Dai-Qiang Chen

25 papers Journal 25

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Exacter set-level nonlocal attention mechanism based on learning weights for image denoising. Pattern Anal. Appl. Dai-Qiang Chen, Ying-Chun Chen
2025	J	`jnl`	Hybrid sparse and dense attentions of similar regions for image denoising. Signal Image Video Process. Dai-Qiang Chen
2024	J	`jnl`	Down-scale simplified non-local attention networks with application to image denoising. Signal Image Video Process. Dai-Qiang Chen
2017	J	`jnl`	Inexact alternating direction method based on Newton descent algorithm with application to Poisson image deblurring. Signal Image Video Process. Dai-Qiang Chen
2016	J	`jnl`	Data-Driven Tight Frame Learning Scheme Based on Local and Non-local Sparsity with Application to Image Recovery. J. Sci. Comput. Dai-Qiang Chen
2016	J	`jnl`	Fixed point algorithm based on adapted metric method for convex minimization problem with application to image deblurring. Adv. Comput. Math. Dai-Qiang Chen, Yan Zhou, Li-Juan Song
2016	J	`jnl`	Inexact alternating direction method based on proximity projection operator for image inpainting in wavelet domain. Neurocomputing Dai-Qiang Chen, Yan Zhou
2016	J	`jnl`	Primal-dual algorithm based on Gauss-Seidel scheme with application to multiplicative noise removal. J. Comput. Appl. Math. Dai-Qiang Chen, Xinpeng Du, Yan Zhou
2016	J	`jnl`	Wavelet Frame Based Image Restoration via Combined Sparsity and Nonlocal Prior of Coefficients. J. Sci. Comput. Dai-Qiang Chen, Yan Zhou
2015	J	`jnl`	Active contours driven by localizing region and edge-based intensity fitting energy with application to segmentation of the left ventricle in cardiac CT images. Neurocomputing Yan Zhou, Weiren Shi, Wei Chen, Yong-Lin Chen, Ying Li, Li-Wen Tan, Dai-Qiang Chen
2015	J	`jnl`	Image denoising based on improved data-driven sparse representation. CoRR Dai-Qiang Chen
2014	J	`jnl`	A simulated annealing algorithm for sparse recovery by l Neurocomputing Xinpeng Du, Lizhi Cheng, Dai-Qiang Chen
2014	J	`jnl`	Fast linearized alternating direction minimization algorithm with adaptive parameter selection for multiplicative noise removal. J. Comput. Appl. Math. Dai-Qiang Chen, Lizhi Cheng
2014	J	`jnl`	Fixed Point Algorithm Based on Quasi-Newton Method for Convex Minimization Problem with Application to Image Deblurring. CoRR Dai-Qiang Chen
2014	J	`jnl`	Inexact Alternating Direction Method Based on Proximal Hessian Matrix with Application to Poisson Image Deblurring. CoRR Dai-Qiang Chen
2014	J	`jnl`	Multiplicative Denoising Based on Linearized Alternating Direction Method Using Discrepancy Function Constraint. J. Sci. Comput. Dai-Qiang Chen, Yan Zhou
2014	J	`jnl`	Regularized Generalized Inverse Accelerating Linearized Alternating Minimization Algorithm for Frame-Based Poissonian Image Deblurring. SIAM J. Imaging Sci. Dai-Qiang Chen
2013	J	`jnl`	A reduced IET Signal Process. Xinpeng Du, Dai-Qiang Chen, Lizhi Cheng
2013	J	`jnl`	Fast Linearized Alternating Direction Minimization Algorithm with Adaptive Parameter Selection for Multiplicative Noise Removal. CoRR Dai-Qiang Chen, Lizhi Cheng
2013	J	`jnl`	Novel variational model for inpainting in the wavelet domain CoRR Dai-Qiang Chen, Lizhi Cheng
2012	J	`jnl`	A Fast Fixed Point Algorithm for Total Variation Deblurring and Segmentation. J. Math. Imaging Vis. Dai-Qiang Chen, Hui Zhang, Lizhi Cheng
2012	J	`jnl`	A New TV-Stokes Model with Augmented Lagrangian Method for Image Denoising and Deconvolution. J. Sci. Comput. Dai-Qiang Chen, Lizhi Cheng, Fang Su
2012	J	`jnl`	Spatially Adapted Total Variation Model to Remove Multiplicative Noise. IEEE Trans. Image Process. Dai-Qiang Chen, Lizhi Cheng
2011	J	`jnl`	Deconvolving Poissonian images by a novel hybrid variational model. J. Vis. Commun. Image Represent. Dai-Qiang Chen, Lizhi Cheng
2011	J	`jnl`	Restoration of images based on subspace optimization accelerating augmented Lagrangian approach. J. Comput. Appl. Math. Dai-Qiang Chen, Lizhi Cheng, Fang Su

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.