Le-Bing Zhang - RankMe

20 papers A 1C 2Journal 15Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FARL: deepfake detection based on adaptive feature aggregation and reconstruction learning. Int. J. Auton. Adapt. Commun. Syst. Min Long, Chun-Lung Philip Chen, Le-Bing Zhang, Fei Peng
2025	J	`jnl`	A styleGAN-based face de-morphing network for restoring accomplice's facial image. Multim. Syst. Juan Cai, Min Long, Le-Bing Zhang, Quantao Yao, Xiangling Ding
2025	J	`jnl`	DFS-Net: StyleGAN2-based dual feature separation for face De-Morphing. Multim. Tools Appl. Ming Long, Song Chen, Le-Bing Zhang, Fei Peng, Dengyong Zhang
2025	J	`jnl`	Face de-morphing based on identity feature transfer. IET Image Process. Le-Bing Zhang, Song Chen, Min Long, Juan Cai
2025	J	`jnl`	LGDF-Net: Local and Global Feature-Based Dual-Branch Fusion Networks for Deepfake Detection. IEEE Trans. Circuits Syst. Video Technol. Min Long, Zhenyu Liu, Le-Bing Zhang, Fei Peng
2024	J	`jnl`	ADFF: Adaptive de-morphing factor framework for restoring accomplice's facial image. IET Image Process. Min Long, Jun Zhou, Le-Bing Zhang, Fei Peng, Dengyong Zhang
2024	J	`jnl`	Face De-Morphing Based on Diffusion Autoencoders. IEEE Trans. Inf. Forensics Secur. Min Long, Quantao Yao, Le-Bing Zhang, Fei Peng
2024	J	`jnl`	Feature Interaction-Based Face De-Morphing Factor Prediction for Restoring Accomplice's Facial Image. Sensors Juan Cai, Qiangqiang Duan, Min Long, Le-Bing Zhang, Xiangling Ding
2024	J	`jnl`	One-Class Hybrid Heterogeneous Network for Detecting HEVC Double Compression With the Same Coding Parameters. IEEE Internet Things J. Xiangling Ding, Yulin Zhao, Le-Bing Zhang, Yunyi Li
2024	J	`jnl`	Trans-FD: Transformer-Based Representation Interaction for Face De-Morphing. IEEE Trans. Biom. Behav. Identity Sci. Min Long, Qiangqiang Duan, Le-Bing Zhang, Fei Peng, Dengyong Zhang
2023	—	`conf`	CALP-FD: Cross Attention-Based Facial Landmarks Prompt for Face De-Morphing. ICSAI Min Long, Qihuan Wang, Le-Bing Zhang, Jun Zhou
2021	C	`conf`	MSA-CNN: Face Morphing Detection via a Multiple Scales Attention Convolutional Neural Network. IWDW Le-Bing Zhang, Juan Cai, Fei Peng, Min Long
2020	J	`jnl`	CGR-GAN: CG Facial Image Regeneration for Antiforensics Based on Generative Adversarial Network. IEEE Trans. Multim. Fei Peng, Liping Yin, Le-Bing Zhang, Min Long
2019	J	`jnl`	FD-GAN: Face De-Morphing Generative Adversarial Network for Restoring Accomplice's Facial Image. IEEE Access Fei Peng, Le-Bing Zhang, Min Long
2018	J	`jnl`	FD-GAN: Face-demorphing generative adversarial network for restoring accomplice's facial image. CoRR Fei Peng, Le-Bing Zhang, Min Long
2018	A	`conf`	Face Morphing Detection Using Fourier Spectrum of Sensor Pattern Noise. ICME Le-Bing Zhang, Fei Peng, Min Long
2018	J	`jnl`	Face spoofing detection based on color texture Markov feature and support vector machine recursive feature elimination. J. Vis. Commun. Image Represent. Le-Bing Zhang, Fei Peng, Le Qin, Min Long
2017	—	`conf`	Content-Independent Face Presentation Attack Detection with Directional Local Binary Pattern. CCBR Le Qin, Le-Bing Zhang, Fei Peng, Min Long
2017	J	`jnl`	Identifying source camera using guided image estimation and block weighted average. J. Vis. Commun. Image Represent. Le-Bing Zhang, Fei Peng, Min Long
2016	C	`conf`	Source Camera Identification Based on Guided Image Estimation and Block Weighted Average. IWDW Le-Bing Zhang, Fei Peng, Min Long

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.