Výsledky vyhledávání - "sparse autoencoder network"

IoT and cloud computing-based automated epileptic seizure detection using optimized Siamese convolutional sparse autoencoder network

Autoři: M. Ramkumar S. Syed Jamaesha M. S. Gowtham a další

Zdroj: Signal, Image and Video Processing. 18:3509-3525

An industrial process fault diagnosis method based on independent slow feature analysis and stacked sparse autoencoder network

Autoři: Chang Li Chenglin Wen Zhe Zhou

Zdroj: Journal of the Franklin Institute. 361:234-247

Mineralized-Anomaly Identification Based on Convolutional Sparse Autoencoder Network and Isolated Forest

Autoři: Na Yang Zhenkai Zhang Jianhua Yang a další

Zdroj: Natural Resources Research. 32:1-18

Témata: 0101 mathematics, 01 natural sciences, 0105 earth and related environmental sciences

Compressive Reconstruction Based on Sparse Autoencoder Network Prior for Single-Pixel Imaging

Autoři: Hong Zeng Jiawei Dong Qianxi Li a další

Zdroj: Photonics, Vol 10, Iss 10, p 1109 (2023)

Témata: sparse autoencoder network prior, single-photon counting compressive imaging, single-pixel imaging, multi-channel prior, numerical gradient descent, Applied optics. Photonics, TA1501-1820

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2304-6732/10/10/1109; https://doaj.org/toc/2304-6732

Přístupová URL adresa: https://doaj.org/article/48f428c1b807403680477c220849c39b

Self-Supervised Marine Noise Learning with Sparse Autoencoder Network for Generative Target Magnetic Anomaly Detection

Autoři: Shigang Wang Xiangyuan Zhang Yifan Zhao a další

Zdroj: Remote Sensing, Vol 16, Iss 17, p 3263 (2024)

Témata: magnetic anomaly detection (MAD), marine noise modeling, self-supervised learning (SSL), sparse denoising autoencoder (SDAE), Science

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2072-4292/16/17/3263; https://doaj.org/toc/2072-4292

Přístupová URL adresa: https://doaj.org/article/9ea907301efc4761bbfcc2d89a02d1ac

An Innovative PolSAR Image Classification Method Based on Non-Negative Constraints Stacked Sparse Autoencoder Network with Multi-Features Joint Representation Learning

Zdroj: Academic Journal of Computing & Information Science. 6

EndNet: Sparse AutoEncoder Network for Endmember Extraction and Hyperspectral Unmixing

Autoři: Savas Ozkan Berk Kaya Gozde Bozdagi Akar

Zdroj: IEEE Transactions on Geoscience and Remote Sensing. 57:482-496

Témata: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://arxiv.org/pdf/1708.01894
http://arxiv.org/abs/1708.01894
https://dblp.uni-trier.de/db/journals/tgrs/tgrs57.html#OzkanKA19
https://avesis.metu.edu.tr/yayin/0e0175c1-59bd-4ff8-a11c-a16c4dfae998/endnet-sparse-autoencoder-network-for-endmember-extraction-and-hyperspectral-unmixing
https://ieeexplore.ieee.org/document/8429926
https://arxiv.org/abs/1708.01894
https://doi.org/10.1109/TGRS.2018.2856929
http://ui.adsabs.harvard.edu/abs/2019ITGRS..57..482O/abstract
https://aperta.ulakbim.gov.tr/record/99827

Face Recognition Based on Deep Aggregated Sparse Autoencoder Network

Autoři: Guofeng Zou Guixia Fu Dingyi Lin a další

Zdroj: 2018 37th Chinese Control Conference (CCC). :9434-9439

Témata: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://xplorestaging.ieee.org/ielx7/8456315/8482271/08482730.pdf?arnumber=8482730
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=8482730

Softmax regression based deep sparse autoencoder network for facial emotion recognition in human-robot interaction

Autoři: Luefeng Chen Wanjuan Su Mengtian Zhou a další

Zdroj: Information Sciences. 428:49-61

Témata: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://dl.acm.org/doi/10.1016/j.ins.2017.10.044
https://www.sciencedirect.com/science/article/pii/S0020025517310496
https://dblp.uni-trier.de/db/journals/isci/isci428.html#ChenZSWSH18
https://doi.org/10.1016/j.ins.2017.10.044

Deep Sparse Autoencoder Network for Facial Emotion Recognition

Autoři: Witold Pedrycz Kaoru Hirota Min Wu a další

Zdroj: Studies in Computational Intelligence ISBN: 9783030615765

Přístupová URL adresa: https://link.springer.com/content/pdf/10.1007%2F978-3-030-61577-2_3.pdf
https://link.springer.com/chapter/10.1007/978-3-030-61577-2_3

Wavelet Transform and Stacked Sparse Autoencoder Network Based Location Method of Cable Incipient Fault

Autoři: Xue Bai Li Shenghui Dong Henan

Zdroj: Proceedings of the 2019 International Conference on Computer, Network, Communication and Information Systems (CNCI 2019).

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://www.atlantis-press.com/proceedings/cnci-19/125906915

Parameter identification for nonlinear Hammerstein models with stacked sparse autoencoder network.

Autoři: Li, Feng Song, Liexin Wang, Tianhu a další

Zdroj: Engineering Applications of Artificial Intelligence. Jan2026:Part 2, Vol. 163, pN.PAG-N.PAG. 1p.

Témata: *HAMMERSTEIN equations, *NONLINEAR systems, *LEAST squares, *TECHNOLOGICAL innovations, *STATISTICAL models, *MATHEMATICAL analysis, *PARAMETER estimation, *ARTIFICIAL neural networks

A deep learning based malicious module identification using stacked sparse autoencoder network for VLSI circuit reliability

Autoři: M. Priyatharishini M. Nirmala Devi

Zdroj: Measurement. 194:111055

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

EndNet: Sparse AutoEncoder Network for Endmember Extraction and Hyperspectral Unmixing

Autoři: Ozkan, Savas Kaya, Berk Akar, Gozde Bozdagi

Témata: Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/1708.01894

Compressive Reconstruction Based on Sparse Autoencoder Network Prior for Single-Pixel Imaging.

Autoři: Zeng, Hong Dong, Jiawei Li, Qianxi a další

Zdroj: Photonics; Oct2023, Vol. 10 Issue 10, p1109, 21p

Témata: PIXELS, MULTICHANNEL communication, COMPRESSED sensing, FEATURE extraction, IMAGE reconstruction, LINEAR equations, INFORMATION networks

IoT and cloud computing-based automated epileptic seizure detection using optimized Siamese convolutional sparse autoencoder network.

Autoři: Ramkumar, M. Jamaesha, S. Syed Gowtham, M. S. a další

Zdroj: Signal, Image & Video Processing; Jun2024, Vol. 18 Issue 4, p3509-3525, 17p

Self-Supervised Marine Noise Learning with Sparse Autoencoder Network for Generative Target Magnetic Anomaly Detection.

Autoři: Wang, Shigang Zhang, Xiangyuan Zhao, Yifan a další

Zdroj: Remote Sensing; Sep2024, Vol. 16 Issue 17, p3263, 19p

Témata: MAGNETIC anomalies, MAGNETIC noise, ANOMALY detection (Computer security), STATISTICAL decision making, DETECTORS, AUTOENCODERS

基于深度稀疏自编码网络的植物叶片分类.

Alternate Title: Plant leaf classification based on Softmax regression and K* deep sparse autoencoder network.

Autoři: 王　雪 陈　炼 肖志勇

Zdroj: Journal of Nanchang University (Natural Science). Dec2019, Vol. 43 Issue 6, p606-610. 5p.

Mineralized-Anomaly Identification Based on Convolutional Sparse Autoencoder Network and Isolated Forest.

Autoři: Yang, Na Zhang, Zhenkai Yang, Jianhua a další

Zdroj: Natural Resources Research; Feb2023, Vol. 32 Issue 1, p1-18, 18p

Témata: ADDITION (Mathematics), GENERALIZATION, MINERALIZATION, ORE deposits, PRIOR learning

Geografický termín: SHAANXI Sheng (China), CHINA

Image edge detection based on Sparse Autoencoder network

Autoři: Jinlong Li Xiaorong Gao Yingwei Liu

Zdroj: Tenth International Conference on Information Optics and Photonics. :138

Témata: 03 medical and health sciences, 0302 clinical medicine

Přístupová URL adresa: http://ui.adsabs.harvard.edu/abs/2018SPIE10964E..32L/abstract