Liangxiu Han

4.0k total citations · 2 hit papers
105 papers, 2.6k citations indexed

About

Liangxiu Han is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Liangxiu Han has authored 105 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Networks and Communications, 18 papers in Computer Vision and Pattern Recognition and 17 papers in Information Systems. Recurrent topics in Liangxiu Han's work include Distributed and Parallel Computing Systems (15 papers), Remote Sensing in Agriculture (10 papers) and Cloud Computing and Resource Management (10 papers). Liangxiu Han is often cited by papers focused on Distributed and Parallel Computing Systems (15 papers), Remote Sensing in Agriculture (10 papers) and Cloud Computing and Resource Management (10 papers). Liangxiu Han collaborates with scholars based in United Kingdom, China and United States. Liangxiu Han's co-authors include Xin Zhang, Donald C. Rundquist, Jano van Hemert, Lianghao Han, Muhammad Salman Haleem, Daoqiang Zhang, Liang Sun, Wenyong Zhu, Yue Shi and Baihua Li and has published in prestigious journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Liangxiu Han

98 papers receiving 2.5k citations

Hit Papers

A Deep Learning-Based Approach for Automated Yellow Rust ... 2019 2026 2021 2023 2019 2021 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Deep Learning-Based Approach for Automated Yellow Rust Disease Detection from High-Resolution Hyperspectral UAV Images
    2019 244 citations Xin Zhang, Liangxiu Han et al. Remote Sensing profile →
  2. Dual Attention Multi-Instance Deep Learning for Alzheimer’s Disease Diagnosis With Structural MRI
    2021 165 citations Wenyong Zhu, Liang Sun et al. profile →

Peers

Liangxiu Han
Xiaohui Yuan United States
Uzair Aslam Bhatti China
Guoqiang Zhong China
Mohd Anul Haq Saudi Arabia
Weiwei Cai China
Jamil Ahmad Pakistan
Krishna Kant Singh India
Jair Cervantes Mexico
Imran Ahmed Pakistan
Weikuan Jia China
Xiaohui Yuan United States
Liangxiu Han
Citations per year, relative to Liangxiu Han Liangxiu Han (= 1×) peers Xiaohui Yuan

Countries citing papers authored by Liangxiu Han

Since Specialization
Citations

This map shows the geographic impact of Liangxiu Han's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Liangxiu Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liangxiu Han more than expected).

Fields of papers citing papers by Liangxiu Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Liangxiu Han. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Liangxiu Han. The network helps show where Liangxiu Han may publish in the future.

Co-authorship network of co-authors of Liangxiu Han

This figure shows the co-authorship network connecting the top 25 collaborators of Liangxiu Han. A scholar is included among the top collaborators of Liangxiu Han based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Liangxiu Han. Liangxiu Han is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Zhang, Xin, Liangxiu Han, Lianghao Han, et al.. (2023). sMRI-PatchNet: A Novel Efficient Explainable Patch-Based Deep Learning Network for Alzheimer’s Disease Diagnosis With Structural MRI. IEEE Access. 11. 108603–108616. 10 indexed citations
3.
4.
Dai, Min, Lixing Wang, Shanwen Zhang, et al.. (2023). Pepper leaf disease recognition based on enhanced lightweight convolutional neural networks. Frontiers in Plant Science. 14. 1230886–1230886. 22 indexed citations
5.
Han, Liangxiu, et al.. (2022). A Hybrid Parallelization Approach for Distributed and Scalable Deep Learning. IEEE Access. 10. 77950–77961. 6 indexed citations
6.
Zhang, Xin, Liangxiu Han, Lianghao Han, et al.. (2022). CXR-Net: A Multitask Deep Learning Network for Explainable and Accurate Diagnosis of COVID-19 Pneumonia From Chest X-Ray Images. IEEE Journal of Biomedical and Health Informatics. 27(2). 980–991. 21 indexed citations
7.
Zhang, Xin, Liangxiu Han, Wenyong Zhu, Liang Sun, & Daoqiang Zhang. (2021). An Explainable 3D Residual Self-Attention Deep Neural Network for Joint Atrophy Localization and Alzheimer’s Disease Diagnosis Using Structural MRI. IEEE Journal of Biomedical and Health Informatics. 26(11). 5289–5297. 133 indexed citations
8.
Zhang, Xin, et al.. (2021). A Gans-Based Deep Learning Framework for Automatic Subsurface Object Recognition From Ground Penetrating Radar Data. IEEE Access. 9. 39009–39018. 37 indexed citations
9.
Yap, Moi Hoon, et al.. (2021). Computational modelling unveils how epiblast remodelling and positioning rely on trophectoderm morphogenesis during mouse implantation. PLoS ONE. 16(7). e0254763–e0254763. 8 indexed citations
10.
Han, Liangxiu, et al.. (2021). Performance Analysis of Distributed Deep Learning Frameworks in a Multi-GPU Environment. 406–413. 5 indexed citations
11.
Ma, Huiqin, Wenjiang Huang, Yuanshu Jing, et al.. (2019). Integrating Growth and Environmental Parameters to Discriminate Powdery Mildew and Aphid of Winter Wheat Using Bi-Temporal Landsat-8 Imagery. Remote Sensing. 11(7). 846–846. 43 indexed citations
12.
Zhang, Xin, Liangxiu Han, Yingying Dong, et al.. (2019). A Deep Learning-Based Approach for Automated Yellow Rust Disease Detection from High-Resolution Hyperspectral UAV Images. Remote Sensing. 11(13). 1554–1554. 244 indexed citations breakdown →
13.
Li, Siguang, Zhengwen Huang, Liangxiu Han, & Changjun Jiang. (2018). A genetic algorithm enhanced automatic data flow management solution for facilitating data intensive applications in the cloud. Concurrency and Computation Practice and Experience. 30(23). 6 indexed citations
14.
Wang‎, Shuihua, Khan Muhammad, Yiding Lv, et al.. (2018). Identification of Alcoholism Based on Wavelet Renyi Entropy and Three‐Segment Encoded Jaya Algorithm. Complexity. 2018(1). 43 indexed citations
15.
Han, Liangxiu, et al.. (2018). A Unified Framework for Opinion Dynamics. Adaptive Agents and Multi-Agents Systems. 1079–1086. 6 indexed citations
16.
Han, Liangxiu, et al.. (2015). DIVINE: Building a Wearable Device for Intelligent Control of Environment Using Google Glass. 1280–1285. 1 indexed citations
17.
Han, Liangxiu, et al.. (2013). Building a Virtual Constructivist Learning Environment for Learning Computing Security and Forensics. 12(1). 49–61. 2 indexed citations
18.
Gao, Chuanshan, et al.. (2001). A New Multifractal Traffic Model Based on the Wavelet Transform.. 157–162. 2 indexed citations
19.
Zhao, Jizong, et al.. (1999). [In situ localization of mRNA gelatinases in cerebral aneurysms].. PubMed. 79(11). 822–4. 2 indexed citations
20.
Han, Liangxiu & Donald C. Rundquist. (1994). The response of both surface reflectance and the underwater light field to various levels of suspended sediments: preliminary results. Photogrammetric Engineering & Remote Sensing. 60(12). 1463–1471. 54 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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