Marco Russodivito

According to our database, Marco Russodivito authored at least 7 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2024

Machine Learning-Based Qualitative Analysis of Human Gait Through Video Features.

Nicoletta Balletti, Roberto Zinni, Marco Russodivito, Gennaro Laudato, Simone Scalabrino, Rocco Oliveto

Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies, 2024

2023

StegWare: A Novel Malware Model Exploiting Payload Steganography and Dynamic Compilation.

Daniele Albanese, Rosangela Casolare, Giovanni Ciaramella, Giacomo Iadarola, Fabio Martinelli, Francesco Mercaldo, Marco Russodivito, Antonella Santone

Proceedings of the 9th International Conference on Information Systems Security and Privacy, 2023

2022

2Faces: a new model of malware based on dynamic compiling and reflection.

Rosangela Casolare, Giovanni Lacava, Fabio Martinelli, Francesco Mercaldo, Marco Russodivito, Antonella Santone

J. Comput. Virol. Hacking Tech., 2022

ST-Segment Anomalies Detection from Compressed Sensing Based ECG Data by Means of Machine Learning.

Giovanni Rosa, Marco Russodivito, Gennaro Laudato, Angela Rita Colavita, Luca De Vito, Francesco Picariello, Simone Scalabrino, Ioan Tudosa, Rocco Oliveto

Proceedings of the Biomedical Engineering Systems and Technologies, 2022

A Robust Approach for a Real-time Accurate Screening of ST Segment Anomalies.

Giovanni Rosa, Marco Russodivito, Gennaro Laudato, Angela Rita Colavita, Simone Scalabrino, Rocco Oliveto

Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies, 2022

2021

A Multi-Class Approach for the Automatic Detection of Congestive Heart Failure in Windowed ECG.

Giovanni Rosa, Marco Russodivito, Gennaro Laudato, Simone Scalabrino, Angela Rita Colavita, Rocco Oliveto

Proceedings of the MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation, 2021

Multi-class Detection of Arrhythmia Conditions Through the Combination of Compressed Sensing and Machine Learning.

Giovanni Rosa, Marco Russodivito, Gennaro Laudato, Angela Rita Colavita, Luca De Vito, Francesco Picariello, Simone Scalabrino, Ioan Tudosa, Rocco Oliveto

Proceedings of the Biomedical Engineering Systems and Technologies, 2021