A. G. Ivakhnenko, “The review of problems solvable by algorithms of the group method of data handling (GMDH),” Pattern Recogn. Image Anal. 5, 527–535 (1995).

M. T. Hagan and M. B. Menhaj, “Training feed forward networks with the Marquardt algorithm,” IEEE Trans. Neural Netw. 5, 989–993 (1994).

[CrossRef]

J. Weng, P. Cohen, and M. Herniou, “Camera calibration with distortion models and accuracy evaluation,” IEEE Trans. Pattern Anal. Machine Intell. 14, 965–980 (1992).

[CrossRef]

M. B. Lynch and C. H. Dagli, “Back propagation neural network for stereoscopic vision calibration,” Proc. SPIE 8194, 289–298 (1991).

A. Hirotugu, “A new look at the statistical model identification,” IEEE Trans. Autom. Control 19, 716–723 (1974).

[CrossRef]

A. G. Ivakhnenko, “Polynomial theory of complex systems,” IEEE Trans. Syst. Man Cybernet. 1, 364–378 (1971).

[CrossRef]

M. T. Ahmed, E. E. Hemayed, and A. A. Farag, “Neurocalibration: a neural network that can tell camera calibration parameters,” in Proceedings of IEEE Conference on Computer Vision (IEEE, 1999), pp. 463–468.

J. I. González, J. C. Gámez, C. G. Artal, and A. M. N. Cabrera, “Stability study of camera calibration methods,” in Proceedings of CI Workshop en Agentes Fisicos (WAF), Spain, 2005, pp. 1–8.

J. I. González, J. C. Gámez, C. G. Artal, and A. M. N. Cabrera, “Stability study of camera calibration methods,” in Proceedings of CI Workshop en Agentes Fisicos (WAF), Spain, 2005, pp. 1–8.

D. Ge, X. Yao, and W. Chen, “Research of machine vision system based on RBF neural network,” in Proceedings of Computer Science and Information Technology, Singapore, 2008, pp. 218–222.

J. Weng, P. Cohen, and M. Herniou, “Camera calibration with distortion models and accuracy evaluation,” IEEE Trans. Pattern Anal. Machine Intell. 14, 965–980 (1992).

[CrossRef]

M. B. Lynch and C. H. Dagli, “Back propagation neural network for stereoscopic vision calibration,” Proc. SPIE 8194, 289–298 (1991).

E.-S. M. El-Alfy, “A hierarchical GMDH-based polynomial neural network for handwritten numeral recognition using topological features,” in Proceedings of Neural Networks, Barcelona, 2010, pp. 1–7.

M. T. Ahmed, E. E. Hemayed, and A. A. Farag, “Neurocalibration: a neural network that can tell camera calibration parameters,” in Proceedings of IEEE Conference on Computer Vision (IEEE, 1999), pp. 463–468.

J. I. González, J. C. Gámez, C. G. Artal, and A. M. N. Cabrera, “Stability study of camera calibration methods,” in Proceedings of CI Workshop en Agentes Fisicos (WAF), Spain, 2005, pp. 1–8.

D. Ge, X. Yao, and W. Chen, “Research of machine vision system based on RBF neural network,” in Proceedings of Computer Science and Information Technology, Singapore, 2008, pp. 218–222.

J. I. González, J. C. Gámez, C. G. Artal, and A. M. N. Cabrera, “Stability study of camera calibration methods,” in Proceedings of CI Workshop en Agentes Fisicos (WAF), Spain, 2005, pp. 1–8.

M. T. Hagan and M. B. Menhaj, “Training feed forward networks with the Marquardt algorithm,” IEEE Trans. Neural Netw. 5, 989–993 (1994).

[CrossRef]

M. T. Ahmed, E. E. Hemayed, and A. A. Farag, “Neurocalibration: a neural network that can tell camera calibration parameters,” in Proceedings of IEEE Conference on Computer Vision (IEEE, 1999), pp. 463–468.

J. Weng, P. Cohen, and M. Herniou, “Camera calibration with distortion models and accuracy evaluation,” IEEE Trans. Pattern Anal. Machine Intell. 14, 965–980 (1992).

[CrossRef]

A. Hirotugu, “A new look at the statistical model identification,” IEEE Trans. Autom. Control 19, 716–723 (1974).

[CrossRef]

A. G. Ivakhnenko, “The review of problems solvable by algorithms of the group method of data handling (GMDH),” Pattern Recogn. Image Anal. 5, 527–535 (1995).

A. G. Ivakhnenko, “Polynomial theory of complex systems,” IEEE Trans. Syst. Man Cybernet. 1, 364–378 (1971).

[CrossRef]

G. Jekabsons, “Adaptive basis function construction: an approach for adaptive building of sparse polynomial regression models,” in Machine Learning, Y. Zhang, ed. (InTech, 2010), pp. 127–155.

M. B. Lynch and C. H. Dagli, “Back propagation neural network for stereoscopic vision calibration,” Proc. SPIE 8194, 289–298 (1991).

M. T. Hagan and M. B. Menhaj, “Training feed forward networks with the Marquardt algorithm,” IEEE Trans. Neural Netw. 5, 989–993 (1994).

[CrossRef]

J. Wen and G. Schweitzer, “Hybrid calibration of CCD cameras using artificial neural nets,” in Proceedings of Neural Networks, Singapore, 1991, pp. 337–342.

J. Wen and G. Schweitzer, “Hybrid calibration of CCD cameras using artificial neural nets,” in Proceedings of Neural Networks, Singapore, 1991, pp. 337–342.

J. Weng, P. Cohen, and M. Herniou, “Camera calibration with distortion models and accuracy evaluation,” IEEE Trans. Pattern Anal. Machine Intell. 14, 965–980 (1992).

[CrossRef]

D. Ge, X. Yao, and W. Chen, “Research of machine vision system based on RBF neural network,” in Proceedings of Computer Science and Information Technology, Singapore, 2008, pp. 218–222.

A. Hirotugu, “A new look at the statistical model identification,” IEEE Trans. Autom. Control 19, 716–723 (1974).

[CrossRef]

M. T. Hagan and M. B. Menhaj, “Training feed forward networks with the Marquardt algorithm,” IEEE Trans. Neural Netw. 5, 989–993 (1994).

[CrossRef]

J. Weng, P. Cohen, and M. Herniou, “Camera calibration with distortion models and accuracy evaluation,” IEEE Trans. Pattern Anal. Machine Intell. 14, 965–980 (1992).

[CrossRef]

A. G. Ivakhnenko, “Polynomial theory of complex systems,” IEEE Trans. Syst. Man Cybernet. 1, 364–378 (1971).

[CrossRef]

A. G. Ivakhnenko, “The review of problems solvable by algorithms of the group method of data handling (GMDH),” Pattern Recogn. Image Anal. 5, 527–535 (1995).

M. B. Lynch and C. H. Dagli, “Back propagation neural network for stereoscopic vision calibration,” Proc. SPIE 8194, 289–298 (1991).

D. Ge, X. Yao, and W. Chen, “Research of machine vision system based on RBF neural network,” in Proceedings of Computer Science and Information Technology, Singapore, 2008, pp. 218–222.

J. Wen and G. Schweitzer, “Hybrid calibration of CCD cameras using artificial neural nets,” in Proceedings of Neural Networks, Singapore, 1991, pp. 337–342.

J. I. González, J. C. Gámez, C. G. Artal, and A. M. N. Cabrera, “Stability study of camera calibration methods,” in Proceedings of CI Workshop en Agentes Fisicos (WAF), Spain, 2005, pp. 1–8.

E.-S. M. El-Alfy, “A hierarchical GMDH-based polynomial neural network for handwritten numeral recognition using topological features,” in Proceedings of Neural Networks, Barcelona, 2010, pp. 1–7.

M. Lourakis, “Levmar,” http://www.ics.forth.gr/~lourakis/levmar/ .

G. Jekabsons, “Adaptive basis function construction: an approach for adaptive building of sparse polynomial regression models,” in Machine Learning, Y. Zhang, ed. (InTech, 2010), pp. 127–155.

M. T. Ahmed, E. E. Hemayed, and A. A. Farag, “Neurocalibration: a neural network that can tell camera calibration parameters,” in Proceedings of IEEE Conference on Computer Vision (IEEE, 1999), pp. 463–468.