Fangfang Qiang

18 papers Journal 17Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Lightweight Scope Integration Network for Rail Surface Defect Detection. IEEE Trans. Big Data Wujie Zhou, Yue Wu, Fangfang Qiang, Weiqing Yan
2026	J	`jnl`	Multi-stream interaction network with cross-modal contrast distillation for co-salient object detection. Signal Process. Image Commun. Wujie Zhou, Bingying Wang, Xiena Dong, Caie Xu, Fangfang Qiang
2025	J	`jnl`	AESeg: Affinity-enhanced segmenter using feature class mapping knowledge distillation for efficient RGB-D semantic segmentation of indoor scenes. Neural Networks Wujie Zhou, Yuxiang Xiao, Fangfang Qiang, Xiena Dong, Caie Xu, Lu Yu
2025	J	`jnl`	Depth Enhancement Mask Mapping Network With Multi-Teacher Distillation for RGB-D Scene Parsing. IEEE Trans Autom. Sci. Eng. Yuxiang Xiao, Jiajun Meng, Fangfang Qiang, Xiena Dong, Wujie Zhou
2025	J	`jnl`	IIBNet: Inter- and Intra-Information balance network with Self-Knowledge distillation and region attention for RGB-D indoor scene parsing. Expert Syst. Appl. Yuming Zhang, Fangfang Qiang, Wujie Zhou, Weiqing Yan, Lv Ye
2025	J	`jnl`	Location, Neighborhood, and Semantic Guidance Network for RGB-D Co-Salient Object Detection. IEEE Trans. Artif. Intell. Wujie Zhou, Bingying Wang, Xiena Dong, Caie Xu, Fangfang Qiang
2025	J	`jnl`	PFCNet: Enhancing Rail Surface Defect Detection With Pixel-Aware Frequency Conversion Networks. IEEE Signal Process. Lett. Yue Wu, Fangfang Qiang, Wujie Zhou, Weiqing Yan
2024	J	`jnl`	ACENet: Auxiliary Context-Information Enhancement Network for RGB-D Indoor Scene Semantic Segmentation. IEEE Trans. Emerg. Top. Comput. Intell. Wujie Zhou, Gao Xu, Fangfang Qiang, Lu Yu
2024	J	`jnl`	ADRNet-S*: Asymmetric depth registration network via contrastive knowledge distillation for RGB-D mirror segmentation. Inf. Fusion Wujie Zhou, Yuqi Cai, Xiena Dong, Fangfang Qiang, Weiwei Qiu
2024	J	`jnl`	Effective Bi-decoding networks for rail-surface defect detection by knowledge distillation. Appl. Soft Comput. Wujie Zhou, Yue Wu, Weiwei Qiu, Caie Xu, Fangfang Qiang
2024	J	`jnl`	Graph Enhancement and Transformer Aggregation Network for RGB-Thermal Crowd Counting. IEEE Geosci. Remote. Sens. Lett. Yi Pan, Wujie Zhou, Meixin Fang, Fangfang Qiang
2024	J	`jnl`	Morphology-Guided Network via Knowledge Distillation for RGB-D Mirror Segmentation. IEEE Trans. Intell. Transp. Syst. Wujie Zhou, Yuqi Cai, Fangfang Qiang
2024	J	`jnl`	Node positioning based on IPSO-IDE in WSNs. Evol. Intell. Zheng Lv, Fangfang Qiang, Yu Zhan
2024	J	`jnl`	STONet-S*: A Knowledge-Distilled Approach for Semantic Segmentation in Remote Sensing Images. IEEE Trans. Geosci. Remote. Sens. Wujie Zhou, Penghan Yang, Weiwei Qiu, Fangfang Qiang
2023	J	`jnl`	Intelligent Anti-Jamming Decision With Continuous Action and State in Bivariate Frequency Agility Communication System. IEEE Trans. Cogn. Commun. Netw. Yupei Zhang, Zhijin Zhao, Shilian Zheng, Fangfang Qiang
2020	J	`jnl`	Estimation of spreading sequences in LC-DS-CDMA signals based on sparse auto-encoder. Evol. Intell. Fangfang Qiang, Zhijin Zhao, Junna Shang, Lei Shen
2018	—	`conf`	TCF-SAE Algorithm for m-Sequence Recognition. FSDM Fangfang Qiang, Zhijin Zhao, Ying Chen, Lei Shen, Xianyang Jiang
2017	J	`jnl`	Blind Estimation of PN Codes in Multi-user LSC-DSSS Signals. J. Commun. Zhijin Zhao, Xiaowei Gu, Fangfang Qiang, Lei Shen

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.