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Tri-aural Perception: A Comparison of Neural Network and Maximum Likelihood Algorithms to Solve the Correspondence Problem. Proceedings of the European Symposium on Optics for Productivity in Manufacturing, p. 11, Frankfurt, 1994.

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MLA
Peremans, Herbert, and J. CHEN. Tri-Aural Perception: A Comparison of Neural Network and Maximum Likelihood Algorithms to Solve the Correspondence Problem. Proceedings of the European Symposium on Optics for Productivity in Manufacturing, p. 11, Frankfurt, 1994.
APA
Peremans, H., & CHEN, J. (n.d.). Tri-aural Perception: A Comparison of Neural Network and Maximum Likelihood Algorithms to Solve the Correspondence Problem. Proceedings of the European Symposium on Optics for Productivity in Manufacturing, p. 11, Frankfurt, 1994.
Chicago author-date
Peremans, Herbert, and J CHEN. n.d. “Tri-Aural Perception: A Comparison of Neural Network and Maximum Likelihood Algorithms to Solve the Correspondence Problem. Proceedings of the European Symposium on Optics for Productivity in Manufacturing, p. 11, Frankfurt, 1994.” In .
Chicago author-date (all authors)
Peremans, Herbert, and J CHEN. “Tri-Aural Perception: A Comparison of Neural Network and Maximum Likelihood Algorithms to Solve the Correspondence Problem. Proceedings of the European Symposium on Optics for Productivity in Manufacturing, p. 11, Frankfurt, 1994.” In .
Vancouver
1.
Peremans H, CHEN J. Tri-aural Perception: A Comparison of Neural Network and Maximum Likelihood Algorithms to Solve the Correspondence Problem. Proceedings of the European Symposium on Optics for Productivity in Manufacturing, p. 11, Frankfurt, 1994. In.
IEEE
[1]
H. Peremans and J. CHEN, “Tri-aural Perception: A Comparison of Neural Network and Maximum Likelihood Algorithms to Solve the Correspondence Problem. Proceedings of the European Symposium on Optics for Productivity in Manufacturing, p. 11, Frankfurt, 1994.”
@inproceedings{246110,
  author       = {{Peremans, Herbert and CHEN, J}},
  language     = {{eng}},
  title        = {{Tri-aural Perception: A Comparison of Neural Network and Maximum Likelihood Algorithms to Solve the Correspondence Problem. Proceedings of the European Symposium on Optics for Productivity in Manufacturing, p. 11, Frankfurt, 1994.}},
}