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.
Augmented Reality Learning Experiences: Survey of Prototype Design and Evaluation
2014336 citationsTakafumi Taketomi, Goshiro Yamamoto 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 Jun Miyazaki'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 Jun Miyazaki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Miyazaki more than expected).
This network shows the impact of papers produced by Jun Miyazaki. 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 Jun Miyazaki. The network helps show where Jun Miyazaki may publish in the future.
Co-authorship network of co-authors of Jun Miyazaki
This figure shows the co-authorship network connecting the top 25 collaborators of Jun Miyazaki.
A scholar is included among the top collaborators of Jun Miyazaki 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 Jun Miyazaki. Jun Miyazaki is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Taketomi, Takafumi, et al.. (2013). Robust model-based tracking considering changes in the measurable DoF of the target object. Tokyo Tech Research Repository (Tokyo Institute of Technology).
10.
Keyaki, Atsushi, Jun Miyazaki, Kenji Hatano, et al.. (2013). XML Element Retrieval@1CLICK-2. NAIST Digital Library (Nara Institute of Science and Technology).2 indexed citations
11.
Fujisawa, Makoto, Jun Miyazaki, & Hirokazu Kato. (2011). Controlled Illumination for the Object Recognition with Projector Camera Feedback. 152–155.3 indexed citations
12.
Keyaki, Atsushi, Kenji Hatano, & Jun Miyazaki. (2010). A Query-oriented XML Fragment Search Approach on A Relational Database System. Journal of Digital Information Management. 8(3). 175–180.2 indexed citations
13.
Satoh, Kazuo, Makoto Fujisawa, Toshiyuki Amano, Jun Miyazaki, & Hirokazu Kato. (2010). A Method to Display Connelation Between Images by Using a Recursive Photomosaic System. 2010(14). 1–5.1 indexed citations
14.
Nakajima, Shinsuke, et al.. (2007). Investigation for Designing of Context-Aware Recommendation System Using SVM.. International MultiConference of Engineers and Computer Scientists. 970–975.3 indexed citations
15.
Nakajima, Shinsuke, et al.. (2007). Evaluation of Tag-Based Contextual Collaborative Filtering Effectiveness in Website Recommendation. Tokyo Tech Research Repository (Tokyo Institute of Technology). 107(131). 25–30.2 indexed citations
Miyazaki, Jun. (2002). Concurrency Control and Performance Evaluation of Parallel B-tree Structures. IEICE Transactions on Information and Systems. 85(8). 1269–1283.7 indexed citations
19.
Miyazaki, Jun, et al.. (1998). Advanced database systems for integration of media and user environments '98. WORLD SCIENTIFIC eBooks.1 indexed citations
20.
Miyazaki, Jun, et al.. (1997). Dynamical Associative Memory based on Synchronization in Chaotic Neural Network : Proposal for the Scenario via Spatio-Temporal Symmetry Recovering Bifurcation. Natural Computing. 96(511). 95–100.1 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.