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ORCIDJulián A. Pucheta
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- affiliation: National University of Cordoba, Argentina
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2020 – today
- 2021
[c11]Julián A. Pucheta
, Sergio Laboret, H. Daniel Patiño, Carlos A. Salas, Cristian Rodriguez Rivero, Martín R. Herrera:
Dynamic model change analysis of social behavior processes during the COVID19 pandemic. CSCI 2021: 1381-1387- 2020
- [c10]Cristian Rodriguez Rivero, Julián A. Pucheta, H. Daniel Patiño, Paula Otaño, Leonardo Franco, Gustavo Juárez:
Short-Term Rainfall Forecasting with E-LSTM Recurrent Neural Networks Using Small Datasets. ICIC (3) 2020: 258-270
2010 – 2019
- 2017
- [j5]Cristian Rodrìguez Rivero, Juliàn A. Pucheta, Sergio Laboret, Vìctor Sauchelli, H. Daniel Patiño:
Energy Associated Tuning Method for Short-Term Series Forecasting by Complete and Incomplete Datasets. J. Artif. Intell. Soft Comput. Res. 7(1): 5 (2017) - [c9]Cristian Rodriguez Rivero, Yván Túpac, Julián A. Pucheta, Gustavo Juárez, Leonardo Franco, Paula Otaño:
Time-series prediction with BEMCA approach: Application to short rainfall series. LA-CCI 2017: 1-6 - 2016
- [j4]Josef Baumgartner, Ana Georgina Flesia, Javier Gimenez, Julián A. Pucheta:
A new image segmentation framework based on two-dimensional hidden Markov models. Integr. Comput. Aided Eng. 23(1): 1-13 (2016) - [c8]Cristian Rodriguez Rivero, Julián A. Pucheta, Sergio Laboret, Vìctor Sauchelli, Alvaro David Orjuela-Cañón, Leonardo Franco:
Noisy chaotic time series forecast approximated by combining Reny's entropy with energy associated to series method: Application to rainfall series. LA-CCI 2016: 1-6 - 2015
- [j3]Josef Baumgartner, Javier Gimenez, Marcelo C. Scavuzzo, Julián A. Pucheta:
A New Approach to Segmentation of Multispectral Remote Sensing Images Based on MRF. IEEE Geosci. Remote. Sens. Lett. 12(8): 1720-1724 (2015) - [c7]Javier A. Redolfi, Jorge A. Sánchez, Julián A. Pucheta:
Fisher Vectors for Leaf Image Classification: An Experimental Evaluation. CIARP 2015: 298-305 - [c6]Marc Thibeault, Juan Manuel Caceres, Danilo Dadamia, Alvaro G. Soldano, Marcelo Uriburu Quirno, Juan Martin Guerrieri, Rodrigo Edrosa, Matias Palomeque, Luciano Romaldi, Julián A. Pucheta, Jonatan Mogadouro, Ezequiel De Luca, Santiago Bustos Revol, Sebastián Aguero, Ignacio Pascual, Mauro Mariotti d'Alessandro:
Spatial and temporal analysis of the Monte Buey SAOCOM and SMAP core site. IGARSS 2015: 969-971 - [c5]Cristian Rodriguez Rivero, Hector Daniel Patiño, Juliàn Antonio Pucheta:
Short-term rainfall time series prediction with incomplete data. IJCNN 2015: 1-6 - 2013
- [c4]Cristian Rodrìguez Rivero, Julián A. Pucheta, Hector D. Patiño, Josef Baumgartner, Sergio Laboret, Vìctor Sauchelli:
Analysis of a Gaussian process and feed-forward neural networks based filter for forecasting short rainfall time series. IJCNN 2013: 1-6 - 2011
- [j2]Julián A. Pucheta, Cristian Rodrìguez Rivero, Martín R. Herrera, Carlos A. Salas, H. Daniel Patiño, Benjamín R. Kuchen:
A Feed-Forward Neural Networks-Based Nonlinear Autoregressive Model for Forecasting Time Series. Computación y Sistemas 14(4) (2011) - 2010
- [c3]Cristian Rodrìguez Rivero, Julián A. Pucheta, Josef Baumgartner, Hector D. Patiño, Benjamín R. Kuchen:
An Approach for Time Series Forecasting by Simulating Stochastic Processes Through Time Lagged Feed-forward Neural Network. DMIN 2010: 287-293
2000 – 2009
- 2008
- [c2]Julián A. Pucheta, H. Daniel Patiño, Benjamín R. Kuchen:
A Statistically Dependent Approach for the Monthly Rainfall Forecastfrom One Point Observations. CCTA (2) 2008: 787-798 - 2006
- [j1]Julián A. Pucheta, Hector D. Patiño, R. Fullana, Carlos Schugurensky, Benjamín R. Kuchen:
A Neuro-Dynamic Programming-Based Optimal Controller for Tomato Seedling Growth in Greenhouse Systems. Neural Process. Lett. 24(3): 241-260 (2006) - 2004
- [c1]Hector D. Patiño, Julián A. Pucheta, R. Fullana, Carlos Schugurensky, Benjamín R. Kuchen:
Neuro-dynamic programming-based optimal control for crop growth in precision agriculture. ISIC 2004: 397-402
Coauthor Index
aka: Cristian Rodriguez Rivero
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