Martina Iammarino

According to our database, Martina Iammarino authored at least 31 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

A data-aware explainable deep learning approach for next activity prediction.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Chiara Verdone

Eng. Appl. Artif. Intell., November, 2023

Evo-GUNet3++: Using evolutionary algorithms to train UNet-based architectures for efficient 3D lung cancer detection.

Pasquale Ardimento, Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Chiara Verdone

Appl. Soft Comput., September, 2023

Forecasting technical debt evolution in software systems: an empirical study.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Debora Montano

Frontiers Comput. Sci., 2023

Forecasting the Developer's Impact in Managing the Technical Debt.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino

Proceedings of the Product-Focused Software Process Improvement, 2023

Raman Spectroscopy of Cells for Cancer Classification Through Machine Learning.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Andrea Cusano, Martina Iammarino, Marco Pisco, Sara Spaziani, Chiara Verdone

Proceedings of the IEEE International Conference on Metrology for eXtended Reality, 2023

Early Diagnosis of Parkinson's Disease Exploting Motor and Non-Motor Symptoms: Results from the PPMI Cohort.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Antonella Madau, Chiara Verdone

Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 27th International Conference KES-2023, 2023

Understanding Compiler Effects on Clone Detection Process.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Debora Montano

Proceedings of the 18th International Conference on Software Technologies, 2023

Early Parkinson's Disease Detection from EEG Traces Using Machine Learning Techniques.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Debora Montano, Chiara Verdone

Proceedings of the Fuzzy Logic and Technology, and Aggregation Operators, 2023

An Empirical Study on the Relationship Between the Co-Occurrence of Design Smell and Refactoring Activities.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Debora Montano

Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering, 2023

An Explainable Approach for Early Parkinson Disease Detection Using Deep Learning.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Antonella Madau, Chiara Verdone

Proceedings of the Deep Learning Theory and Applications - 4th International Conference, 2023

Machine Learning Applied to Speech Recordings for Parkinson's Disease Recognition.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Antonella Madau, Chiara Verdone

Proceedings of the Deep Learning Theory and Applications - 4th International Conference, 2023

2022

Just-in-time software defect prediction using deep temporal convolutional networks.

Pasquale Ardimento, Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino

Neural Comput. Appl., 2022

Using deep temporal convolutional networks to just-in-time forecast technical debt principal.

Pasquale Ardimento, Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino

J. Syst. Softw., 2022

Technical Debt Forecasting from Source Code Using Temporal Convolutional Networks.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino

Proceedings of the Product-Focused Software Process Improvement, 2022

An enhanced UNet variant for Effective Lung Cancer Detection.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Chiara Verdone

Proceedings of the International Joint Conference on Neural Networks, 2022

Early Detection of Parkinson's Disease using Spiral Test and Echo State Networks.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Chiara Verdone

Proceedings of the International Joint Conference on Neural Networks, 2022

Is There Any Correlation between Refactoring and Design Smell Occurrence?

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Debora Montano

Proceedings of the 17th International Conference on Software Technologies, 2022

An Empirical Study to Predict Student Performance Using Information of the Virtual Learning Environment.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Debora Montano, Chiara Verdone

Proceedings of the Higher Education Learning Methodologies and Technologies Online, 2022

A Machine Learning approach for Early Detection of Parkinson's Disease Using acoustic traces.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Debora Montano, Chiara Verdone

Proceedings of the IEEE International Conference on Evolving and Adaptive Intelligent System, 2022

Using Machine Learning for early prediction of Heart Disease.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Debora Montano, Chiara Verdone

Proceedings of the IEEE International Conference on Evolving and Adaptive Intelligent System, 2022

Using Machine Learning for Classification of Cancer Cells from Raman Spectroscopy.

Lerina Aversano, Mario Luca Bernardi, Vincenzo Calgano, Marta Cimitile, Concetta Esposito, Martina Iammarino, Marco Pisco, Sara Spaziani, Chiara Verdone

Proceedings of the 3rd International Conference on Deep Learning Theory and Applications, 2022

2021

An empirical study on the co-occurrence between refactoring actions and Self-Admitted Technical Debt removal.

Martina Iammarino, Fiorella Zampetti, Lerina Aversano, Massimiliano Di Penta

J. Syst. Softw., 2021

Temporal convolutional networks for just-in-time design smells prediction using fine-grained software metrics.

Pasquale Ardimento, Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino

Neurocomputing, 2021

Thyroid Disease Treatment prediction with machine learning approaches.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Paolo Emidio Macchia, Immacolata Cristina Nettore, Chiara Verdone

Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES-2021, 2021

Technical Debt predictive model through Temporal Convolutional Network.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino

Proceedings of the International Joint Conference on Neural Networks, 2021

Transfer Learning for Just-in-Time Design Smells Prediction using Temporal Convolutional Networks.

Pasquale Ardimento, Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino

Proceedings of the 16th International Conference on Software Technologies, 2021

2020

An Empirical Study on the Evolution of Design Smells.

Lerina Aversano, Umberto Carpenito, Martina Iammarino

Inf., 2020

On the Relationship between Self-Admitted Technical Debt Removals and Technical Debt Measures.

Lerina Aversano, Martina Iammarino, Mimmo Carapella, Andrea Del Vecchio, Laura Nardi

Algorithms, 2020

A Topic Modeling Approach To Evaluate The Comments Consistency To Source Code.

Martina Iammarino, Lerina Aversano, Mario Luca Bernardi, Marta Cimitile

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Investigating on the Relationships between Design Smells Removals and Refactorings.

Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, Martina Iammarino, Kateryna Romanyuk

Proceedings of the 15th International Conference on Software Technologies, 2020

2019

Self-Admitted Technical Debt Removal and Refactoring Actions: Co-Occurrence or More?

Martina Iammarino, Fiorella Zampetti, Lerina Aversano, Massimiliano Di Penta

Proceedings of the 2019 IEEE International Conference on Software Maintenance and Evolution, 2019