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.
Deep Learning for Content-Based Image Retrieval
2014544 citationsJi Wan, D. Wang et al.Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University)profile →
Citations per year, relative to Ji Wan Ji Wan (= 1×)
peers
Ning Zhou
Countries citing papers authored by Ji Wan
Since
Specialization
Citations
This map shows the geographic impact of Ji Wan'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 Ji Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ji Wan more than expected).
This network shows the impact of papers produced by Ji Wan. 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 Ji Wan. The network helps show where Ji Wan may publish in the future.
Co-authorship network of co-authors of Ji Wan
This figure shows the co-authorship network connecting the top 25 collaborators of Ji Wan.
A scholar is included among the top collaborators of Ji Wan 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 Ji Wan. Ji Wan is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
8 of 8 papers shown
1.
Gao, Xingyu, Steven C. H. Hoi, Yongdong Zhang, et al.. (2017). Sparse Online Learning of Image Similarity. ACM Transactions on Intelligent Systems and Technology. 8(5). 1–22.23 indexed citations
Wan, Ji, Pengcheng Wu, Steven C. H. Hoi, et al.. (2015). Online learning to rank for content-based image retrieval. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 2284–2290.10 indexed citations
Wan, Ji, D. Wang, Steven C. H. Hoi, et al.. (2014). Deep Learning for Content-Based Image Retrieval. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 157–166.544 indexed citations breakdown →
7.
Wan, Ji, Sheng Tang, Yongdong Zhang, Lei Huang, & Jintao Li. (2013). Data driven multi-index hashing. 2670–2673.13 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.