Qinxiang Zheng

12 papers Journal 10Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Progressive Distillation for Incremental Learning in Corneal Confocal Microscopy Segmentation. IEEE Trans. Medical Imaging Hongshuo Li, Baikai Ma, Lei Mou, Yonghuai Liu, Qinxiang Zheng, Hong Qi, Yitian Zhao
2025	J	`jnl`	Adaptive boundary-enhanced Dice loss for image segmentation. Biomed. Signal Process. Control. Yanyan Zheng, Bihan Tian, Shuchen Yu, Xiaoguo Yang, Qingxiang Yu, Jie Zhou, Gaoqiang Jiang, Qinxiang Zheng, Jiantao Pu, Lei Wang
2024	J	`jnl`	CorNet: Autonomous feature learning in raw Corvis ST data for keratoconus diagnosis via residual CNN approach. Comput. Biol. Medicine PeiPei Zhang, Lanting Yang, Yicheng Mao, Xinyu Zhang, Jiaxuan Cheng, Yuanyuan Miao, Fangjun Bao, Shihao Chen, Qinxiang Zheng, Junjie Wang
2024	J	`jnl`	Deep learning for multi-type infectious keratitis diagnosis: A nationwide, cross-sectional, multicenter study. npj Digit. Medicine Zhongwen Li, He Xie, Zhouqian Wang, Daoyuan Li, Kuan Chen, Xihang Zong, Wei Qiang, Feng Wen, Zhihong Deng, Limin Chen, Huiping Li, He Dong, Pengcheng Wu, Tao Sun, Yan Cheng, Yanning Yang, Jinsong Xue, Qinxiang Zheng, Jiewei Jiang, Wei Chen
2023	J	`jnl`	Automated segmentation of optic disc and cup depicted on color fundus images using a distance-guided deep learning strategy. Biomed. Signal Process. Control. Juan Zhang, Chenyang Mei, Zhongwen Li, Jianing Ying, Qinxiang Zheng, Quanyong Yi, Lei Wang
2023	J	`jnl`	Automated segmentation of palpebral fissures from eye videography using a texture fusion neural network. Biomed. Signal Process. Control. Qinxiang Zheng, Zhongwen Li, Juan Zhang, Chenyang Mei, Guangyu Li, Lei Wang
2023	—	`conf`	Structure Constrained Diffusion Models for Pterygium Segmentation. ISBI Xinyu Guo, Zhouqian Wang, Huaying Hao, Qinxiang Zheng, Jiong Zhang, Wei Chen, Yitian Zhao
2022	J	`jnl`	A texture-aware U-Net for identifying incomplete blinking from eye videography. Biomed. Signal Process. Control. Qinxiang Zheng, Xin Zhang, Juan Zhang, Furong Bai, Shenghai Huang, Jiantao Pu, Wei Chen, Lei Wang
2021	J	`jnl`	Development of a deep learning-based image eligibility verification system for detecting and filtering out ineligible fundus images: A multicentre study. Int. J. Medical Informatics Zhongwen Li, Jiewei Jiang, Heding Zhou, Qinxiang Zheng, Xiaotian Liu, Kuan Chen, Hongfei Weng, Wei Chen
2021	J	`jnl`	Development of a deep learning-based image quality control system to detect and filter out ineligible slit-lamp images: A multicenter study. Comput. Methods Programs Biomed. Zhongwen Li, Jiewei Jiang, Kuan Chen, Qinxiang Zheng, Xiaotian Liu, Hongfei Weng, Shanjun Wu, Wei Chen
2021	J	`jnl`	Feasibility assessment of infectious keratitis depicted on slit-lamp and smartphone photographs using deep learning. Int. J. Medical Informatics Lei Wang, Kuan Chen, Han Wen, Qinxiang Zheng, Yang Chen, Jiantao Pu, Wei Chen
2020	—	`conf`	Nonrigid Registration of Multimodal Images Using Local Structural Descriptors. ICBIP Lei Wang, Shenghai Huang, Qian Chang, Qinxiang Zheng, Hao Chen

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.