Daniele Berardini

19 papers C 1Journal 10Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	A Modular and Efficient Framework for the Development of Large Language Model-Based Virtual Humans: An Educational Scenario. ICIAP (Workshops 1) Michele Giordano, Daniele Berardini, Emanuele Frontoni, Primo Zingaretti, Lorenzo Stacchio
2025	J	`jnl`	Edge artificial intelligence and super-resolution for enhanced weapon detection in video surveillance. Eng. Appl. Artif. Intell. Daniele Berardini, Lucia Migliorelli, Alessandro Galdelli, Manuel J. Marín-Jiménez
2025	J	`jnl`	Improving real-time detection of laryngeal lesions in endoscopic images using a decoupled super-resolution enhanced YOLO. Comput. Methods Programs Biomed. Chiara Baldini, Lucia Migliorelli, Daniele Berardini, Muhammad Adeel Azam, Claudio Sampieri, Alessandro Ioppi, Rakesh Srivastava, Giorgio Peretti, Leonardo S. Mattos
2025	J	`jnl`	Online Knowledge Distillation and Deep Supervision in HRNet: Green AI for Preterm Infants' Pose Estimation. ACM Trans. Comput. Heal. Alessandro Cacciatore, Daniele Berardini, Vito Scaraggi, Adriano Mancini, Sara Moccia, Lucia Migliorelli
2024	—	`conf`	A Monitoring Support System Based on HRNet+DEKR for Neonatal Intensive Care Units. BMVC Workshops Greta Di Marino, Lucia Migliorelli, Sara Moccia, Matteo Lorenzo Bramucci, Jacopo Carpaneto, Alessandro Cacciatore, Daniele Berardini
2024	J	`jnl`	A deep-learning framework running on edge devices for handgun and knife detection from indoor video-surveillance cameras. Multim. Tools Appl. Daniele Berardini, Lucia Migliorelli, Alessandro Galdelli, Emanuele Frontoni, Adriano Mancini, Sara Moccia
2024	J	`jnl`	A preliminary study on continual learning in computer vision using Kolmogorov-Arnold Networks. CoRR Alessandro Cacciatore, Valerio Morelli, Federica Paganica, Emanuele Frontoni, Lucia Migliorelli, Daniele Berardini
2024	—	`conf`	Benchmark Analysis of YOLOv8 for Edge AI Video-Surveillance Applications. MESA Daniele Berardini, Lucia Migliorelli, Lorenzo Cardoni, Christian Parente, Alessandro Rongoni, Daniele Sergiacomi, Adriano Mancini
2024	—	`conf`	Edge-AI for Buoy Detection and Mussel Farming: A Comparative Study of YOLO Frameworks. MESA Gagan Narang, Daniele Berardini, Rocco Pietrini, Anna Nora Tassetti, Adriano Mancini, Alessandro Galdelli
2023	—	`conf`	A preliminary study on self-care telemonitoring of dysarthria in spinal muscular atrophy. EMBC Lucia Migliorelli, Sara Moccia, Daniele Berardini, Emanuele Frontoni, Michela Coccia, Laura Villani, Andrea Bandini
2023	J	`jnl`	A store-and-forward cloud-based telemonitoring system for automatic assessing dysarthria evolution in neurological diseases from video-recording analysis. Comput. Biol. Medicine Lucia Migliorelli, Daniele Berardini, Kevin Cela, Michela Coccia, Laura Villani, Emanuele Frontoni, Sara Moccia
2023	J	`jnl`	A store-and-forward cloud-based telemonitoring system for automatic assessing dysarthria evolution in neurological diseases from video-recording analysis. CoRR Lucia Migliorelli, Daniele Berardini, Kevin Cela, Michela Coccia, Laura Villani, Emanuele Frontoni, Sara Moccia
2023	J	`jnl`	Deep learning-based approaches for human motion decoding in smart walkers for rehabilitation. CoRR Carolina Gonçalves, João M. Lopes, Sara Moccia, Daniele Berardini, Lucia Migliorelli, Cristina P. Santos
2023	J	`jnl`	Deep learning-based approaches for human motion decoding in smart walkers for rehabilitation. Expert Syst. Appl. Carolina Gonçalves, João M. Lopes, Sara Moccia, Daniele Berardini, Lucia Migliorelli, Cristina P. Santos
2023	J	`jnl`	TwinEDA: a sustainable deep-learning approach for limb-position estimation in preterm infants' depth images. Medical Biol. Eng. Comput. Lucia Migliorelli, Alessandro Cacciatore, Valeria Ottaviani, Daniele Berardini, Raffaele L. Dellacà, Emanuele Frontoni, Sara Moccia
2022	—	`conf`	Benchmarking of Dual-Step Neural Networks for Detection of Dangerous Weapons on Edge Devices. MESA Daniele Berardini, Alessandro Galdelli, Adriano Mancini, Primo Zingaretti
2022	—	`conf`	Some Ethical Remarks on Deep Learning-Based Movements Monitoring for Preterm Infants: Green AI or Red AI? ICIAP Workshops Alessandro Cacciatore, Lucia Migliorelli, Daniele Berardini, Simona Tiribelli, Stefano Pigliapoco, Sara Moccia
2021	—	`conf`	Asymmetric Three-dimensional Convolutions For Preterm Infants' Pose Estimation. EMBC Lucia Migliorelli, Daniele Berardini, Francesca Rossini, Emanuele Frontoni, Virginio Paolo Carnielli, Sara Moccia
2020	C	`conf`	Evaluating the autonomy of children with autism spectrum disorder in washing hands: a deep-learning approach. ISCC Daniele Berardini, Lucia Migliorelli, Sara Moccia, Marcello Naldini, Gioia De Angelis, Emanuele Frontoni

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.