Short Bio

Daniele Baracchi received the bachelor’s and master’s degrees in computer engineering and the Ph.D. degree in information engineering from the University of Florence. He is currently a Postdoctoral Fellow with the University of Florence, where he has been a member of the Image Analysis, Processing, and Protection Research Group, Department of Information Engineering, since 2018. In this role, he is actively engaged in the development of machine learning-based techniques for multimedia forensics. Over the past four years, he has contributed to research initiatives supported by both the U.S. Defense Advanced Research Projects Agency (DARPA) and the Italian Ministry of University and Research (MUR)

Research interests

Multimedia forensics and digital watermarking with a particular focus on data-driven approaches.

Publications

• Giulia Bertazzini, Daniele Baracchi, Dasara Shullani, Massimo Iuliani, and Alessandro Piva, "CoFFEE: a codec-based forensic feature extraction and evaluation software for H.264 videos.", EURASIP JIS, 2024
• Daniele Baracchi, Giulia Boato, Francesco De Natale, Massimo Iuliani, Andrea Montibeller, Cecilia Pasquini, Alessandro Piva, and Dasara Shullani, "Towards open-world multimedia forensics through media signature encoding", IEEE Access, 2024
• Paolo Frasconi, Daniele Baracchi, Betti Giusti, Ada Kura, Gaia Spaziani, Antonella Cherubini, Silvia Favilli, Andrea Di Lenarda, Guglielmina Pepe, and Stefano Nistri, "Two-dimensional aortic size normalcy: A novelty detection approach", Diagnostics, 2023
• Andrea Gemelli, Dasara Shullani, Daniele Baracchi, Simone Marinai, and Alessandro Piva, "Structure Matters: Analyzing Videos Via Graph Neural Networks for Social Media Platform Attribution.", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024
• Giulia Bertazzini, Daniele Baracchi, Dasara Shullani, Massimo Iuliani, and Alessandro Piva, "A Codec-Based Approach for Video Life-Cycle Characterization in Social Networks.", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024
• Simone Magistri, Daniele Baracchi, Dasara Shullani, Andrew D. Bagdanov, and Alessandro Piva, "Continual learning for adaptive social network identification.", Pattern Recognition Letters, 2024
• Daniele Baracchi, Dasara Shullani, Massimo Iuliani, Damiano Giani, and Alessandro Piva, "Uncovering the authorship: Linking media content to social user profiles.", Pattern Recognition Letters, 2024
• Simone Magistri, Daniele Baracchi, Dasara Shullani, Andrew D. Bagdanov, and Alessandro Piva, "Towards Continual Social Network Identification.", International Workshop on Biometrics and Forensics (IWBF), 2023
• Daniele Baracchi, Dasara Shullani, Massimo Iuliani, and Alessandro Piva, "FloreView: An Image and Video Dataset for Forensic Analysis.", IEEE Access, 2023
• Dasara Shullani, Daniele Baracchi, Massimo Iuliani, and Alessandro Piva, "Social Network Identification of Laundered Videos Based on DCT Coefficient Analysis.", IEEE Signal Processing Letters, 2022
• Daniele Baracchi, Dasara Shullani, Massimo Iuliani, Damiano Giani, and Alessandro Piva, "Camera Obscura: Exploiting in-camera processing for image counter forensics.", Forensic Science International: Digital Investigation, 2021
• Daniele Baracchi, Massimo Iuliani, Andrea G. Nencini, and Alessandro Piva, "Facing Image Source Attribution on iPhone X.", IWDW, 2020
• Pengpeng Yang, Daniele Baracchi, Massimo Iuliani, Dasara Shullani, Rongrong Ni, Yao Zhao, and Alessandro Piva, "Efficient Video Integrity Analysis Through Container Characterization.", IEEE Journal of Selected Topics in Signal Processing, 2020
• Pengpeng Yang, Daniele Baracchi, Rongrong Ni, Yao Zhao, Fabrizio Argenti, and Alessandro Piva, "A Survey of Deep Learning-Based Source Image Forensics.", Journal of Imaging, 2020
• Benjamin Hadwiger, Daniele Baracchi, Alessandro Piva, and Christian Riess, "Towards Learned Color Representations for Image Splicing Detection.", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
• Francesco Orsini, Daniele Baracchi, and Paolo Frasconi, "Shift Aggregate Extract Networks.", Frontiers in Robotics and AI, 2018