@ARTICLE{Rodríguez-Quiñonez_J.C._Improve_2017,
 author={Rodríguez-Quiñonez, J.C. and Sergiyenko, O. and Flores-Fuentes, W. and Rivas-lopez, M. and Hernandez-Balbuena, D. and Rascón, R. and Mercorelli, P.},
 volume={vol. 25},
 number={No 1},
 journal={Opto-Electronics Review},
 pages={24-32},
 howpublished={online},
 year={2017},
 publisher={Polish Academy of Sciences (under the auspices of the Committee on Electronics and Telecommunication) and Association of Polish Electrical Engineers in cooperation with Military University of Technology},
 abstract={This paper presents a 3D distance measurement accuracy improvement for stereo vision systems using optimization methods A Stereo Vision system is developed and tested to identify common uncertainty sources. As the optimization methods are used to train a neural network, the resulting equation can be implemented in real time stereo vision systems. Computational experiments and a comparative analysis are conducted to identify a training function with a minimal error performance for such method. The offered method provides a general purpose modelling technique, attending diverse problems that affect stereo vision systems. Finally, the proposed method is applied in the developed stereo vision system and a statistical analysis is performed to validate the obtained improvements.},
 type={Article},
 title={Improve a 3D distance measurement accuracy in stereo vision systems using optimization methods’ approach},
 URL={http://ochroma.man.poznan.pl/Content/115341/PDF/main.pdf},
 keywords={Stereo vision, Optimization methods, Distance measurement},
}