Comparison of a Bayesian classifier with a multilayer feed-forward neural network using the example of plant/weed/soil discrimination-Reference-Cited by-同舟云学术

Comparison of a Bayesian classifier with a multilayer feed-forward neural network using the example of plant/weed/soil discrimination

Published:2003-04 Issue:1 Volume:39 Page:3-22
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Marchant J.A,Onyango C.M

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference19 articles.

1. Machine vision for precise control of weeds;Blasco;Proc. SPIE,1998

2. Brivot, R., Marchant, J.A., 1996. Segmentation of plants and weeds using infrared images. In: Proceedings of the Institution of Electrical Engineers. Vision, Image Signal Process. 143 (2), 118–124.

3. Neural Network Toolbox: User's Guide;Dumuth,2000

4. Digital Image Processing;Gonzales,1992

5. Hague, T., Marchant, J.A., Tillett, N.D., 1997. A system for plant scale husbandry. In: Proceedings of the First European Conference on Precision Agriculture, September 7–10, Warwick, UK, pp. 635–642.

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