Leonardo Franco

According to our database1, Leonardo Franco authored at least 60 papers between 1998 and 2020.

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

Timeline

Legend:

Book 
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PhD thesis 
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Online presence:

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Bibliography

2020
Improving learning and generalization capabilities of the C-Mantec constructive neural network algorithm.
Neural Comput. Appl., 2020

Improving classification accuracy using data augmentation on small data sets.
Expert Syst. Appl., 2020

Short-Term Rainfall Forecasting with E-LSTM Recurrent Neural Networks Using Small Datasets.
Proceedings of the Intelligent Computing Methodologies - 16th International Conference, 2020

2019
Addition of Pathway-Based Information to Improve Predictions in Transcriptomics.
Proceedings of the Bioinformatics and Biomedical Engineering, 2019

A Transfer-Learning Approach to Feature Extraction from Cancer Transcriptomes with Deep Autoencoders.
Proceedings of the Advances in Computational Intelligence, 2019

Command Acknowledge through Tactile Feedback Improves the Usability of an EMG-based Interface for the Frontalis Muscle.
Proceedings of the 2019 IEEE World Haptics Conference, 2019

2018
BLASSO: integration of biological knowledge into a regularized linear model.
BMC Syst. Biol., 2018

Forward Noise Adjustment Scheme for Data Augmentation.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Poster: SIMNET: Simulation-Based Exercises for Computer Network Curriculum Through Gamification and Augmented Reality.
Proceedings of the Smart Industry & Smart Education, 2018

2017
FPGA Implementation of Neurocomputational Models: Comparison Between Standard Back-Propagation and C-Mantec Constructive Algorithm.
Neural Process. Lett., 2017

Layer multiplexing FPGA implementation for deep back-propagation learning.
Integr. Comput. Aided Eng., 2017

Classification of high dimensional data using LASSO ensembles.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Time-series prediction with BEMCA approach: Application to short rainfall series.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2017

L_1 L 1 -regularization Model Enriched with Biological Knowledge.
Proceedings of the Bioinformatics and Biomedical Engineering, 2017

Deep Learning to Analyze RNA-Seq Gene Expression Data.
Proceedings of the Advances in Computational Intelligence, 2017

Solving Scheduling Problems with Genetic Algorithms Using a Priority Encoding Scheme.
Proceedings of the Advances in Computational Intelligence, 2017

Machine learning models to search relevant genetic signatures in clinical context.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016
FPGA Hardware Acceleration of Monte Carlo Simulations for the Ising Model.
IEEE Trans. Parallel Distributed Syst., 2016

Efficient Implementation of the Backpropagation Algorithm in FPGAs and Microcontrollers.
IEEE Trans. Neural Networks Learn. Syst., 2016

Supervised discretization can discover risk groups in cancer survival analysis.
Comput. Methods Programs Biomed., 2016

Deep Neural Network Architecture Implementation on FPGAs Using a Layer Multiplexing Scheme.
Proceedings of the Distributed Computing and Artificial Intelligence, 2016

2015
FPGA Implementation Comparison Between C-Mantec and Back-Propagation Neural Network Algorithms.
Proceedings of the Advances in Computational Intelligence, 2015

2014
FPGA Implementation of the C-Mantec Neural Network Constructive Algorithm.
IEEE Trans. Ind. Informatics, 2014

Robust gene signatures from microarray data using genetic algorithms enriched with biological pathway keywords.
J. Biomed. Informatics, 2014

Smart sensor/actuator node reprogramming in changing environments using a neural network model.
Eng. Appl. Artif. Intell., 2014

High precision FPGA implementation of neural network activation functions.
Proceedings of the IEEE Symposium on Intelligent Embedded Systems, 2014

Use of q-values to Improve a Genetic Algorithm to Identify Robust Gene Signatures.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2014

2013
Addressing critical issues in the development of an Oncology Information System.
Int. J. Medical Informatics, 2013

Analysis of Cancer Microarray Data using Constructive Neural Networks and Genetic Algorithms.
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2013

A Constructive Neural Network to Predict Pitting Corrosion Status of Stainless Steel.
Proceedings of the Advances in Computational Intelligence, 2013

Committee C-Mantec: A Probabilistic Constructive Neural Network.
Proceedings of the Advances in Computational Intelligence, 2013

Implementation of the C-Mantec Neural Network Constructive Algorithm in an Arduino Uno Microcontroller.
Proceedings of the Advances in Computational Intelligence, 2013

2012
C-Mantec: A novel constructive neural network algorithm incorporating competition between neurons.
Neural Networks, 2012

WIMP: Web server tool for missing data imputation.
Comput. Methods Programs Biomed., 2012

Data Discretization Using the Extreme Learning Machine Neural Network.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

2011
Hybrid (Generalization-Correlation) Method for Feature Selection in High Dimensional DNA Microarray Prediction Problems.
Proceedings of the Advances in Computational Intelligence, 2011

2010
Multiclass Pattern Recognition Extension for the New C-Mantec Constructive Neural Network Algorithm.
Cogn. Comput., 2010

Missing data imputation using statistical and machine learning methods in a real breast cancer problem.
Artif. Intell. Medicine, 2010

Extension of the Generalization Complexity Measure to Real Valued Input Data Sets.
Proceedings of the Advances in Neural Networks, 2010

Constructive Neural Networks to Predict Breast Cancer Outcome by Using Gene Expression Profiles.
Proceedings of the Trends in Applied Intelligent Systems, 2010

2009
Active Learning Using a Constructive Neural Network Algorithm.
Proceedings of the Constructive Neural Networks, 2009

Constructive Neural Network Algorithms for Feedforward Architectures Suitable for Classification Tasks.
Proceedings of the Constructive Neural Networks, 2009

Neural Network Architecture Selection: Can Function Complexity Help?
Neural Process. Lett., 2009

2008
A New Decomposition Algorithm for Threshold Synthesis and Generalization of Boolean Functions.
IEEE Trans. Circuits Syst. I Regul. Pap., 2008

Active Learning Using a Constructive Neural Network Algorithm.
Proceedings of the Artificial Neural Networks, 2008

2007
Neuronal selectivity, population sparseness, and ergodicity in the inferior temporal visual cortex.
Biol. Cybern., 2007

Early Breast Cancer Prognosis Prediction and Rule Extraction Using a New Constructive Neural Network Algorithm.
Proceedings of the Computational and Ambient Intelligence, 2007

MaxSet: An Algorithm for Finding a Good Approximation for the Largest Linearly Separable Set.
Proceedings of the Artificial Neural Networks, 2007

2006
The influence of oppositely classified examples on the generalization complexity of Boolean functions.
IEEE Trans. Neural Networks, 2006

Generalization ability of Boolean functions implemented in feedforward neural networks.
Neurocomputing, 2006

A New Constructive Approach for Creating All Linearly Separable (Threshold) Functions.
Proceedings of the International Joint Conference on Neural Networks, 2006

Optimal Synthesis of Boolean Functions by Threshold Functions.
Proceedings of the Artificial Neural Networks, 2006

Neural Network Architecture Selection: Size Depends on Function Complexity.
Proceedings of the Artificial Neural Networks, 2006

2005
Role of Function Complexity and Network Size in the Generalization Ability of Feedforward Networks.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Artificial neural networks and prognosis in medicine. Survival analysis in breast cancer patients.
Proceedings of the ESANN 2005, 2005

2004
Information encoding in the inferior temporal visual cortex: contributions of the firing rates and the correlations between the firing of neurons.
Biol. Cybern., 2004

2003
CBA Generated Receptive Fields Implemented in a Facial Expression Recognition Task.
Proceedings of the Artificial Neural Nets Problem Solving Methods, 2003

2001
Generalization properties of modular networks: implementing the parity function.
IEEE Trans. Neural Networks, 2001

2000
Generalization and Selection of Examples in Feedforward Neural Networks.
Neural Comput., 2000

1998
Solving arithmetic problems using feed-forward neural networks.
Neurocomputing, 1998


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