Wavelet filtering of time-series moderate resolution imaging spectroradiometer data for rice crop mapping using support vector machines and maximum likelihood classifier

Chi-Farn Chen

doi:10.1117/1.3595272

Wavelet filtering of time-series moderate resolution imaging spectroradiometer data for rice crop mapping using support vector machines and maximum likelihood classifier

Journal of Applied Remote Sensing ◽

10.1117/1.3595272 ◽

2011 ◽

Vol 5 (1) ◽

pp. 053525 ◽

Cited By ~ 13

Author(s):

Chi-Farn Chen

Keyword(s):

Time Series ◽

Support Vector Machines ◽

Maximum Likelihood ◽

Support Vector ◽

Vector Machines ◽

Maximum Likelihood Classifier ◽

Moderate Resolution ◽

Resolution Imaging ◽

Crop Mapping ◽

Moderate Resolution Imaging Spectroradiometer

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Exploiting the Classification Performance of Support Vector Machines with Multi-Temporal Moderate-Resolution Imaging Spectroradiometer (MODIS) Data in Areas of Agreement and Disagreement of Existing Land Cover Products

Remote Sensing ◽

10.3390/rs4103143 ◽

2012 ◽

Vol 4 (10) ◽

pp. 3143-3167 ◽

Cited By ~ 15

Author(s):

Francesco Vuolo ◽

Clement Atzberger

Keyword(s):

Support Vector Machines ◽

Land Cover ◽

Classification Performance ◽

Support Vector ◽

Modis Data ◽

Vector Machines ◽

Multi Temporal ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer

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Impact of Internal Parameterization on the Performance of Support Vector Machines for Crop Mapping Sentinel-2 NDVI Time Series

Proceedings of the 2nd International Conference on Advanced Technologies for Humanity ◽

10.5220/0010426300050010 ◽

2020 ◽

Author(s):

Badreddine Sebbar ◽

Aicha Moumni ◽

Abderrahman Lahrouni

Keyword(s):

Time Series ◽

Support Vector Machines ◽

Support Vector ◽

Vector Machines ◽

Ndvi Time Series ◽

Crop Mapping ◽

Sentinel 2

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Modified support vector machines in financial time series forecasting

Neurocomputing ◽

10.1016/s0925-2312(01)00676-2 ◽

2002 ◽

Vol 48 (1-4) ◽

pp. 847-861 ◽

Cited By ~ 247

Author(s):

Francis E.H. Tay ◽

L.J. Cao

Keyword(s):

Time Series ◽

Support Vector Machines ◽

Financial Time Series ◽

Time Series Forecasting ◽

Support Vector ◽

Financial Time ◽

Vector Machines

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Sensitivity analysis for time lag selection to forecast seasonal time series using Neural Networks and Support Vector Machines

The 2010 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2010.5596890 ◽

2010 ◽

Cited By ~ 14

Author(s):

Paulo Cortez

Keyword(s):

Neural Networks ◽

Time Series ◽

Sensitivity Analysis ◽

Support Vector Machines ◽

Time Lag ◽

Support Vector ◽

Seasonal Time Series ◽

Lag Selection ◽

Vector Machines

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Directional Forecasting in Financial Time Series Using Support Vector Machines: The USD/EURO Exchange Rate

SSRN Electronic Journal ◽

10.2139/ssrn.2387655 ◽

2011 ◽

Author(s):

Vasilios Plakandaras ◽

Periklis Gogas ◽

Theophilos Papadimitriou

Keyword(s):

Time Series ◽

Exchange Rate ◽

Support Vector Machines ◽

Financial Time Series ◽

Support Vector ◽

Financial Time ◽

Vector Machines

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Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series

International Journal of Applied Earth Observation and Geoinformation ◽

10.1016/j.jag.2018.02.010 ◽

2018 ◽

Vol 69 ◽

pp. 148-163 ◽

Cited By ~ 10

Author(s):

Marcos Adami ◽

Sérgio Bernardes ◽

Egidio Arai ◽

Ramon M. Freitas ◽

Yosio E. Shimabukuro ◽

...

Keyword(s):

Time Series ◽

South America ◽

Vegetation Types ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer

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Support Vector Machines of Interval-based Features for Time Series Classification

Research and Development in Intelligent Systems XXI ◽

10.1007/1-84628-102-4_18 ◽

2007 ◽

pp. 244-257 ◽

Cited By ~ 2

Author(s):

Juan José Rodríguez ◽

Carlos J. Alonso

Keyword(s):

Time Series ◽

Support Vector Machines ◽

Support Vector ◽

Time Series Classification ◽

Vector Machines

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Feature Selection for Support Vector Machines in Financial Time Series Forecasting

Intelligent Data Engineering and Automated Learning — IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents - Lecture Notes in Computer Science ◽

10.1007/3-540-44491-2_38 ◽

2000 ◽

pp. 268-273 ◽

Cited By ~ 5

Author(s):

L. J. Cao ◽

Francis E. H. Tay

Keyword(s):

Time Series ◽

Feature Selection ◽

Support Vector Machines ◽

Financial Time Series ◽

Time Series Forecasting ◽

Support Vector ◽

Financial Time ◽

Vector Machines ◽

Selection For

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A New Hyper-parameters Selection Approach for Support Vector Machines to Predict Time Series

Pervasive Computing and the Networked World - Lecture Notes in Computer Science ◽

10.1007/978-3-642-37015-1_68 ◽

2013 ◽

pp. 775-787 ◽

Cited By ~ 1

Author(s):

Yanhua Yu ◽

Junde Song ◽

Zhijun Ren

Keyword(s):

Time Series ◽

Support Vector Machines ◽

Support Vector ◽

Parameters Selection ◽

Vector Machines ◽

Selection Approach

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Nonlinear Noise Reduction of Chaotic Time Series Based on Multi-dimensional Recurrent Least Squares Support Vector Machines

Neural Information Processing - Lecture Notes in Computer Science ◽

10.1007/11893028_100 ◽

2006 ◽

pp. 900-906 ◽

Cited By ~ 3

Author(s):

Jiancheng Sun ◽

Yatong Zhou ◽

Yaohui Bai ◽

Jianguo Luo

Keyword(s):

Time Series ◽

Support Vector Machines ◽

Noise Reduction ◽

Least Squares ◽

Chaotic Time Series ◽

Support Vector ◽

Vector Machines ◽

Nonlinear Noise

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