Ichiro Ide

2.2k total citations
195 papers, 1.2k citations indexed

About

Ichiro Ide is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Ichiro Ide has authored 195 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 158 papers in Computer Vision and Pattern Recognition, 23 papers in Artificial Intelligence and 22 papers in Aerospace Engineering. Recurrent topics in Ichiro Ide's work include Advanced Image and Video Retrieval Techniques (45 papers), Video Analysis and Summarization (43 papers) and Video Surveillance and Tracking Methods (42 papers). Ichiro Ide is often cited by papers focused on Advanced Image and Video Retrieval Techniques (45 papers), Video Analysis and Summarization (43 papers) and Video Surveillance and Tracking Methods (42 papers). Ichiro Ide collaborates with scholars based in Japan, United States and Netherlands. Ichiro Ide's co-authors include Hiroshi Murase, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Yasutomo Kawanishi, Yukimasa Tamatsu, T. Takahashi, Shuichi Sakai, Hidehiko Tanaka and Shin’ichi Satoh and has published in prestigious journals such as Physical Review Letters, JAMA and IEEE Access.

In The Last Decade

Ichiro Ide

171 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ichiro Ide Japan 18 853 169 136 130 125 195 1.2k
Xinyu Huang United States 13 641 0.8× 131 0.8× 283 2.1× 184 1.4× 61 0.5× 36 991
Guangyou Xu China 21 1.1k 1.3× 161 1.0× 41 0.3× 108 0.8× 115 0.9× 116 1.4k
Jinshi Cui China 18 836 1.0× 349 2.1× 125 0.9× 221 1.7× 50 0.4× 63 1.2k
Tao Yang China 22 935 1.1× 203 1.2× 88 0.6× 445 3.4× 56 0.4× 114 1.5k
Raymond Ptucha United States 18 624 0.7× 333 2.0× 35 0.3× 92 0.7× 141 1.1× 76 1.1k
Hong Bao China 16 393 0.5× 226 1.3× 114 0.8× 82 0.6× 51 0.4× 147 1.0k
Ersin Yumer United States 17 1.4k 1.7× 156 0.9× 53 0.4× 116 0.9× 45 0.4× 30 1.9k
Masao Sakauchi Japan 17 1.1k 1.3× 255 1.5× 173 1.3× 65 0.5× 282 2.3× 130 1.4k
Mohana India 22 856 1.0× 463 2.7× 116 0.9× 66 0.5× 96 0.8× 94 1.6k
J. Woodfill United States 15 1.1k 1.3× 177 1.0× 46 0.3× 263 2.0× 135 1.1× 34 1.5k

Countries citing papers authored by Ichiro Ide

Since Specialization
Citations

This map shows the geographic impact of Ichiro Ide'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 Ichiro Ide with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ichiro Ide more than expected).

Fields of papers citing papers by Ichiro Ide

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ichiro Ide. 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 Ichiro Ide. The network helps show where Ichiro Ide may publish in the future.

Co-authorship network of co-authors of Ichiro Ide

This figure shows the co-authorship network connecting the top 25 collaborators of Ichiro Ide. A scholar is included among the top collaborators of Ichiro Ide 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 Ichiro Ide. Ichiro Ide 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.
Zhang, Bolin, et al.. (2024). Cross-modal recipe retrieval based on unified text encoder with fine-grained contrastive learning. Knowledge-Based Systems. 305. 112641–112641. 1 indexed citations
2.
Kawanishi, Yasutomo, et al.. (2024). Image-Collection Summarization Using Scene-Graph Generation With External Knowledge. IEEE Access. 12. 17499–17512.
3.
Kawanishi, Yasutomo, et al.. (2023). An Approach to Generate a Caption for an Image Collection Using Scene Graph Generation. IEEE Access. 11. 128245–128260. 3 indexed citations
4.
Deguchi, Daisuke, et al.. (2015). A study on the prediction of driver's pedestrian detectability considering characteristics of human fields-of-view while driving. IEICE Technical Report; IEICE Tech. Rep.. 114(521). 223–228. 3 indexed citations
5.
Kawanishi, Yasutomo, et al.. (2015). Pedestrian's Inattention Estimation based on Recognition of Texting While Walking from In-Vehicle Camera Images. IEICE Technical Report; IEICE Tech. Rep.. 115(98). 83–88. 2 indexed citations
6.
Zheng, Yinqiang, et al.. (2014). Nagoya University at TRECVID 2014: the Instance Search Task.. TRECVID.
7.
Ide, Ichiro, et al.. (2013). Segmentation of Human Instances Using Grab-cut and Active Shape Model Feedback. Machine Vision and Applications. 77–80. 2 indexed citations
8.
Noda, Masafumi, Tomokazu Takahashi, Daisuke Deguchi, et al.. (2011). Detection of Road Markings Recorded in In-Vehicle Camera Images by Using Position-Dependent Classifiers. IEEJ Transactions on Industry Applications. 131(4). 466–474. 2 indexed citations
9.
Deguchi, Daisuke, et al.. (2011). On-road Obstacle Detection by Comparing Present and Past In-vehicle Camera Images. Machine Vision and Applications. 357–360. 12 indexed citations
10.
Deguchi, Daisuke, et al.. (2011). Quantification of the Visibility of Pedestrians Based on Integration of Local and Global Features. 110(381). 253–258. 1 indexed citations
11.
Deguchi, Daisuke, et al.. (2010). Improvement of Automatic Calibration of an In-vehicle Gaze Tracking System Using Positional Relation between Gaze Targets. IEICE Technical Report; IEICE Tech. Rep.. 109(470). 199–204. 1 indexed citations
12.
Noda, Masafumi, et al.. (2010). Study on the Creation of a Scenery Category Map using Geo-tagged Photographic Images. IEICE Technical Report; IEICE Tech. Rep.. 110(238). 79–84.
13.
Takahashi, Tomokazu, et al.. (2009). Extraction of difficult expressions for cooking beginners in cooking recipes. IEICE Technical Report; IEICE Tech. Rep.. 109(281). 37–40. 1 indexed citations
14.
Noda, Masafumi, Tomokazu Takahashi, Ichiro Ide, et al.. (2009). Recognition of Road Markings from In-Vehicle Camera Images by a Generative Learning Method. Machine Vision and Applications. 514–517. 14 indexed citations
15.
Noda, Masafumi, Tomokazu Takahashi, Ichiro Ide, Yoshito Mekada, & Hiroshi Murase. (2008). Recognition of Road Markings from In-Vehicle Camera Images using Generative Learning Method. IEICE Technical Report; IEICE Tech. Rep.. 108(263). 31–36. 1 indexed citations
16.
Deguchi, Daisuke, et al.. (2008). Cascaded Traffic Sign Detector Using Generative Learning Considering Color Variance. IEICE Technical Report; IEICE Tech. Rep.. 108(363). 135–140. 2 indexed citations
17.
Takahashi, Tomokazu, et al.. (2008). Frame Registration between In-vehicle Omni-directional and Normal Cameras for Self-position Estimation. IEICE Technical Report; IEICE Tech. Rep.. 107(539). 167–172. 1 indexed citations
18.
Takahashi, Tomokazu, et al.. (2007). Accurate Vehicle Localization and Traveling Lane Classification by Aligning Laser Scanner Data Sequences. IEICE technical report. Speech. 107(206). 17–22. 1 indexed citations
19.
Takahashi, Tomokazu, et al.. (2006). Recognition of Very Low-Resolution Characters from Motion Images Taken by Portable Digital Cameras. 89(2). 323–331. 1 indexed citations
20.
Ide, Ichiro, et al.. (1998). Automatic Video Indexing Based on Shot Classification. 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.

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