Elena Resmerita

17 papers Journal 16Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Applications of Multiscale Hierarchical Decomposition to Blind Deconvolution. Multiscale Model. Simul. Tobias Wolf, Stefan Kindermann, Elena Resmerita, Luminita A. Vese
2025	J	`jnl`	Multiscale Hierarchical Decomposition Methods for Images Corrupted by Multiplicative Noise. J. Math. Imaging Vis. Joel Barnett, Wen Li, Elena Resmerita, Luminita A. Vese
2025	J	`jnl`	Nested Bregman Iterations for Decomposition Problems. SIAM J. Imaging Sci. Tobias Wolf, Derek Driggs, Kostas Papafitsoros, Elena Resmerita, Carola-Bibiane Schönlieb
2024	J	`jnl`	Applications of multiscale hierarchical decomposition to blind deconvolution. CoRR Tobias Wolf, Stefan Kindermann, Elena Resmerita, Luminita A. Vese
2024	J	`jnl`	Higher order error estimates for regularization of inverse problems under non-additive noise. CoRR Diana-Elena Mirciu, Elena Resmerita
2024	J	`jnl`	Nested Bregman Iterations for Decomposition Problems. CoRR Tobias Wolf, Derek Driggs, Kostas Papafitsoros, Elena Resmerita, Carola-Bibiane Schönlieb
2023	J	`jnl`	Multiscale hierarchical decomposition methods for ill-posed problems. CoRR Stefan Kindermann, Elena Resmerita, Tobias Wolf
2023	J	`jnl`	Multiscale hierarchical decomposition methods for images corrupted by multiplicative noise. CoRR Joel Barnett, Wen Li, Elena Resmerita, Luminita A. Vese
2022	J	`jnl`	On Hamilton-Jacobi PDEs and Image Denoising Models with Certain Nonadditive Noise. J. Math. Imaging Vis. Jérôme Darbon, Tingwei Meng, Elena Resmerita
2021	J	`jnl`	Multiscale Hierarchical Image Decomposition and Refinements: Qualitative and Quantitative Results. SIAM J. Imaging Sci. Wen Li, Elena Resmerita, Luminita A. Vese
2021	J	`jnl`	Nonconvex flexible sparsity regularization: theory and monotone numerical schemes. CoRR Daria Ghilli, Dirk A. Lorenz, Elena Resmerita
2021	J	`jnl`	On Hamilton-Jacobi PDEs and image denoising models with certain non-additive noise. CoRR Jérôme Darbon, Tingwei Meng, Elena Resmerita
2019	J	`jnl`	An entropic projection method for linear ill-posed problems. CoRR Martin Burger, Elena Resmerita, Martin Benning
2012	J	`jnl`	Dual Norm Based Iterative Methods for Image Restoration. J. Math. Imaging Vis. Miyoun Jung, Elena Resmerita, Luminita A. Vese
2011	J	`jnl`	Morozov's Principle for the Augmented Lagrangian Method Applied to Linear Inverse Problems. Multiscale Model. Simul. Klaus Frick, Dirk A. Lorenz, Elena Resmerita
2010	—	`conf`	An Iterative Method with General Convex Fidelity Term for Image Restoration. ECCV (1) Miyoun Jung, Elena Resmerita, Luminita A. Vese
2007	J	`jnl`	Error estimation for Bregman iterations and inverse scale space methods in image restoration. Computing Martin Burger, Elena Resmerita, Lin He

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.