Qiong Hu - RankMe

15 papers Journal 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Comprehensive Review of Agricultural Parcel and Boundary Delineation from Remote Sensing Images: Recent Progress and Future Perspectives. CoRR Juepeng Zheng, Zi Ye, Yibin Wen, Jianxi Huang, Zhiwei Zhang, Qingmei Li, Qiong Hu, Baodong Xu, Lingyuan Zhao, Haohuan Fu
2025	J	`jnl`	CT-HiffNet: A contour-texture hierarchical feature fusion network for cropland field parcel extraction from high-resolution remote sensing images. Comput. Electron. Agric. Hao Wu, Junyang Xie, Weihao Deng, Anqi Lin, Abdul Rashid Mohamed Shariff, Shamshodbek Akmalov, Wenbin Wu, Zhaoliang Li, Qiangyi Yu, Qunming Wang, Jian Zhang, Xin Mei, Qiong Hu
2024	J	`jnl`	Understanding the potentials of early-season crop type mapping by using Landsat-8, Sentinel-1/2, and GF-1/6 data. Comput. Electron. Agric. Cong Wang, Xinyu Zhang, Wenjing Wang, Haodong Wei, Jiayue Wang, Zexuan Li, Xiuni Li, Hao Wu, Qiong Hu
2022	J	`jnl`	An Adaptive Image Segmentation Method with Automatic Selection of Optimal Scale for Extracting Cropland Parcels in Smallholder Farming Systems. Remote. Sens. Zhiwen Cai, Qiong Hu, Xinyu Zhang, Jingya Yang, Haodong Wei, Zhen He, Qian Song, Cong Wang, Gaofei Yin, Baodong Xu
2022	J	`jnl`	Comparison of Vegetation Phenology Derived from Solar-Induced Chlorophyll Fluorescence and Enhanced Vegetation Index, and Their Relationship with Climatic Limitations. Remote. Sens. Cong Wang, Yijin Wu, Qiong Hu, Jie Hu, Yunping Chen, Shangrong Lin, Qiaoyun Xie
2022	J	`jnl`	Exploring the potential of Chinese GF-6 images for crop mapping in regions with complex agricultural landscapes. Int. J. Appl. Earth Obs. Geoinformation Tian Xia, Zhen He, Zhiwen Cai, Cong Wang, Wenjing Wang, Jiayue Wang, Qiong Hu, Qian Song
2022	J	`jnl`	Genetic Programming for High-Level Feature Learning in Crop Classification. Remote. Sens. Miao Lu, Ying Bi, Bing Xue, Qiong Hu, Mengjie Zhang, Yanbing Wei, Peng Yang, Wenbin Wu
2021	J	`jnl`	An Object- and Topology-Based Analysis (OTBA) Method for Mapping Rice-Crayfish Fields in South China. Remote. Sens. Haodong Wei, Qiong Hu, Zhiwen Cai, Jingya Yang, Qian Song, Gaofei Yin, Baodong Xu
2020	J	`jnl`	Evaluation of Global Decametric-Resolution LAI, FAPAR and FVC Estimates Derived from Sentinel-2 Imagery. Remote. Sens. Qiong Hu, Jingya Yang, Baodong Xu, Jianxi Huang, Muhammad Sohail Memon, Gaofei Yin, Yelu Zeng, Jing Zhao, Ke Liu
2019	J	`jnl`	A phenology-based spectral and temporal feature selection method for crop mapping from satellite time series. Int. J. Appl. Earth Obs. Geoinformation Qiong Hu, Damien Sulla-Menashe, Baodong Xu, He Yin, Huajun Tang, Peng Yang, Wenbin Wu
2018	J	`jnl`	Estimating Sub-Pixel Soybean Fraction from Time-Series MODIS Data Using an Optimized Geographically Weighted Regression Model. Remote. Sens. Qiong Hu, Yaxiong Ma, Baodong Xu, Qian Song, Huajun Tang, Wenbin Wu
2018	J	`jnl`	GlobeLand30 shows little cropland area loss but greater fragmentation in China. Int. J. Appl. Earth Obs. Geoinformation Qiangyi Yu, Qiong Hu, Jasper van Vliet, Peter H. Verburg, Wenbin Wu
2017	J	`jnl`	In-Season Crop Mapping with GF-1/WFV Data by Combining Object-Based Image Analysis and Random Forest. Remote. Sens. Qian Song, Qiong Hu, Qingbo Zhou, Ciara Hovis, Mingtao Xiang, Huajun Tang, Wenbin Wu
2016	J	`jnl`	Extending the Pairwise Separability Index for Multicrop Identification Using Time-Series MODIS Images. IEEE Trans. Geosci. Remote. Sens. Qiong Hu, Wenbin Wu, Qian Song, Qiangyi Yu, Miao Lu, Peng Yang, Huajun Tang, Yuqiao Long
2013	J	`jnl`	Exploring the Use of Google Earth Imagery and Object-Based Methods in Land Use/Cover Mapping. Remote. Sens. Qiong Hu, Wenbin Wu, Tian Xia, Qiangyi Yu, Peng Yang, Zhengguo Li, Qian Song

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.