A multi-objective neural network based method for cover crop identification from remote sensed data
- 21 February 2012
- journal article
- research article
- Published by Elsevier BV in Expert Systems with Applications
- Vol. 39 (11), 10038-10048
- https://doi.org/10.1016/j.eswa.2012.02.046
Abstract
No abstract availableKeywords
Funding Information
- Ministerio de Ciencia e Innovación (AGL2011–30442-CO2–01)
- Comisión Interministerial de Ciencia y Tecnología (TIN2011–22794)
- European Regional Development Fund
- Junta de Andalucía (P2011-TIC-7508)
- Ministério da Educação e Ciência (AP2009–0487)
This publication has 49 references indexed in Scilit:
- A logistic radial basis function regression method for discrimination of cover crops in olive orchardsExpert Systems with Applications, 2010
- From pixel to vine parcel: A complete methodology for vineyard delineation and characterization using remote-sensing dataComputers and Electronics in Agriculture, 2009
- Distinguishing blueberry bushes from mixed vegetation land use using high resolution satellite imagery and geospatial techniquesComputers and Electronics in Agriculture, 2009
- Mapping sunflower yield as affected by Ridolfia segetum patches and elevation by applying evolutionary product unit neural networks to remote sensed dataComputers and Electronics in Agriculture, 2008
- Multi-class pattern classification using neural networksPattern Recognition, 2006
- Weed detection in multi-spectral images of cotton fieldsComputers and Electronics in Agriculture, 2005
- Discrimination of weed seedlings, wheat (Triticum aestivum) stubble and sunflower (Helianthus annuus) by near-infrared reflectance spectroscopy (NIRS)Crop Protection, 2003
- Empirical evaluation of the improved Rprop learning algorithmsNeurocomputing, 2002
- Improving generalization of MLPs with multi-objective optimizationNeurocomputing, 2000
- Land degradation, soil erosion and desertification monitoring in Mediterranean ecosystemsRemote Sensing Reviews, 1995