Publicaciones en las que colabora con Alberto Tellaeche Iglesias (12)

2011

  1. A computer vision approach for weeds identification through Support Vector Machines

    Applied Soft Computing Journal, Vol. 11, Núm. 1, pp. 908-915

2010

  1. Analysis of natural images processing for the extraction of agricultural elements

    Image and Vision Computing, Vol. 28, Núm. 1, pp. 138-149

  2. On combining vision-based hybrid classifiers for weeds detection in precision agriculture

    International Journal of Reasoning-based Intelligent Systems, Vol. 2, Núm. 2, pp. 100-109

2009

  1. Improving weed pressure assessment using digital images from an experience-based reasoning approach

    Computers and Electronics in Agriculture, Vol. 65, Núm. 2, pp. 176-185

2008

  1. A new vision-based approach to differential spraying in precision agriculture

    Computers and Electronics in Agriculture, Vol. 60, Núm. 2, pp. 144-155

  2. A vision-based method for weeds identification through the Bayesian decision theory

    Pattern Recognition, Vol. 41, Núm. 2, pp. 521-530

  3. Optimisation of natural images processing using different evolutionary algorithms

    2008 IEEE Congress on Evolutionary Computation, CEC 2008

2007

  1. A vision-based classifier in precision agriculture combining Bayes and support vector machines

    2007 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING, CONFERENCE PROCEEDINGS BOOK

  2. A vision-based classifier in precision agriculture combining bayes and support vector machines

    2007 IEEE International Symposium on Intelligent Signal Processing, WISP

  3. A vision-based hybrid classifier for weeds detection in precision agriculture through the Bayesian and Fuzzy k-Means paradigms

    INNOVATIONS IN HYBRID INTELLIGENT SYSTEMS

  4. A vision-based hybrid classifier for weeds detection in precision agriculture through the bayesian and fuzzy k-Means paradigms

    Advances in Soft Computing

  5. Design of a computer vision system for a differential spraying operation in precision agriculture using Hebbian learning

    IET Computer Vision, Vol. 1, Núm. 3-4, pp. 93-99