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2020 – today
- 2024
[j74]Leandro A Bugnon
, Leandro E. Di Persia, Matias Gerard, Jonathan Raad, Santiago Prochetto, Emilio Fenoy, Uciel Chorostecki, Federico Ariel, Georgina Stegmayer, Diego H. Milone:
sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure. Briefings Bioinform. 25(4) (2024)- [j73]Alejandro A. Edera, Georgina Stegmayer, Diego H. Milone:
gGN: Representing the Gene Ontology as low-rank Gaussian distributions. Comput. Biol. Medicine 183: 109234 (2024) - [j72]Lucas Mansilla, Estanislao Claucich, Rodrigo Echeveste, Diego H. Milone, Enzo Ferrante:
Demographically-Informed Prediction Discrepancy Index: Early Warnings of Demographic Biases for Unlabeled Populations. Trans. Mach. Learn. Res. 2024 (2024) - [i13]Josefina Catoni, Enzo Ferrante, Diego H. Milone, Rodrigo Echeveste:
Uncertainty in latent representations of variational autoencoders optimized for visual tasks. CoRR abs/2404.15390 (2024) - 2023
- [j71]Leandro A Bugnon, Emilio Fenoy, Alejandro A. Edera, Jonathan Raad, Georgina Stegmayer, Diego H. Milone:
Transfer learning: The key to functionally annotate the protein universe. Patterns 4(2): 100691 (2023) - [j70]Leandro E. Di Persia, Tiago Lopez, Agustin Arce, Diego H. Milone, Georgina Stegmayer:
exp2GO: Improving Prediction of Functions in the Gene Ontology With Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 999-1008 (2023) - [j69]Nicolás Gaggion, Lucas Mansilla, Candelaria Mosquera, Diego H. Milone, Enzo Ferrante:
Improving Anatomical Plausibility in Medical Image Segmentation via Hybrid Graph Neural Networks: Applications to Chest X-Ray Analysis. IEEE Trans. Medical Imaging 42(2): 546-556 (2023) - [c17]Nicolás Gaggion, Rodrigo Echeveste, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Unsupervised Bias Discovery in Medical Image Segmentation. CLIP/FAIMI/EPIMI@MICCAI 2023: 266-275 - [c16]Nicolás Gaggion, Maria Vakalopoulou, Diego H. Milone, Enzo Ferrante:
Multi-Center Anatomical Segmentation with Heterogeneous Labels Via Landmark-Based Models. ISBI 2023: 1-5 - [i12]Nicolás Gaggion, Candelaria Mosquera, Lucas Mansilla, Martina Aineseder, Diego H. Milone, Enzo Ferrante:
CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images. CoRR abs/2307.03293 (2023) - [i11]Nicolás Gaggion, Rodrigo Echeveste, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Unsupervised bias discovery in medical image segmentation. CoRR abs/2309.00451 (2023) - [i10]Nicolás Gaggion, Benjamin A. Matheson, Yan Xia, Rodrigo Bonazzola, Nishant Ravikumar, Zeike A. Taylor, Diego H. Milone, Alejandro F. Frangi, Enzo Ferrante:
Multi-view Hybrid Graph Convolutional Network for Volume-to-mesh Reconstruction in Cardiovascular MRI. CoRR abs/2311.13706 (2023) - 2022
- [j68]Alejandro A. Edera, Diego H. Milone, Georgina Stegmayer:
Anc2vec: embedding gene ontology terms by preserving ancestors relationships. Briefings Bioinform. 23(2) (2022) - [j67]Leandro A Bugnon, Alejandro A. Edera, Santiago Prochetto, Matias Gerard, Jonathan Raad, Emilio Fenoy, Mariano Rubiolo, Uciel Chorostecki, Toni Gabaldón, Federico Ariel, Leandro E. Di Persia, Diego H. Milone, Georgina Stegmayer:
Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches. Briefings Bioinform. 23(4) (2022) - [j66]Jonathan Raad, Leandro A Bugnon, Diego H. Milone, Georgina Stegmayer:
miRe2e: a full end-to-end deep model based on transformers for prediction of pre-miRNAs. Bioinform. 38(5): 1191-1197 (2022) - [j65]Gabriela Alejandra Merino, Rabie Saidi, Diego H. Milone, Georgina Stegmayer, Maria Jesus Martin:
Hierarchical deep learning for predicting GO annotations by integrating protein knowledge. Bioinform. 38(19): 4488-4496 (2022) - [j64]Victoria Peterson, Nicolás Nieto, Dominik Wyser, Olivier Lambercy, Roger Gassert, Diego H. Milone, Ruben D. Spies:
Transfer Learning Based on Optimal Transport for Motor Imagery Brain-Computer Interfaces. IEEE Trans. Biomed. Eng. 69(2): 807-817 (2022) - [i9]Nicolás Gaggion, Lucas Mansilla, Candelaria Mosquera, Diego H. Milone, Enzo Ferrante:
Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis. CoRR abs/2203.10977 (2022) - [i8]José O. Chelotti, Sebastián R. Vanrell, Luciano S. Martínez Rau, Julio R. Galli, Santiago A. Utsumi, Alejandra M. Planisich, Suyai A. Almirón, Diego H. Milone, Leonardo L. Giovanini, Hugo Leonardo Rufiner:
Using segment-based features of jaw movements to recognize foraging activities in grazing cattle. CoRR abs/2204.00331 (2022) - [i7]Nicolás Gaggion, Maria Vakalopoulou, Diego H. Milone, Enzo Ferrante:
Multi-center anatomical segmentation with heterogeneous labels via landmark-based models. CoRR abs/2211.07395 (2022) - 2021
- [j63]Leandro A Bugnon, Cristian A. Yones, Diego H. Milone, Georgina Stegmayer:
Genome-wide discovery of pre-miRNAs: comparison of recent approaches based on machine learning. Briefings Bioinform. 22(3) (2021) - [j62]Gabriela Alejandra Merino, Jonathan Raad, Leandro A Bugnon, Cristian A. Yones, Laura Kamenetzky, Juan Claus, Federico Ariel, Diego H. Milone, Georgina Stegmayer:
Novel SARS-CoV-2 encoded small RNAs in the passage to humans. Bioinform. 36(24): 5571-5581 (2021) - [j61]Cristian A. Yones, Jonathan Raad, Leandro A Bugnon, Diego H. Milone, Georgina Stegmayer:
High precision in microRNA prediction: A novel genome-wide approach with convolutional deep residual networks. Comput. Biol. Medicine 134: 104448 (2021) - [j60]Alejandro Edera, Ian Small, Diego H. Milone, M. Virginia Sanchez-Puerta:
Deepred-Mt: Deep representation learning for predicting C-to-U RNA editing in plant mitochondria. Comput. Biol. Medicine 136: 104682 (2021) - [c15]Lucas Mansilla, Rodrigo Echeveste, Diego H. Milone, Enzo Ferrante:
Domain Generalization via Gradient Surgery. ICCV 2021: 6610-6618 - [c14]Nicolás Gaggion, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Hybrid Graph Convolutional Neural Networks for Landmark-Based Anatomical Segmentation. MICCAI (1) 2021: 600-610 - [i6]Nicolás Gaggion, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Hybrid graph convolutional neural networks for landmark-based anatomical segmentation. CoRR abs/2106.09832 (2021) - [i5]Lucas Mansilla, Rodrigo Echeveste, Diego H. Milone, Enzo Ferrante:
Domain Generalization via Gradient Surgery. CoRR abs/2108.01621 (2021) - [i4]Candelaria Mosquera, Luciana Ferrer, Diego H. Milone, Daniel R. Luna, Enzo Ferrante:
Understanding the impact of class imbalance on the performance of chest x-ray image classifiers. CoRR abs/2112.12843 (2021) - 2020
- [j59]Jonathan Raad, Georgina Stegmayer, Diego H. Milone:
Complexity measures of the mature miRNA for improving pre-miRNAs prediction. Bioinform. 36(8): 2319-2327 (2020) - [j58]Leandro A Bugnon, Cristian A. Yones, Jonathan Raad, Matias Gerard, Mariano Rubiolo, Gabriela Alejandra Merino, Milton Pividori, Leandro E. Di Persia, Diego H. Milone, Georgina Stegmayer:
DL4papers: a deep learning approach for the automatic interpretation of scientific articles. Bioinform. 36(11): 3499-3506 (2020) - [j57]José O. Chelotti, Sebastián R. Vanrell, Luciano Martínez Rau, Julio R. Galli, Alejandra M. Planisich, Santiago A. Utsumi, Diego H. Milone, Leonardo L. Giovanini, Hugo Leonardo Rufiner:
An online method for estimating grazing and rumination bouts using acoustic signals in grazing cattle. Comput. Electron. Agric. 173: 105443 (2020) - [j56]Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Learning deformable registration of medical images with anatomical constraints. Neural Networks 124: 269-279 (2020) - [j55]Leandro A Bugnon, Rafael A. Calvo, Diego H. Milone:
Dimensional Affect Recognition from HRV: An Approach Based on Supervised SOM and ELM. IEEE Trans. Affect. Comput. 11(1): 32-44 (2020) - [j54]Leandro A Bugnon, Cristian A. Yones, Diego H. Milone, Georgina Stegmayer:
Deep Neural Architectures for Highly Imbalanced Data in Bioinformatics. IEEE Trans. Neural Networks Learn. Syst. 31(8): 2857-2867 (2020) - [i3]Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Learning Deformable Registration of Medical Images with Anatomical Constraints. CoRR abs/2001.07183 (2020)
2010 – 2019
- 2019
- [j53]Georgina Stegmayer, Leandro E. Di Persia, Mariano Rubiolo, Matias Gerard, Milton Pividori, Cristian A. Yones, Leandro A Bugnon, Tadeo Rodriguez, Jonathan Raad, Diego H. Milone:
Predicting novel microRNA: a comprehensive comparison of machine learning approaches. Briefings Bioinform. 20(5): 1607-1620 (2019) - [j52]Milton Pividori, Andres Cernadas, Luis A. de Haro, Fernando Carrari, Georgina Stegmayer, Diego H. Milone:
Clustermatch: discovering hidden relations in highly diverse kinds of qualitative and quantitative data without standardization. Bioinform. 35(11): 1931-1939 (2019) - 2018
- [j51]Cristian A. Yones, Georgina Stegmayer, Diego H. Milone:
Genome-wide pre-miRNA discovery from few labeled examples. Bioinform. 34(4): 541-549 (2018) - [j50]Mariano Rubiolo, Diego H. Milone, Georgina Stegmayer:
Extreme learning machines for reverse engineering of gene regulatory networks from expression time series. Bioinform. 34(7): 1253-1260 (2018) - [j49]Sebastián R. Vanrell, José O. Chelotti, Julio R. Galli, Santiago A. Utsumi, Leonardo L. Giovanini, Hugo Leonardo Rufiner, Diego H. Milone:
A regularity-based algorithm for identifying grazing and rumination bouts from acoustic signals in grazing cattle. Comput. Electron. Agric. 151: 392-402 (2018) - [j48]Federico Schlüter, Yanela Strappa, Diego H. Milone, Facundo Bromberg:
Blankets Joint Posterior score for learning Markov network structures. Int. J. Approx. Reason. 92: 295-320 (2018) - [j47]Guillermo Leale, Ariel E. Bayá, Diego H. Milone, Pablo M. Granitto, Georgina Stegmayer:
Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 15(1): 168-180 (2018) - [j46]Sebastián R. Vanrell, Diego H. Milone, Hugo Leonardo Rufiner:
Assessment of Homomorphic Analysis for Human Activity Recognition From Acceleration Signals. IEEE J. Biomed. Health Informatics 22(4): 1001-1010 (2018) - [c13]Enzo Ferrante, Ozan Oktay, Ben Glocker, Diego H. Milone:
On the Adaptability of Unsupervised CNN-Based Deformable Image Registration to Unseen Image Domains. MLMI@MICCAI 2018: 294-302 - 2017
- [j45]Enrique M. Albornoz, Diego H. Milone, Hugo Leonardo Rufiner:
Feature extraction based on bio-inspired model for robust emotion recognition. Soft Comput. 21(17): 5145-5158 (2017) - [j44]Enrique Marcelo Albornoz, Diego H. Milone:
Emotion Recognition in Never-Seen Languages Using a Novel Ensemble Method with Emotion Profiles. IEEE Trans. Affect. Comput. 8(1): 43-53 (2017) - [j43]Georgina Stegmayer, Cristian A. Yones, Laura Kamenetzky, Diego H. Milone:
High Class-Imbalance in pre-miRNA Prediction: A Novel Approach Based on deepSOM. IEEE ACM Trans. Comput. Biol. Bioinform. 14(6): 1316-1326 (2017) - [c12]Tadeo Rodriguez, Leandro E. Di Persia, Diego H. Milone, Georgina Stegmayer:
Extreme learning machine prediction under high class imbalance in bioinformatics. CLEI 2017: 1-8 - 2016
- [j42]Georgina Stegmayer, Milton Pividori, Diego H. Milone:
A very simple and fast way to access and validate algorithms in reproducible research. Briefings Bioinform. 17(1): 180-183 (2016) - [j41]Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone:
Evolutionary algorithm for metabolic pathways synthesis. Biosyst. 144: 55-67 (2016) - [j40]José O. Chelotti, Sebastián R. Vanrell, Diego H. Milone, Santiago A. Utsumi, Julio R. Galli, Hugo Leonardo Rufiner, Leonardo L. Giovanini:
A real-time algorithm for acoustic monitoring of ingestive behavior of grazing cattle. Comput. Electron. Agric. 127: 64-75 (2016) - [j39]David Nazareno Campo, Georgina Stegmayer, Diego H. Milone:
A new index for clustering validation with overlapped clusters. Expert Syst. Appl. 64: 549-556 (2016) - [j38]Leandro Daniel Vignolo, Hugo Leonardo Rufiner, Diego H. Milone:
Multi-objective optimisation of wavelet features for phoneme recognition. IET Signal Process. 10(6): 685-691 (2016) - [j37]Milton Pividori, Georgina Stegmayer, Diego H. Milone:
Diversity control for improving the analysis of consensus clustering. Inf. Sci. 361-362: 120-134 (2016) - [j36]Leandro Daniel Vignolo, S. R. Mahadeva Prasanna, Samarendra Dandapat, Hugo Leonardo Rufiner, Diego H. Milone:
Feature optimisation for stress recognition in speech. Pattern Recognit. Lett. 84: 1-7 (2016) - [j35]Leandro E. Di Persia, Diego H. Milone:
Using multiple frequency bins for stabilization of FD-ICA algorithms. Signal Process. 119: 162-168 (2016) - [i2]Federico Schlüter, Yanela Strappa, Facundo Bromberg, Diego H. Milone:
Blankets Joint Posterior score for learning irregular Markov network structures. CoRR abs/1608.02315 (2016) - [i1]Guillermo L. Grinblat, Ariel E. Bayá, Diego H. Milone, Pablo M. Granitto, Georgina Stegmayer:
Inferring unknown biological function by integration of GO annotations and gene expression data. CoRR abs/1608.03672 (2016) - 2015
- [j34]Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone:
EvoMS: An evolutionary tool to find de novo metabolic pathways. Biosyst. 134: 43-47 (2015) - [j33]Cristian A. Yones, Georgina Stegmayer, Laura Kamenetzky, Diego H. Milone:
miRNAfe: A comprehensive tool for feature extraction in microRNA prediction. Biosyst. 138: 1-5 (2015) - [j32]César Ernesto Martínez, John C. Goddard, Leandro E. Di Persia, Diego H. Milone, Hugo Leonardo Rufiner:
Denoising sound signals in a bioinspired non-negative spectro-temporal domain. Digit. Signal Process. 38: 22-31 (2015) - [j31]Diego Tomassi, Diego H. Milone, James D. B. Nelson:
Wavelet shrinkage using adaptive structured sparsity constraints. Signal Process. 106: 73-87 (2015) - [j30]Mariano Rubiolo, Diego H. Milone, Georgina Stegmayer:
Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series. IEEE ACM Trans. Comput. Biol. Bioinform. 12(6): 1365-1373 (2015) - 2014
- [j29]Milton Pividori, Georgina Stegmayer, Diego H. Milone:
A Method to Improve the Analysis of Cluster Ensembles. Inteligencia Artif. 17(53): 46-56 (2014) - [j28]David Nazareno Campo, Georgina Stegmayer, Diego H. Milone:
Stability analysis in overlapped clusters. Inteligencia Artif. 17(53): 79-89 (2014) - [j27]Diego H. Milone, Georgina Stegmayer, Mariana G. Lopez, Laura Kamenetzky, Fernando Carrari:
Improving clustering with metabolic pathway data. BMC Bioinform. 15: 101 (2014) - 2013
- [j26]Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone:
An evolutionary approach for searching metabolic pathways. Comput. Biol. Medicine 43(11): 1704-1712 (2013) - [j25]Leandro Daniel Vignolo, Diego H. Milone, Hugo Leonardo Rufiner:
Genetic wavelet packets for speech recognition. Expert Syst. Appl. 40(6): 2350-2359 (2013) - [j24]Georgina Stegmayer, Diego H. Milone, Sergio Garran, Lourdes Burdyn:
Automatic recognition of quarantine citrus diseases. Expert Syst. Appl. 40(9): 3512-3517 (2013) - [j23]Diego H. Milone, Georgina Stegmayer, Laura Kamenetzky, Mariana G. Lopez, Fernando Carrari:
Clustering biological data with SOMs: On topology preservation in non-linear dimensional reduction. Expert Syst. Appl. 40(9): 3841-3845 (2013) - [j22]Leandro Daniel Vignolo, Diego H. Milone, Jacob Scharcanski:
Feature selection for face recognition based on multi-objective evolutionary wrappers. Expert Syst. Appl. 40(13): 5077-5084 (2013) - [j21]Mariano Rubiolo, Georgina Stegmayer, Diego H. Milone:
Compressing arrays of classifiers using Volterra-neural network: application to face recognition. Neural Comput. Appl. 23(6): 1687-1701 (2013) - 2012
- [j20]Matias Fernando Gerard, Diego H. Milone, Georgina Stegmayer:
An evolutionary approach to metabolic pathways search. Inteligencia Artif. 15(49): 1-12 (2012) - [j19]Georgina Stegmayer, Matias Gerard, Diego H. Milone:
Data Mining Over Biological Datasets: An Integrated Approach Based on Computational Intelligence. IEEE Comput. Intell. Mag. 7(4): 22-34 (2012) - [j18]César Ernesto Martínez, John C. Goddard, Diego H. Milone, Hugo Leonardo Rufiner:
Bioinspired sparse spectro-temporal representation of speech for robust classification. Comput. Speech Lang. 26(5): 336-348 (2012) - [j17]Georgina Stegmayer, Diego H. Milone, Laura Kamenetzky, Mariana G. Lopez, Fernando Carrari:
A Biologically Inspired Validity Measure for Comparison of Clustering Methods over Metabolic Data Sets. IEEE ACM Trans. Comput. Biol. Bioinform. 9(3): 706-716 (2012) - [c11]Leandro Daniel Vignolo, Diego H. Milone, Carlos A. R. Behaine, Jacob Scharcanski:
An evolutionary wrapper for feature selection in face recognition applications. SMC 2012: 1286-1290 - 2011
- [j16]Leandro Daniel Vignolo, Hugo Leonardo Rufiner, Diego H. Milone, John C. Goddard:
Evolutionary cepstral coefficients. Appl. Soft Comput. 11(4): 3419-3428 (2011) - [j15]Enrique M. Albornoz, Diego H. Milone, Hugo Leonardo Rufiner:
Spoken emotion recognition using hierarchical classifiers. Comput. Speech Lang. 25(3): 556-570 (2011) - [j14]Leandro Daniel Vignolo, Hugo Leonardo Rufiner, Diego H. Milone, John C. Goddard:
Evolutionary Splines for Cepstral Filterbank Optimization in Phoneme Classification. EURASIP J. Adv. Signal Process. 2011 (2011) - [j13]Leandro E. Di Persia, Diego H. Milone, Masuzo Yanagida:
Correlated Postfiltering and Mutual Information in Pseudoanechoic Model Based Blind Source Separation. J. Signal Process. Syst. 63(3): 333-344 (2011) - [c10]Pablo Gautério Cavalcanti, Jacob Scharcanski, Leandro E. Di Persia, Diego H. Milone:
An ICA-based method for the segmentation of pigmented skin lesions in macroscopic images. EMBC 2011: 5993-5996 - 2010
- [j12]Diego H. Milone, Georgina Stegmayer, Laura Kamenetzky, Mariana G. Lopez, Je Min Lee, James J. Giovannoni, Fernando Carrari:
*omeSOM: a software for clustering and visualization of transcriptional and metabolite data mined from interspecific crosses of crop plants. BMC Bioinform. 11: 438 (2010) - [j11]Diego H. Milone, Leandro E. Di Persia, María Eugenia Torres:
Denoising and recognition using hidden Markov models with observation distributions modeled by hidden Markov trees. Pattern Recognit. 43(4): 1577-1589 (2010) - [j10]Diego Tomassi, Diego H. Milone, Liliana Forzani:
Minimum classification error learning for sequential data in the wavelet domain. Pattern Recognit. 43(12): 3998-4010 (2010) - [c9]Mariano Rubiolo, Georgina Stegmayer, Diego H. Milone:
Compressing a neural network classifier using a Volterra-Neural Network model. IJCNN 2010: 1-7
2000 – 2009
- 2009
- [j9]D. Capello, César Ernesto Martínez, Diego H. Milone, Georgina Stegmayer:
Array of Multilayer Perceptrons with No-class Resampling Training for Face Recognition. Inteligencia Artif. 13(44): 5-13 (2009) - [j8]Diego Tomassi, Diego H. Milone, Liliana Forzani:
Minimum Classification Error Training of Hidden Markov Models for Sequential Data in the Wavelet Domain. Inteligencia Artif. 13(44): 46-55 (2009) - [j7]Diego H. Milone, Georgina Stegmayer, Matias Gerard, Laura Kamenetzky, Mariana G. Lopez, Fernando Carrari:
Métodos de agrupamiento no supervisado para la integración de datos genómicos y metabólicos de múltiples líneas de introgresión. Inteligencia Artif. 13(44): 56-66 (2009) - [j6]Leandro E. Di Persia, Diego H. Milone, Masuzo Yanagida:
Indeterminacy Free Frequency-Domain Blind Separation of Reverberant Audio Sources. IEEE Trans. Speech Audio Process. 17(2): 299-311 (2009) - [c8]Leandro Daniel Vignolo, Hugo Leonardo Rufiner, Diego H. Milone, John C. Goddard:
Genetic Optimization of Cepstrum Filterbank for Phoneme Classification. BIOSIGNALS 2009: 179-185 - [c7]Enrique M. Albornoz, Diego H. Milone, Hugo Leonardo Rufiner:
Multiple Feature Extraction and Hierarchical Classifiers for Emotions Recognition. COST 2102 Training School 2009: 242-254 - [c6]Diego H. Milone, Georgina Stegmayer, Daniel Beber:
Artificial Life Contest - A Tool for Informal Teaching of Artificial Intelligence. CSEDU (1) 2009: 119-124 - [c5]Georgina Stegmayer, Diego H. Milone, Laura Kamenetzky, Mariana G. Lopez, Fernando Carrari:
Neural network model for integration and visualization of introgressed genome and metabolite data. IJCNN 2009: 2983-2989 - 2008
- [j5]Diego H. Milone, Leandro E. Di Persia:
Learning Hidden Markov Models with Hidden Markov Trees as Observation Distributions. Inteligencia Artif. 12(37): 7-13 (2008) - [j4]Leandro E. Di Persia, Diego H. Milone, Hugo Leonardo Rufiner, Masuzo Yanagida:
Perceptual evaluation of blind source separation for robust speech recognition. Signal Process. 88(10): 2578-2583 (2008) - 2007
- [j3]Diego H. Milone:
Adaptive learning of polynomial networks, genetic programming, backpropagation and Bayesian methods, series on genetic and evolutionary computation. Genet. Program. Evolvable Mach. 8(3): 289-291 (2007) - [j2]Leandro E. Di Persia, Masuzo Yanagida, Hugo Leonardo Rufiner, Diego H. Milone:
Objective quality evaluation in blind source separation for speech recognition in a real room. Signal Process. 87(8): 1951-1965 (2007) - [c4]Diego H. Milone, Leandro E. Di Persia:
An EM Algorithm to Learn Sequences in the Wavelet Domain. MICAI 2007: 518-528 - [c3]Hugo Leonardo Rufiner, César Ernesto Martínez, Diego H. Milone, John C. Goddard:
Auditory Cortical Representations of Speech Signals for Phoneme Classification. MICAI 2007: 1004-1014 - 2003
- [j1]Diego H. Milone, Antonio J. Rubio:
Prosodic and accentual information for automatic speech recognition. IEEE Trans. Speech Audio Process. 11(4): 321-333 (2003) - 2002
- [c2]Diego H. Milone, Juan Julián Merelo, Hugo Leonardo Rufiner:
Evolutionary algorithm for speech segmentation. IEEE Congress on Evolutionary Computation 2002: 1115-1120 - 2001
- [c1]Ramón López-Cózar, Diego H. Milone:
A new technique based on augmented language models to improve the performance of spoken dialogue systems. INTERSPEECH 2001: 741-744
Coauthor Index
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