Suchergebnisse - "stacked denoising autoencoder neural network"

Traffic Image Analysis Based on Stacked Denoising Autoencoder Neural Network

Autoren: Daehyon Kim

Quelle: Journal of Innovation Information Technology and Application, Vol 5, Iss 2, Pp 183-192 (2023)

Schlagwörter: autoencoding, deep belief network, neural network, Electronic computers. Computer science, 0502 economics and business, 05 social sciences, stacked denoising, 0202 electrical engineering, electronic engineering, information engineering, Information technology, QA75.5-76.95, 02 engineering and technology, T58.5-58.64, backpropagation

Zugangs-URL: https://doaj.org/article/fabc870fc1524bf4a89ecb4aaed0ca7a

Identifying marsh dieback events from Landsat image series (1998–2018) with an Autoencoder in the NIWB estuary, South Carolina.

Autoren: Li, Huixuan Wang, Cuizhen Ellis, Jean T. et al.

Quelle: International Journal of Digital Earth; Dec2020, Vol. 13 Issue 12, p1467-1483, 17p

Schlagwörter: DIEBACK, NORMALIZED difference vegetation index, MARSHES, ESTUARIES, TIDAL flats

Geografische Kategorien: SOUTH Carolina, PERSIAN Gulf

Survey of Research on SMOTE Type Algorithms. (English)

Autoren: WANG Xiaoxia LI Leixiao LIN Hao

Quelle: Journal of Frontiers of Computer Science & Technology; May2024, Vol. 18 Issue 5, p1135-1159, 25p

Schlagwörter: ALGORITHMS, DATA distribution

An imbalanced data classification algorithm of improved autoencoder neural network.

Autoren: Zhang, Chenggang Gao, Wei Song, Jiazhi et al.

Quelle: 2016 Eighth International Conference on Advanced Computational Intelligence (ICACI); 2016, p95-99, 5p

Stacked Denoising Autoencoders Applied to Star/Galaxy Classification.

Autoren: Hao-ran, Qin Ji-ming, Lin Jun-yi, Wang

Quelle: Chinese Astronomy & Astrophysics. Apr2017, Vol. 41 Issue 2, p282-292. 11p.

Schlagwörter: *SIGNAL denoising, *DEEP learning, *COMPUTATIONAL complexity, *MILKY Way

Firma/Körperschaft: SLOAN Digital Sky Survey

Hyperspectral Imaging Combined with Convolutional Neural Network for Rapid and Accurate Evaluation of Tilapia Fillet Freshness.

Autoren: Shuqi Tang Peng Li Shenghui Chen et al.

Quelle: Spectroscopy; Nov/Dec2024, Vol. 39 Issue 8, p36-60, 9p

Schlagwörter: CONVOLUTIONAL neural networks, EXTREME learning machines, MACHINE learning, SUPPORT vector machines, K-nearest neighbor classification

Bayesian Fusion Model Enhanced Codfish Classification Using Near Infrared and Raman Spectrum.

Autoren: Xu, Yi Koidis, Anastasios Tian, Xingguo et al.

Quelle: Foods; Dec2022, Vol. 11 Issue 24, p4100, 17p

Schlagwörter: RAMAN spectroscopy, INFRARED spectra, CODFISH, RAMAN scattering, DISCRIMINANT analysis, MULTISENSOR data fusion

The role of machine learning applications in diagnosing and assessing critical and non-critical CHD: a scoping review.

Autoren: Helman, Stephanie M. Herrup, Elizabeth A. Christopher, Adam B. et al.

Quelle: Cardiology in the Young; Nov2021, Vol. 31 Issue 11, p1770-1780, 11p

Application of VIS/NIR Spectroscopy and SDAE-NN Algorithm for Predicting the Cold Storage Time of Salmon

Autoren: Ting Wu Nan Zhong Ling Yang

Quelle: Journal of Spectroscopy, Vol 2018 (2018)

Schlagwörter: 2. Zero hunger, 0404 agricultural biotechnology, QC350-467, 04 agricultural and veterinary sciences, Optics. Light, 0405 other agricultural sciences

Dateibeschreibung: text/xhtml

Zugangs-URL: http://downloads.hindawi.com/journals/jspec/2018/7450695.pdf
https://doaj.org/article/8ca9afaad1384938a7247ec2e0fcc881
https://www.hindawi.com/journals/jspec/2018/7450695/
https://downloads.hindawi.com/journals/jspec/2018/7450695.pdf
http://downloads.hindawi.com/journals/jspec/2018/7450695.pdf
https://paperity.org/p/129714953/application-of-vis-nir-spectroscopy-and-sdae-nn-algorithm-for-predicting-the-cold-storage
https://core.ac.uk/display/157794598

An imbalanced data classification algorithm of improved autoencoder neural network

Autoren: Jinqing Jiang Chenggang Zhang Jiazhi Song et al.

Quelle: 2016 Eighth International Conference on Advanced Computational Intelligence (ICACI). :95-99

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

Zugangs-URL: https://ieeexplore.ieee.org/abstract/document/7449810
http://ieeexplore.ieee.org/document/7449810/
https://dblp.uni-trier.de/db/conf/icaci/icaci2016.html#ZhangGSJ16
https://doi.org/10.1109/ICACI.2016.7449810

Indoor Motion State Recognition using Denoising Autoencoders on Smartphone

Autoren: H. B. Lu Y. Lu C. B. Tao et al.

Quelle: 2018 International Computers, Signals and Systems Conference (ICOMSSC). :743-745

Schlagwörter: 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=8941962
http://xplorestaging.ieee.org/ielx7/8935453/8941585/08941962.pdf?arnumber=8941962

Satellite Observations and Spatiotemporal Assessment of Salt Marsh /Dieback Along Coastal South Carolina (1990-2019)

Autoren: Li, Huixuan

Quelle: Theses and Dissertations

Schlagwörter: Coastal South Carolina, salt, satellite, Spatiotemporal Assessment, Geography

Dateibeschreibung: application/pdf

Relation: https://scholarcommons.sc.edu/etd/6751; https://scholarcommons.sc.edu/context/etd/article/7464/viewcontent/Li_sc_0202A_17830.pdf

Verfügbarkeit: https://scholarcommons.sc.edu/etd/6751
https://scholarcommons.sc.edu/context/etd/article/7464/viewcontent/Li_sc_0202A_17830.pdf

Sensing Technology for Fish Freshness and Safety: A Review.

Autoren: Franceschelli, Leonardo Berardinelli, Annachiara Dabbou, Sihem et al.

Quelle: Sensors (14248220); 2/15/2021, Vol. 21 Issue 4, p1373-1373, 1p

Schlagwörter: FISH spoilage, FOOD quality, MEAT texture, TECHNICAL reports, PHYSICAL measurements

Industry 4.0 in Small and Medium-Sized Enterprises (SMEs) : Opportunities, Challenges, and Solutions

Autoren: Ketan Kotecha Satish Kumar Arunkumar Bongale et al.

Resource Type: eBook.

Schlagworte: Industry 4.0, Small business--Management

Categories: BUSINESS & ECONOMICS / Workplace Culture, TECHNOLOGY & ENGINEERING / Industrial Engineering, TECHNOLOGY & ENGINEERING / Industrial Design / General, TECHNOLOGY & ENGINEERING / Manufacturing