regularizing Networks for Solving Inverse Problems". Journal of Mathematical Imaging and Vision 62, nr 3 (3.10.2019): 445–55. http://dx.doi.org/10.1007/s10851-019-00911-1.
Pełny tekst źródła.., Vani, i Piyush Kumar Pareek. "Deep Multiple Instance Learning Approach for Classification in Clinical Decision Support Systems". American Journal of Business and Operations Research 10, nr 2 (2023): 52–60. http://dx.doi.org/10.54216/ajbor.100206.
Pełny tekst źródłaHe, Haoyuan, Lingxuan Huang, Zisen Huang i Tiantian Yang. "The Compression Techniques Applied on Deep Learning Model". Highlights in Science, Engineering and Technology 4 (26.07.2022): 325–31. http://dx.doi.org/10.54097/hset.v4i.920.
Pełny tekst źródłaAlmulla Khalaf, Maysa Ibrahem, i John Q. Gan. "A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder". Artificial Intelligence Research 8, nr 1 (2.04.2019): 41. http://dx.doi.org/10.5430/air.v8n1p41.
Pełny tekst źródłaZahn, Olivia, Jorge Bustamante, Callin Switzer, Thomas L. Daniel i J. Nathan Kutz. "Pruning deep neural networks generates a sparse, bio-inspired nonlinear controller for insect flight". PLOS Computational Biology 18, nr 9 (27.09.2022): e1010512. http://dx.doi.org/10.1371/journal.pcbi.1010512.
Pełny tekst źródłaLiu, Xiao, Wenbin Li, Jing Huo, Lili Yao i Yang Gao. "Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio". Proceedings of the AAAI Conference on Artificial Intelligence 34, nr 04 (3.04.2020): 4900–4907. http://dx.doi.org/10.1609/aaai.v34i04.5927.
Pełny tekst źródłaYao, Zhongtian, Kejie Huang, Haibin Shen i Zhaoyan Ming. "Deep Neural Network Acceleration With Sparse Prediction Layers". IEEE Access 8 (2020): 6839–48. http://dx.doi.org/10.1109/access.2020.2963941.
Pełny tekst źródłaLee, Gwo-Chuan, Jyun-Hong Li i Zi-Yang Li. "A Wasserstein Generative Adversarial Network–Gradient Penalty-Based Model with Imbalanced Data Enhancement for Network Intrusion Detection". Applied Sciences 13, nr 14 (12.07.2023): 8132. http://dx.doi.org/10.3390/app13148132.
Pełny tekst źródłaPhan, Huy, Miao Yin, Yang Sui, Bo Yuan i Saman Zonouz. "CSTAR: Towards Compact and Structured Deep Neural Networks with Adversarial Robustness". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 2 (26.06.2023): 2065–73. http://dx.doi.org/10.1609/aaai.v37i2.25299.
Pełny tekst źródłaZhang, Hongwei, Jiacheng Ni, Kaiming Li, Ying Luo i Qun Zhang. "Nonsparse SAR Scene Imaging Network Based on Sparse Representation and Approximate Observations". Remote Sensing 15, nr 17 (22.08.2023): 4126. http://dx.doi.org/10.3390/rs15174126.
Pełny tekst źródłaGong, Zhenghui, Xiaolong Su, Panhe Hu, Shuowei Liu i Zhen Liu. "Deep Unfolding Sparse Bayesian Learning Network for Off-Grid DOA Estimation with Nested Array". Remote Sensing 15, nr 22 (10.11.2023): 5320. http://dx.doi.org/10.3390/rs15225320.
Pełny tekst źródłaChen, Yuanyuan, i Zhang Yi. "Adaptive sparse dropout: Learning the certainty and uncertainty in deep neural networks". Neurocomputing 450 (sierpień 2021): 354–61. http://dx.doi.org/10.1016/j.neucom.2021.04.047.
Pełny tekst źródłaChen, Jiayu, Xiang Li, Vince D. Calhoun, Jessica A. Turner, Theo G. M. Erp, Lei Wang, Ole A. Andreassen i in. "Sparse deep neural networks on imaging genetics for schizophrenia case–control classification". Human Brain Mapping 42, nr 8 (16.03.2021): 2556–68. http://dx.doi.org/10.1002/hbm.25387.
Pełny tekst źródłaKovacs, Mate, i Victor V. Kryssanov. "Expanding the Feature Space of Deep Neural Networks for Sentiment Classification". International Journal of Machine Learning and Computing 10, nr 2 (luty 2020): 271–76. http://dx.doi.org/10.18178/ijmlc.2020.10.2.931.
Pełny tekst źródłaLui, Hugo F. S., i William R. Wolf. "Construction of reduced-order models for fluid flows using deep feedforward neural networks". Journal of Fluid Mechanics 872 (14.06.2019): 963–94. http://dx.doi.org/10.1017/jfm.2019.358.
Pełny tekst źródłaChen, Qipeng, Qiaoqiao Xiong, Haisong Huang, Saihong Tang i Zhenghong Liu. "Research on the Construction of an Efficient and Lightweight Online Detection Method for Tiny Surface Defects through Model Compression and Knowledge Distillation". Electronics 13, nr 2 (5.01.2024): 253. http://dx.doi.org/10.3390/electronics13020253.
Pełny tekst źródłaZhao, Yao, Chengwen Ou, He Tian, Bingo Wing-Kuen Ling, Ye Tian i Zhe Zhang. "Sparse SAR Imaging Algorithm in Marine Environments Based on Memory-Augmented Deep Unfolding Network". Remote Sensing 16, nr 7 (5.04.2024): 1289. http://dx.doi.org/10.3390/rs16071289.
Pełny tekst źródłaKohjima, Masahiro. "Shuffled Deep Regression". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 12 (24.03.2024): 13238–45. http://dx.doi.org/10.1609/aaai.v38i12.29224.
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