Edmondo Trentin

Orcid: 0000-0003-2197-0703

Affiliations:
  • Università di Siena, Italy


According to our database1, Edmondo Trentin authored at least 64 papers between 1994 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Automatic Interpretation of <sup>18</sup>F-Fluorocholine PET/CT Findings in Patients with Primary Hyperparathyroidism: A Novel Dataset with Benchmarks.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2024

Gaussian-Mixture Neural Networks.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2024

2023
Multivariate Density Estimation with Deep Neural Mixture Models.
Neural Process. Lett., December, 2023

Downward-Growing Neural Networks.
Entropy, 2023

2022
A Novel Representation of Graphical Patterns for Graph Convolution Networks.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2022

2020
Mixtures of Deep Neural Experts for Automated Speech Scoring.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

2018
Recursive Neural Networks for Density Estimation Over Generalized Random Graphs.
IEEE Trans. Neural Networks Learn. Syst., 2018

Off the Mainstream: Advances in Neural Networks and Machine Learning for Pattern Recognition.
Neural Process. Lett., 2018

Soft-Constrained Neural Networks for Nonparametric Density Estimation.
Neural Process. Lett., 2018

Dynamic Hybrid Random Fields for the Probabilistic Graphical Modeling of Sequential Data: Definitions, Algorithms, and an Application to Bioinformatics.
Neural Process. Lett., 2018

Parzen neural networks: Fundamentals, properties, and an application to forensic anthropology.
Neural Networks, 2018

Nonparametric small random networks for graph-structured pattern recognition.
Neurocomputing, 2018

Maximum-Likelihood Estimation of Neural Mixture Densities: Model, Algorithm, and Preliminary Experimental Evaluation.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2018

A Refinement Algorithm for Deep Learning via Error-Driven Propagation of Target Outputs.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2018

2016
Soft-Constrained Nonparametric Density Estimation with Artificial Neural Networks.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2016

A Hybrid Recurrent Neural Network/Dynamic Probabilistic Graphical Model Predictor of the Disulfide Bonding State of Cysteines from the Primary Structure of Proteins.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2016

2015
Emotion recognition from speech signals via a probabilistic echo-state network.
Pattern Recognit. Lett., 2015

Maximum-likelihood normalization of features increases the robustness of neural-based spoken human-computer interaction.
Pattern Recognit. Lett., 2015

Techniques for dealing with incomplete data: a tutorial and survey.
Pattern Anal. Appl., 2015

2014
Pattern classification and clustering: A review of partially supervised learning approaches.
Pattern Recognit. Lett., 2014

Partially supervised learning for pattern recognition.
Pattern Recognit. Lett., 2014

Combination of supervised and unsupervised learning for training the activation functions of neural networks.
Pattern Recognit. Lett., 2014

2013
Hidden Markov models with graph densities for action recognition.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

2012
Towards a Novel Probabilistic Graphical Model of Sequential Data: Fundamental Notions and a Solution to the Problem of Parameter Learning.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2012

Towards a Novel Probabilistic Graphical Model of Sequential Data: A Solution to the Problem of Structure Learning and an Empirical Evaluation.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2012

2011
Hybrid Random Fields - A Scalable Approach to Structure and Parameter Learning in Probabilistic Graphical Models
Intelligent Systems Reference Library 15, Springer, ISBN: 978-3-642-20307-7, 2011

Comparison of Combined Probabilistic Connectionist Models in a Forensic Application.
Proceedings of the Partially Supervised Learning - First IAPR TC3 Workshop, 2011

Semi-unsupervised Weighted Maximum-Likelihood Estimation of Joint Densities for the Co-training of Adaptive Activation Functions.
Proceedings of the Partially Supervised Learning - First IAPR TC3 Workshop, 2011

Supervised and Unsupervised Co-training of Adaptive Activation Functions in Neural Nets.
Proceedings of the Partially Supervised Learning - First IAPR TC3 Workshop, 2011

2010
Kernel-Based Hybrid Random Fields for Nonparametric Density Estimation.
Proceedings of the ECAI 2010, 2010

Recognition of Sequences of Graphical Patterns.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2010

Maximum Echo-State-Likelihood Networks for Emotion Recognition.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2010

2009
Probabilistic Interpretation of Neural Networks for the Classification of Vectors, Sequences and Graphs.
Proceedings of the Innovations in Neural Information Paradigms and Applications, 2009

A hybrid random field model for scalable statistical learning.
Neural Networks, 2009

Classification of graphical data made easy.
Neurocomputing, 2009

Scalable pseudo-likelihood estimation in hybrid random fields.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Unsupervised nonparametric density estimation: A neural network approach.
Proceedings of the International Joint Conference on Neural Networks, 2009

Scalable statistical learning: A modular bayesian/markov network approach.
Proceedings of the International Joint Conference on Neural Networks, 2009

A Maximum-Likelihood Connectionist Model for Unsupervised Learning over Graphical Domains.
Proceedings of the Artificial Neural Networks, 2009

2008
Classification of molecular structures made easy.
Proceedings of the International Joint Conference on Neural Networks, 2008

2007
Neural-based downlink scheduling algorithm for broadband wireless networks.
Comput. Commun., 2007

A Simple and Effective Neural Model for the Classification of Structured Patterns.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2007

Unbiased SVM Density Estimation with Application to Graphical Pattern Recognition.
Proceedings of the Artificial Neural Networks, 2007

2006
Inversion-based nonlinear adaptation of noisy acoustic parameters for a neural/HMM speech recognizer.
Neurocomputing, 2006

A Novel Connectionist-Oriented Feature Normalization Technique.
Proceedings of the Artificial Neural Networks, 2006

Simple and Effective Connectionist Nonparametric Estimation of Probability Density Functions.
Proceedings of the Artificial Neural Networks in Pattern Recognition, Second IAPR Workshop, 2006

2005
Feature Normalization via ANN/HMM Inversion for Speech Recognition Under Noisy Conditions.
Proceedings of the IEEE 7th Workshop on Multimedia Signal Processing, 2005

2003
Robust combination of neural networks and hidden Markov models for speech recognition.
IEEE Trans. Neural Networks, 2003

Noise-tolerant speech recognition: the SNN-TA approach.
Inf. Sci., 2003

Nonparametric Hidden Markov Models: Principles and Applications to Speech Recognition.
Proceedings of the Neural Nets, 14th Italian Workshop on Neural Nets, 2003

Evaluation on the Aurora 2 database of acoustic models that are less noise-sensitive.
Proceedings of the 8th European Conference on Speech Communication and Technology, EUROSPEECH 2003, 2003

2001
Networks with trainable amplitude of activation functions.
Neural Networks, 2001

A Mixture of Recurrent Neural Networks for Speaker Normalisation.
Neural Comput. Appl., 2001

A survey of hybrid ANN/HMM models for automatic speech recognition.
Neurocomputing, 2001

Toward noise-tolerant acoustic models.
Proceedings of the EUROSPEECH 2001 Scandinavia, 2001

Continuous Speech Recognition with a Robust Connectionist/Markovian Hybrid Model.
Proceedings of the Artificial Neural Networks, 2001

2000
The Regularized SNN-TA Model for Recognition of Noisy Speech.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999
Learning Perception for Indoor Robot Navigation with a Hybrid Hidden Markov Model/Recurrent Neural Networks Approach.
Connect. Sci., 1999

Activation functions with learnable amplitude.
Proceedings of the International Joint Conference Neural Networks, 1999

1997
Estimating the crowding level with a neuro-fuzzy classifier.
J. Electronic Imaging, 1997

Speaker Normalization and Model Selection of Combined Neural Networks.
Connect. Sci., 1997

Speaker normalization with a mixture of recurrent networks.
Proceedings of the 5th Eurorean Symposium on Artificial Neural Networks, 1997

1995
Application of Generalized Radial Basis Functions In Speaker Normalization and Identification.
Proceedings of the 1995 IEEE International Symposium on Circuits and Systems, ISCAS 1995, Seattle, Washington, USA, April 30, 1995

1994
Connectionist Speaker Normalization with Generalized Resource Allocating Networks.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994


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