Daniel Franco-Barranco

13 papers Journal 8Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	SAMJ: Fast Image Annotation on ImageJ/Fiji via Segment Anything Model. CoRR Carlos Garcia-Lopez-de-Haro, Caterina Fuster-Barceló, Curtis T. Rueden, Jónathan Heras, Vladimír Ulman, Daniel Franco-Barranco, Adrián Inés, Kevin W. Eliceiri, Jean-Christophe Olivo-Marin, Jean-Yves Tinevez, Daniel Sage, Arrate Muñoz-Barrutia
2025	—	`conf`	Super-Resolution Benchmarking for 3D Image-to-Image Fusion Problem. ISBI Daniel Franco-Barranco, Aitor González-Marfil, Albert Cardona, Arrate Muñoz-Barrutia, Ignacio Arganda-Carreras
2025	J	`jnl`	Towards Generalized Synapse Detection Across Invertebrate Species. CoRR Samia Mohinta, Daniel Franco-Barranco, Shi Yan Lee, Albert Cardona
2024	J	`jnl`	A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features. Nat. Mac. Intell. Davide Carnevali, Limei Zhong, Esther González-Almela, Carlotta Viana, Mikhail Rotkevich, Aiping Wang, Daniel Franco-Barranco, Aitor González-Marfil, Maria Victoria Neguembor, Alvaro Castells-Garcia, Ignacio Arganda-Carreras, Maria Pia Cosma
2024	—	`conf`	Self-supervised Vision Transformers for image-to-image labeling: a BiaPy solution to the LightMyCells Challenge. ISBI Daniel Franco-Barranco, Aitor González-Marfil, Ignacio Arganda-Carreras
2023	—	`conf`	BiaPy: a ready-to-use library for Bioimage Analysis Pipelines. ISBI Daniel Franco-Barranco, Jesús A. Andrés-San Román, Pedro Gómez-Gálvez, Luis M. Escudero, Arrate Muñoz-Barrutia, Ignacio Arganda-Carreras
2023	J	`jnl`	Current Progress and Challenges in Large-Scale 3D Mitochondria Instance Segmentation. IEEE Trans. Medical Imaging Daniel Franco-Barranco, Zudi Lin, Won-Dong Jang, Xueying Wang, Qijia Shen, Wenjie Yin, Yutian Fan, Mingxing Li, Chang Chen, Zhiwei Xiong, Rui Xin, Hao Liu, Huai Chen, Zhili Li, Jie Zhao, Xuejin Chen, Constantin Pape, Ryan Conrad, Luke Nightingale, Joost de Folter, Martin L. Jones, Yanling Liu, Dorsa Ziaei, Stephan Huschauer, Ignacio Arganda-Carreras, Hanspeter Pfister, Donglai Wei
2023	—	`conf`	Modeling Wound Healing Using Vector Quantized Variational Autoencoders and Transformers. ISBI Lenka Backová, Guillermo Bengoetxea, Svana Rogalla, Daniel Franco-Barranco, Jérôme Solon, Ignacio Arganda-Carreras
2022	J	`jnl`	Deep learning based domain adaptation for mitochondria segmentation on EM volumes. Comput. Methods Programs Biomed. Daniel Franco-Barranco, Julio Pastor-Tronch, Aitor González-Marfil, Arrate Muñoz-Barrutia, Ignacio Arganda-Carreras
2022	J	`jnl`	Deep learning based domain adaptation for mitochondria segmentation on EM volumes. CoRR Daniel Franco-Barranco, Julio Pastor-Tronch, Aitor González-Marfil, Arrate Muñoz-Barrutia, Ignacio Arganda-Carreras
2022	J	`jnl`	Stable Deep Neural Network Architectures for Mitochondria Segmentation on Electron Microscopy Volumes. Neuroinformatics Daniel Franco-Barranco, Arrate Muñoz-Barrutia, Ignacio Arganda-Carreras
2021	J	`jnl`	Stable deep neural network architectures for mitochondria segmentation on electron microscopy volumes. CoRR Daniel Franco-Barranco, Arrate Muñoz-Barrutia, Ignacio Arganda-Carreras
2020	—	`conf`	MitoEM Dataset: Large-Scale 3D Mitochondria Instance Segmentation from EM Images. MICCAI (5) Donglai Wei, Zudi Lin, Daniel Franco-Barranco, Nils Wendt, Xingyu Liu, Wenjie Yin, Xin Huang, Aarush Gupta, Won-Dong Jang, Xueying Wang, Ignacio Arganda-Carreras, Jeff W. Lichtman, Hanspeter Pfister

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.