Yange Sun - RankMe

22 papers Journal 20Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LTPNet: Lesion-Aware Triple-Path Feature Fusion Network for Skin Lesion Segmentation. J. Imaging Yange Sun, Sen Chen, Huaping Guo, Li Zhang, Hongzhou Yue, Yan Feng
2026	J	`jnl`	S3Det: Strip steel surface defect detector via enhanced deformable convolution and dual cross-layer pyramid. Pattern Recognit. Lett. Yange Sun, Chenglong Xu, Huaping Guo, Yongqiang Tang, Wensheng Zhang
2025	J	`jnl`	DEPANet: A Differentiable Edge-Guided Pyramid Aggregation Network for Strip Steel Surface Defect Segmentation. Algorithms Yange Sun, Siyu Geng, Chengyi Zheng, Chenglong Xu, Huaping Guo, Yan Feng
2025	J	`jnl`	Multiscale Feature Fusion for Salient Object Detection of Strip Steel Surface Defects. IEEE Access Li Zhang, Xirui Li, Yange Sun, Yan Feng, Huaping Guo
2025	J	`jnl`	TDDet: A novel lightweight and efficient tea disease detector. Comput. Electron. Agric. Yange Sun, Zhihao Li, Huaping Guo, Yan Feng, Yongqiang Tang, Wensheng Zhang, Jingqiu Gu
2024	J	`jnl`	Dual convolutional neural network for crowd counting. Multim. Tools Appl. Huaping Guo, Rui Wang, Li Zhang, Yange Sun
2022	J	`jnl`	Ensemble based on accuracy and diversity weighting for evolving data streams. Int. Arab J. Inf. Technol. Yange Sun, Han Shao, Bencai Zhang
2022	J	`jnl`	Stability-Constraint-Free Solutions to Solve Time-Varying Linear Equation System. IEEE Access Jian Li, Jianwei Fan, Xinhui Zhu, Yange Sun, Yanling Li
2021	J	`jnl`	Constructing accuracy and diversity ensemble using Pareto-based multi-objective learning for evolving data streams. Neural Comput. Appl. Yange Sun, Honghua Dai
2021	J	`jnl`	Cost-Sensitive Classification for Evolving Data Streams with Concept Drift and Class Imbalance. Comput. Intell. Neurosci. Yange Sun, Meng Li, Lei Li, Han Shao, Yi Sun
2020	J	`jnl`	Stacking model of multi-label classification based on pruning strategies. Neural Comput. Appl. Haiyang Liu, Zhihai Wang, Yange Sun
2020	J	`jnl`	Two-Stage Cost-Sensitive Learning for Data Streams With Concept Drift and Class Imbalance. IEEE Access Yange Sun, Yi Sun, Honghua Dai
2019	J	`jnl`	Efficient Ensemble Classification for Multi-Label Data Streams with Concept Drift. Inf. Yange Sun, Han Shao, Shasha Wang
2019	—	`conf`	Semi-Random Forest Based on Representative Patterns for Noisy and Non-Stationary Data Stream. DSC Bencai Zhang, Hua-Rui Wu, Yange Sun, Ronghua Gao
2019	J	`jnl`	Tracking recurring concepts from evolving data streams using ensemble method. Int. Arab J. Inf. Technol. Yange Sun, Zhihai Wang, Jidong Yuan, Wei Zhang
2018	J	`jnl`	A Classifier Graph Based Recurring Concept Detection and Prediction Approach. Comput. Intell. Neurosci. Yange Sun, Zhihai Wang, Yang Bai, Honghua Dai, Saeid Nahavandi
2018	J	`jnl`	An effective pattern-based Bayesian classifier for evolving data stream. Neurocomputing Jidong Yuan, Zhihai Wang, Yange Sun, Wei Zhang, Jingjing Jiang
2018	J	`jnl`	一种基于树型贝叶斯网络的集成多标记分类算法 (Ensemble Multi-label Classification Algorithm Based on Tree-Bayesian Network). 计算机科学 Zhidong Zhang, Zhihai Wang, Haiyang Liu, Yange Sun
2017	—	`conf`	A Pattern-Based Bayesian Classifier for Data Stream. ICONIP (4) Jidong Yuan, Zhihai Wang, Yange Sun, Wei Zhang, Jingjing Jiang
2017	J	`jnl`	基于时间的局部低秩张量分解的协同过滤推荐算法 (Time-based Local Collaborative Filtering Recommendation Algorithm on Tensor Factorization). 计算机科学 Yange Sun, Zhihai Wang, Dan Huang
2016	J	`jnl`	Online Ensemble Using Adaptive Windowing for Data Streams with Concept Drift. Int. J. Distributed Sens. Networks Yange Sun, Zhihai Wang, Haiyang Liu, Chao Du, Jidong Yuan
2015	J	`jnl`	A lazy associative classifier for time series. Intell. Data Anal. Jidong Yuan, Zhihai Wang, Meng Han, Yange Sun

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.