Publications

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Arribas, J. I., J. Cid-Sueiro, T. Adali, and A. R. Figueiras-Vidal, "Neural networks to estimate ML multi-class constrained conditional probability density functions", Proceedings of the International Joint Conference on Neural Networks, Washington, DC, USA, IEEE, United States, 1999.
Wu, Y., J. He, Y. Man, and J. I. Arribas, "Neural network fusion strategies for identifying breast masses", IEEE International Conference on Neural Networks - Conference Proceedings, Budapest, 2004.
Arribas, J. I., J. Cid-Sueiro, T. Adali, and A. R. Figueiras-Vidal, "Neural architectures for parametric estimation of a posteriori probabilities by constrained conditional density functions", Neural Networks for Signal Processing - Proceedings of the IEEE Workshop, Madison, WI, USA, IEEE, Piscataway, NJ, United States, 1999.
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Arribas, J. I., G. V. Sanchez-Ferrero, G. Ruiz-Ruiz, and J. Gomez-Gil, "Leaf classification in sunflower crops by computer vision and neural networks", Computers and Electronics in Agriculture, vol. 78, pp. 9-18, 2011.
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Wu, Y., and J. I. Arribas, "Fusing Output Information in Neural Networks: Ensemble Performs Better", Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, Cancun, 2003.
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Alonso-Garcia, S., J. Gomez-Gil, and J. I. Arribas, "Evaluation of the use of low-cost GPS receivers in the autonomous guidance of agricultural tractors", Spanish Journal of Agricultural Research, vol. 9, pp. 377-388, 2011.
Arribas, J. I., J. Cid-Sueiro, and C. Alberola-Lopez, "Estimation of Posterior Probabilities with Neural Networks: Application to Microcalcification Detection in Breast Cancer Diagnosis", Handbook of Neural Engineering: John Wiley & Sons, Inc., pp. 41-58, 2006.
Arribas, J. I., J. Cid-Sueiro, and C. Alberola-Lopez, "Estimation of Posterior Probabilities with Neural Networks: Application to Microcalcification Detection in Breast Cancer Diagnosis", Handbook of Neural Engineering: Wiley Online Library, pp. 41–58, 2005.
Arribas, J. I., J. Cid-Sueiro, T. Adali, H. Ni, B. Wang, and A. R. Figueiras-Vidal, "Estimates of constrained multi-class a posteriori probabilities in time series problems with neural networks", Proceedings of the International Joint Conference on Neural Networks, Washington, DC, USA, IEEE, United States, 1999.
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Cid-Sueiro, J., J. I. Arribas, S. Urban-Munoz, and A. R. Figueiras-Vidal, "Cost functions to estimate a posteriori probabilities in multiclass problems", IEEE Transactions on Neural Networks, vol. 10, pp. 645-656, 1999.
Sabzi, S., R. Pourdarbani, and J. I. Arribas, "A Computer Vision System for the Automatic Classification of Five Varieties of Tree Leaf Images", Computers, vol. 9, pp. 6, 2020.
Pourdarbani, R., S. Sabzi, D. Kalantari, J. Luis Hernández-Hernández, and J. I. Arribas, "A Computer Vision System Based on Majority-Voting Ensemble Neural Network for the Automatic Classification of Three Chickpea Varieties", Foods, vol. 9, pp. 113, 2020.
A
Pourdarbani, R., S. Sabzi, D. Kalantari, R. Karimzadeh, E. Ilbeygi, and J. I. Arribas, "Automatic non-destructive video estimation of maturation levels in Fuji apple (Malus Malus pumila) fruit in orchard based on colour (Vis) and spectral (NIR) data", Biosystems Engineering, vol. 195, pp. 136–151, 2020.
Arribas, J. I., V. D. Calhoun, and T. Adali, "Automatic bayesian classification of healthy controls, bipolar disorder, and schizophrenia using intrinsic connectivity maps from fMRI data", IEEE Transactions on Biomedical Engineering, vol. 57, pp. 2850-2860, 2010.
Sabzi, S., Y. Abbaspour-Gilandeh, G. Garcia-Mateos, A. Ruiz-Canales, J. M. Molina-Martinez, and J. I. Arribas, "An Automatic Non-Destructive Method for the Classification of the Ripeness Stage of Red Delicious Apples in Orchards Using Aerial Video", Agronomy, vol. 9, issue 84, 2019.
Leal-Campanario, R., L. Alarcon-Martinez, H. Rieiro, S. Martinez-Conde, T. Alarcon-Martinez, X. Zhao, J. LaMee, P.J. Popp, M.E. Calhoun, J. I. Arribas, et al., "Abnormal Capillary Vasodynamics Contribute to Ictal Neurodegeneration in Epilepsy", Scientific Reports, vol. 7, 2017.

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