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.
Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration
2015750 citationsJiaolong Yang, Hongdong Li et al.profile →
Accurate 3D Face Reconstruction With Weakly-Supervised Learning: From Single Image to Image Set
2019432 citationsJiaolong Yang, Yunde Jia et al.profile →
Go-ICP: Solving 3D Registration Efficiently and Globally Optimally
2013343 citationsJiaolong Yang, Hongdong Li et al.ANU Open Research (Australian National University)profile →
Vehicle Type Classification Using a Semisupervised Convolutional Neural Network
2015289 citationsYuwei Wu, Mingtao Pei et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Yunde Jia'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 Yunde Jia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yunde Jia more than expected).
This network shows the impact of papers produced by Yunde Jia. 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 Yunde Jia. The network helps show where Yunde Jia may publish in the future.
Co-authorship network of co-authors of Yunde Jia
This figure shows the co-authorship network connecting the top 25 collaborators of Yunde Jia.
A scholar is included among the top collaborators of Yunde Jia 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 Yunde Jia. Yunde Jia is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Chi, Pan, et al.. (2021). Effect of Low Complement C4 on Clinical Characteristics of Patients with First-Episode Neuromyelitis Optica Spectrum Disorder. SHILAP Revista de lepidopterología.1 indexed citations
Yang, Jiaolong, Hongdong Li, & Yunde Jia. (2013). Go-ICP: Solving 3D Registration Efficiently and Globally Optimally. ANU Open Research (Australian National University). 1457–1464.343 indexed citations breakdown →
Liu, Xiabi, Yunde Jia, & Ming Tan. (2006). Geometrical-Statistical Modeling of Character Structures for Natural Stroke Extraction and Matching. INRIA a CCSD electronic archive server.5 indexed citations
18.
Jia, Yunde. (2006). Linear Self-Calibration Technique Based on Active Vision. Transactions of Beijing Institute of Technology.1 indexed citations
Jia, Yunde. (2003). New E-Commerce Model Based on Multi-Agent Automated Negotiation. 北京理工大学学报(英文版).
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.