Zhen Yang - RankMe

11 papers Journal 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Open-IndDet: Advancing Open-Set Industrial Surface Defect Detection via Robust Class-Unique Feature Representation. IEEE Trans. Circuits Syst. Video Technol. Zhen Yang, Tianyong Zheng, Xuefeng Ni, Zhi Yan, Hong Chen, Yaonan Wang, Leyuan Fang
2025	J	`jnl`	HSLabeling: Toward Efficient Labeling for Large-Scale Remote Sensing Image Segmentation With Hybrid Sparse Labeling. IEEE Trans. Image Process. Jiaxing Lin, Zhen Yang, Qiang Liu, Yinglong Yan, Pedram Ghamisi, Weiying Xie, Leyuan Fang
2024	J	`jnl`	Infrared Small Target Detection Method Based on High-Low-Frequency Semantic Reconstruction. IEEE Geosci. Remote. Sens. Lett. Tianfeng Ma, Guanqin Guo, Zhimeng Li, Zhen Yang
2024	J	`jnl`	MCDNet: An Infrared Small Target Detection Network Using Multi-Criteria Decision and Adaptive Labeling Strategy. IEEE Trans. Geosci. Remote. Sens. Tianlei Ma, Qi Ma, Zhen Yang, Jing J. Liang, Jun Fu, Yu Dou, Yanan Ku, Usman Ahmad, Liangqiong Qu
2024	J	`jnl`	Open Set Recognition in Real World. Int. J. Comput. Vis. Zhen Yang, Jun Yue, Pedram Ghamisi, Shiliang Zhang, Jiayi Ma, Leyuan Fang
2023	J	`jnl`	A Lightweight Infrared Small Target Detection Network Based on Target Multiscale Context. IEEE Geosci. Remote. Sens. Lett. Tianlei Ma, Zhen Yang, Benxue Liu, Siyuan Sun
2023	J	`jnl`	DMEF-Net: Lightweight Infrared Dim Small Target Detection Network for Limited Samples. IEEE Trans. Geosci. Remote. Sens. Tianlei Ma, Zhen Yang, Yi-Fan Song, Jing J. Liang, Heshan Wang
2022	J	`jnl`	DFFIR-net: Infrared Dim Small Object Detection Network Constrained by Gray-level Distribution Model. IEEE Trans. Instrum. Meas. Zhen Yang, Tianlei Ma, Yanan Ku, Qi Ma, Jun Fu
2022	J	`jnl`	Infrared Small Target Detection Based on Smoothness Measure and Thermal Diffusion Flowmetry. IEEE Geosci. Remote. Sens. Lett. Tianlei Ma, Zhen Yang, Xiangyang Ren, Jiaqi Wang, Yanan Ku
2022	J	`jnl`	Infrared Small Target Detection Network With Generate Label and Feature Mapping. IEEE Geosci. Remote. Sens. Lett. Tianlei Ma, Zhen Yang, Jiaqi Wang, Siyuan Sun, Xiangyang Ren, Usman Ahmad
2022	J	`jnl`	Lightweight Remote Sensing Road Detection Network. IEEE Geosci. Remote. Sens. Lett. Siyuan Sun, Zhen Yang, Tianlei Ma

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.