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.
Capsule-forensics: Using Capsule Networks to Detect Forged Images and Videos
2019495 citationsHuy H. Nguyen, Junichi Yamagishi et al.Edinburgh Research Explorerprofile →
Multi-task Learning for Detecting and Segmenting Manipulated Facial Images and Videos
2019325 citationsHuy H. Nguyen, Fuming Fang et al.Edinburgh Research Explorerprofile →
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 Isao Echizen'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 Isao Echizen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Isao Echizen more than expected).
This network shows the impact of papers produced by Isao Echizen. 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 Isao Echizen. The network helps show where Isao Echizen may publish in the future.
Co-authorship network of co-authors of Isao Echizen
This figure shows the co-authorship network connecting the top 25 collaborators of Isao Echizen.
A scholar is included among the top collaborators of Isao Echizen 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 Isao Echizen. Isao Echizen is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Yamada, Ikuya, et al.. (2022). EASE: Entity-Aware Contrastive Learning of Sentence Embedding. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 3870–3885.14 indexed citations
Echizen, Isao, et al.. (2020). A QR Symbol with ECDSA for Both Public and Secret Areas using Rhombic Sub-cells. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. 1392–1399.2 indexed citations
6.
Kuribayashi, Minoru, et al.. (2020). Detection of Adversarial Examples Based on Sensitivities to Noise Removal Filter. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. 1386–1391.4 indexed citations
7.
Nguyen, Huy H., Junichi Yamagishi, & Isao Echizen. (2019). Capsule-forensics: Using Capsule Networks to Detect Forged Images and Videos. Edinburgh Research Explorer. 2307–2311.495 indexed citations breakdown →
8.
Nguyen, Huy H., Fuming Fang, Junichi Yamagishi, & Isao Echizen. (2019). Multi-task Learning for Detecting and Segmenting Manipulated Facial Images and Videos. Edinburgh Research Explorer. 1–8.325 indexed citations breakdown →
9.
Miyao, Yusuke, et al.. (2015). Paraphrase Detection Based on Identical Phrase and Similar Word Matching. Waseda University Repository (Waseda University). 504–512.2 indexed citations
10.
Shimada, Shigeru, et al.. (2013). Access Control by Detecting Privacy Leaks on Digital Private Documents. 113(211). 31–36.1 indexed citations
11.
Iwamura, Keiichi, et al.. (2012). Evaluation of information extraction from Artificial Fiber Pattern using a camera. IEICE Technical Report; IEICE Tech. Rep.. 112(293). 111–116.
12.
Thị, Phạm, et al.. (2011). An Experimental Evaluation for a New Column - Level Access Control Mechanism for Electronic Health Record Systems. International Journal of u- and e- Service Science and Technology. 4(4). 1–14.2 indexed citations
13.
Echizen, Isao, et al.. (2011). On Privacy-compliant Disclosure of Personal Data to Third Parties using Digital Watermarking. 2(3). 270–281.4 indexed citations
14.
Abe, Yoshihiko, et al.. (2010). Capacity Adaptive Synchronized Acoustic Steganography Scheme. J. Inf. Hiding Multim. Signal Process.. 1. 72–90.7 indexed citations
15.
Echizen, Isao, et al.. (2008). Robust Video Watermarking Based on Dual-Plane Correlation for Immunity to Rotation, Scale, Translation, and Random Distortion. Journal of Digital Information Management. 6(2). 161–167.1 indexed citations
16.
Echizen, Isao, et al.. (2006). Use of Statistically Adaptive Accumulation to Improve Video Watermark Detection (特集:ユビキタス社会を支えるコンピュータセキュリティ技術). 47(8). 2440–2453.1 indexed citations
Echizen, Isao, et al.. (2004). Color Picture Watermarking Correlating Two Constituent Planes for Immunity to Random Geometric Distortion. IEICE Transactions on Information and Systems. 87(9). 2239–2252.7 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.