Search Results - "Stacked sparse autoencoder"

Research on Deep Adaptive Clustering Method Based on Stacked Sparse Autoencoders for Concrete Truck Mixers Driving Conditions

Authors: Ying Huang Fachao Jiang Haiming Xie

Source: World Electric Vehicle Journal, Vol 16, Iss 10, p 581 (2025)

Subject Terms: concrete truck mixers, stacked sparse autoencoder, deep features extraction, adaptive clustering algorithm, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Transportation engineering, TA1001-1280

File Description: electronic resource

Relation: https://www.mdpi.com/2032-6653/16/10/581; https://doaj.org/toc/2032-6653

Access URL: https://doaj.org/article/438be03da83f4e4b8087e7267170ff5e

Research on Dung Beetle Optimization Based Stacked Sparse Autoencoder for Network Situation Element Extraction

Authors: Yongchao Yang Pan Zhao

Source: IEEE Access, Vol 12, Pp 24014-24026 (2024)

Subject Terms: Dung beetle optimization, network security, stacked sparse autoencoder, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, network situation element extraction, TK1-9971

Access URL: https://doaj.org/article/1673678679c54e25ad55d197aad24b5e

A Multi-stage Scenario Tree Generation Method for Wind-Solar Load Based on Complex Feature Extraction and Sinkhorn Distance

Authors: Rui WANG Zhixin FU Jian WANG et al.

Source: Zhongguo dianli, Vol 57, Iss 12, Pp 30-40 (2024)

Subject Terms: scenario tree, stacked sparse autoencoder, improved affinity propagation algorithm, sinkhorn distance, load uncertainty, Electricity, QC501-721, Production of electric energy or power. Powerplants. Central stations, TK1001-1841

File Description: electronic resource

Relation: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202402033; https://doaj.org/toc/1004-9649

Access URL: https://doaj.org/article/f121a8d42ba74079acc492b15a2d1369

Hybrid Deep Learning for Fault Diagnosis in Photovoltaic Systems

Authors: Mouaad Bougoffa Samir Benmoussa Mohand Djeziri et al.

Source: Machines, Vol 13, Iss 5, p 378 (2025)

Subject Terms: photovoltaic system, fault detection, fault diagnosis, stacked sparse autoencoder, optimized multi-layer perceptron, Mechanical engineering and machinery, TJ1-1570

File Description: electronic resource

Relation: https://www.mdpi.com/2075-1702/13/5/378; https://doaj.org/toc/2075-1702

Access URL: https://doaj.org/article/8367d16cc4474d028a0c63bc02604faa

Identificação de defeitos em veículos ferroviários de mercadorias baseado num sistema wayside e com recurso a um Autoencoder

Authors: Jorge, Tomás Simões Ribeiro, Diogo Rodrigo Ferreira REPOSITÓRIO P.PORTO

Contributors: Jorge, Tomás Simões Ribeiro, Diogo Rodrigo Ferreira REPOSITÓRIO P.PORTO

Source: urn:tid:203377842

Subject Terms: Danos nas rodas OOR, Desequilíbrio de cargas, Deteção e classificação de danos, Comboios de mercadorias, Sistemas de monitorização wayside, Autoencoder esparso empilhado, Inteligência artificial, OOR wheel damage, Unbalance loads, Damage detection and classification, Freight trains, Wayside monitoring systems, Stacked sparse autoencoder, Artificial intelligence

File Description: application/pdf

Availability: http://hdl.handle.net/10400.22/23828

A Novel Deep Learning Scheme for Motor Imagery EEG Decoding Based on Spatial Representation Fusion

Authors: Jun Yang Zhengmin Ma Jin Wang et al.

Source: IEEE Access, Vol 8, Pp 202100-202110 (2020)

Subject Terms: Brain–computer interface, convolution neural network, 03 medical and health sciences, 0302 clinical medicine, discriminative and representative deep learning, stacked sparse autoencoder, 0202 electrical engineering, electronic engineering, information engineering, feature fusion, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, TK1-9971

Access URL: https://ieeexplore.ieee.org/ielx7/6287639/6514899/09247162.pdf
https://doaj.org/article/43b4f6dcf67a494b8a601ccc26f5280f
https://dblp.uni-trier.de/db/journals/access/access8.html#YangMWF20
https://doi.org/10.1109/ACCESS.2020.3035347
https://ieeexplore.ieee.org/document/9247162

Multimode system condition monitoring using sparsity reconstruction for quality control

Authors: Wafa Bougheloum Mounir Bekaik Sofiane Gherbi

Subject Terms: Diagnosis, Process monitoring multivariate statistical process control, Stacked sparse autoencoder data reconstruction

Relation: https://zenodo.org/records/7827354; oai:zenodo.org:7827354

Availability: https://doi.org/10.11591/ijece.v13i3.pp2711-2720
https://zenodo.org/records/7827354

Sample-Pair Envelope Diamond Autoencoder Ensemble Algorithm for Chronic Disease Recognition

Authors: Yi Zhang Jie Ma Xiaolin Qin et al.

Source: Applied Sciences, Vol 13, Iss 12, p 7322 (2023)

Subject Terms: recognition of chronic disease, wearable sensor monitoring, sample-pair envelope concatenation, envelope learning, diamond-like feature learning, feature-embedded stacked sparse autoencoder, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Relation: https://www.mdpi.com/2076-3417/13/12/7322; https://doaj.org/toc/2076-3417; https://doaj.org/article/34e413f2a72d4928a8f395c07dad668e

Availability: https://doi.org/10.3390/app13127322
https://doaj.org/article/34e413f2a72d4928a8f395c07dad668e

Deep Neural Network Hardware Implementation Based on Stacked Sparse Autoencoder

Authors: Maria G. F. Coutinho Matheus F. Torquato Marcelo A. C. Fernandes

Source: IEEE Access, Vol 7, Pp 40674-40694 (2019)

Subject Terms: systolic array, stacked sparse autoencoder, 0202 electrical engineering, electronic engineering, information engineering, Deep learning, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, FPGA, TK1-9971

Access URL: https://ieeexplore.ieee.org/ielx7/6287639/8600701/08678408.pdf
https://doaj.org/article/9c4a8535d2774e0281877ba083e9dc25
https://ieeexplore.ieee.org/document/8678408
https://dblp.uni-trier.de/db/journals/access/access7.html#CoutinhoTF19
https://cronfa.swan.ac.uk/Record/cronfa49874/Download/0049874-03042019111711.pdf

Low-Speed Bearing Fault Diagnosis Based on ArSSAE Model Using Acoustic Emission and Vibration Signals

Authors: Syahril Ramadhan Saufi Zair Asrar Bin Ahmad Mohd Salman Leong et al.

Source: IEEE Access, Vol 7, Pp 46885-46897 (2019)

Subject Terms: Low speed, acoustic emission analysis, 0202 electrical engineering, electronic engineering, information engineering, TJ Mechanical engineering and machinery, bearing fault diagnosis, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, vibration analysis, adaptive resilient stacked sparse autoencoder (ArSSAE), TK1-9971

File Description: application/pdf

Access URL: https://ieeexplore.ieee.org/ielx7/6287639/8600701/08684238.pdf
https://doaj.org/article/001aa5d8bb7e4294bfa5da5e2937348e

Prediction of the chlorophyll content in pomegranate leaves based on digital image processing technology and stacked sparse autoencoder

Authors: Yi Wang Yingshu Peng

Source: International Journal of Food Properties, Vol 22, Iss 1, Pp 1720-1732 (2019)

Subject Terms: 0301 basic medicine, 03 medical and health sciences, chlorophyll content, Nutrition. Foods and food supply, pomegranate leaves, stacked sparse autoencoder, deep learning, 0401 agriculture, forestry, and fisheries, TX341-641, 04 agricultural and veterinary sciences, TP368-456, Food processing and manufacture, image processing

Access URL: https://www.tandfonline.com/doi/pdf/10.1080/10942912.2019.1675692?needAccess=true
https://doaj.org/article/cea84b53ee27490caed30bffddd708c9
https://www.tandfonline.com/doi/pdf/10.1080/10942912.2019.1675692
https://www.tandfonline.com/doi/full/10.1080/10942912.2019.1675692

Handling partially labeled network data: a semi-supervised approach using stacked sparse autoencoder

Authors: Aouedi, Ons Piamrat, Kandaraj Bagadthey, Dhruvjyoti et al.

Contributors: Aouedi, Ons Piamrat, Kandaraj Bagadthey, Dhruvjyoti et al.

Source: ISSN: 1389-1286.

Subject Terms: Machine learning, deep learning, stacked sparse autoencoder, feature extraction, traffic classification, semi-supervised learning, partial information, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO]Computer Science [cs]

Availability: https://hal.science/hal-03524935
https://hal.science/hal-03524935v1/document
https://hal.science/hal-03524935v1/file/Comnet%20%282%29.pdf
https://doi.org/10.1016/j.comnet.2021.108742

SVseg: Stacked Sparse Autoencoder-Based Patch Classification Modeling for Vertebrae Segmentation

Authors: Syed Furqan Qadri Linlin Shen Mubashir Ahmad et al.

Source: Mathematics ; Volume 10 ; Issue 5 ; Pages: 796

Subject Terms: stacked sparse autoencoder, deep learning, unsupervised learning, CT images, vertebrae segmentation, SVseg, image patch, MICCAI-CSI dataset, sigmoid classifier

File Description: application/pdf

Relation: E1: Mathematics and Computer Science; https://dx.doi.org/10.3390/math10050796

Availability: https://doi.org/10.3390/math10050796

Research on Diesel Engine Fault Diagnosis Method Based on Stacked Sparse Autoencoder and Support Vector Machine

Authors: Huajun Bai Xianbiao Zhan Hao Yan et al.

Source: Electronics, Vol 11, Iss 2249, p 2249 (2022)

Subject Terms: diesel engine, fault diagnosis, stacked sparse autoencoder, support vector machine, Electronics, TK7800-8360

Relation: https://www.mdpi.com/2079-9292/11/14/2249; https://doaj.org/toc/2079-9292; https://doaj.org/article/21672456c29445a9a92f67b4c08f9a58

Availability: https://doi.org/10.3390/electronics11142249
https://doaj.org/article/21672456c29445a9a92f67b4c08f9a58

Improved Heart Disease Prediction Using Particle Swarm Optimization Based Stacked Sparse Autoencoder

Authors: Ibomoiye Domor Mienye Yanxia Sun

Source: Electronics, Vol 10, Iss 2347, p 2347 (2021)

Subject Terms: deep learning, heart disease, particle swarm optimization, softmax regression, stacked sparse autoencoder, Electronics, TK7800-8360

Relation: https://www.mdpi.com/2079-9292/10/19/2347; https://doaj.org/toc/2079-9292; https://doaj.org/article/d151bef155304f508d8020b791b53a27

Availability: https://doi.org/10.3390/electronics10192347
https://doaj.org/article/d151bef155304f508d8020b791b53a27

SECONDARY PULMONARY TUBERCULOSIS RECOGNITION BY ROTATION ANGLE VECTOR GRID-BASED FRACTIONAL FOURIER ENTROPY: Secondary pulmonary tuberculosis recognition by rotation angle vector grid-based fractional Fourier entropy

Authors: Yeliz Karaca Yudong Zhang Shuihua Wang et al.

Source: Fractals. 30

Subject Terms: Biomedical imaging and signal processing, fractional Fourier entropy, deep learning, 02 engineering and technology, fractional Fourier transform, 3. Good health, multiple-way data augmentation, Fourier and Fourier-Stieltjes transforms and other transforms of Fourier type, Fractional derivatives and integrals, rotation angle vector grid, 0202 electrical engineering, electronic engineering, information engineering, secondary pulmonary tuberculosis, recognition, deep stacked sparse autoencoder

File Description: application/xml

Access URL: https://zbmath.org/7490683
https://doi.org/10.1142/s0218348x22400473
https://www.worldscientific.com/doi/pdf/10.1142/S0218348X22400473

Spectral-Spatial Classification of Hyperspectral Imagery Based on Stacked Sparse Autoencoder and Random Forest

Authors: Bing Cui Wu Liu Chunhui Zhao et al.

Source: European Journal of Remote Sensing, Vol 50, Iss 1, Pp 47-63 (2017)

Subject Terms: QE1-996.5, hyperspectral imagery, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, Geology, class separability, random forest (RF), GC1-1581, 02 engineering and technology, Classification, Oceanography, stacked sparse autoencoder (SSA)

Access URL: https://www.tandfonline.com/doi/pdf/10.1080/22797254.2017.1274566?needAccess=true
https://doaj.org/article/faa638bda2604ab5b97e5c23b587836a
https://tandfonline.com/doi/pdf/10.1080/22797254.2017.1274566
https://www.cabdirect.org/cabdirect/abstract/20183165789?q=(au%3A%22Qi+Bin%22)
https://tandfonline.com/doi/full/10.1080/22797254.2017.1274566

Construction of a Sensitive and Speed Invariant Gearbox Fault Diagnosis Model Using an Incorporated Utilizing Adaptive Noise Control and a Stacked Sparse Autoencoder-Based Deep Neural Network

Authors: Cong Dai Nguyen Alexander E. Prosvirin Cheol Hong Kim et al.

Source: Sensors, Vol 21, Iss 18, p 18 (2020)

Subject Terms: adaptive noise reducer, Gaussian reference signal, gearbox fault diagnosis, stacked sparse autoencoder–based deep neural network, varying rotational speed, Chemical technology, TP1-1185

Relation: https://www.mdpi.com/1424-8220/21/1/18; https://doaj.org/toc/1424-8220; https://doaj.org/article/0655be0ec3ba4534af97edb245871774

Availability: https://doi.org/10.3390/s21010018
https://doaj.org/article/0655be0ec3ba4534af97edb245871774

A Novel Order Analysis and Stacked Sparse Auto-Encoder Feature Learning Method for Milling Tool Wear Condition Monitoring

Authors: Jiayu Ou Hongkun Li Gangjin Huang et al.

Source: Sensors, Vol 20, Iss 2878, p 2878 (2020)

Subject Terms: order analysis, stacked sparse autoencoder, spindle current signals, tool wear condition monitoring, Chemical technology, TP1-1185

Relation: https://www.mdpi.com/1424-8220/20/10/2878; https://doaj.org/toc/1424-8220; https://doaj.org/article/2125b97e70e5493ea742dba66caf1895

Availability: https://doi.org/10.3390/s20102878
https://doaj.org/article/2125b97e70e5493ea742dba66caf1895

Deep Learning Based Retrieval of Forest Aboveground Biomass from Combined LiDAR and Landsat 8 Data

Authors: Linjing Zhang Zhenfeng Shao Jianchen Liu et al.

Source: Remote Sensing, Vol 11, Iss 12, p 1459 (2019)

Subject Terms: LiDAR, Landsat 8 OLI, combined optical and LiDAR indices, synergy, Stacked Sparse Autoencoder network (SSAE), forest aboveground biomass (AGB), Science

Relation: https://www.mdpi.com/2072-4292/11/12/1459; https://doaj.org/toc/2072-4292; https://doaj.org/article/f306008bbc1849e998fd17412f06d8fe

Availability: https://doi.org/10.3390/rs11121459
https://doaj.org/article/f306008bbc1849e998fd17412f06d8fe