Hideki Nakayama
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Neurology top 10%
- Biomedical Engineering
- Co-authors
- Changhee HanLeonardo RundoYujiro FurukawaYasuo KuniyoshiTatsuya HaradaRyosuke ArakiGiancarlo MauriHideaki Hayashi
- Topics
- Multimodal Machine Learning Applications (24 papers)Advanced Image and Video Retrieval Techniques (22 papers)Topic Modeling (17 papers)
- Journals
- IEEE AccessSLEEPBMC Bioinformatics
- Partner nations
- JapanUnited KingdomUnited States
In The Last Decade
Hideki Nakayama
71 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 109
- Computer Vision and Pattern Recognition 702
- Artificial Intelligence 650
- Radiology, Nuclear Medicine and Imaging 234
- Neurology 113
- Biomedical Engineering 65
Countries citing papers authored by Hideki Nakayama
This map shows the geographic impact of Hideki Nakayama'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 Hideki Nakayama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hideki Nakayama more than expected).
Fields of papers citing papers by Hideki Nakayama
This network shows the impact of papers produced by Hideki Nakayama. 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 Hideki Nakayama. The network helps show where Hideki Nakayama may publish in the future.
Co-authorship network of co-authors of Hideki Nakayama
This figure shows the co-authorship network connecting the top 25 collaborators of Hideki Nakayama. A scholar is included among the top collaborators of Hideki Nakayama 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 Hideki Nakayama. Hideki Nakayama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | A Visually-Grounded Parallel Corpus with Phrase-to-Region Linking. | 11 |
| 7 | 13 | |
| 8 | Incorporating Semantic Attention in Video Description Generation | 1 |
| 9 | Prostate Zonal Segmentation Using Deep Learning | 2 |
| 10 | Augmenting Image Question Answering Dataset by Exploiting Image Captions | 1 |
| 11 | 195 | |
| 12 | Word Ordering as Unsupervised Learning Towards Syntactically Plausible Word Representations | 1 |
| 13 | Generating Video Description using Sequence-to-sequence Model with Temporal Attention | 13 |
| 14 | Image feature extraction and transfer learning using deep convolutional neural networks | 6 |
| 15 | 25 | |
| 16 | NLab-UTokyo at ImageCLEF 2013 Plant Identification Task. | 1 |
| 17 | Scene Classification using Generalized Local Correlation | 6 |
| 18 | 1 | |
| 19 | Additional Learning and Forgetting by RBF Networks and its Applications to Design of Support Structures in Tunnel Construction. | 4 |
| 20 | Incremental Learning for Pattern Classification. | 2 |
About Hideki Nakayama
Hideki Nakayama is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 78 papers that have together received 1.2k indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (24 papers), Advanced Image and Video Retrieval Techniques (22 papers) and Topic Modeling (17 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (702 citations), Artificial Intelligence (650 citations) and Health Informatics (25 citations). Hideki Nakayama has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Changhee Han, Leonardo Rundo, Yujiro Furukawa, Yasuo Kuniyoshi, Tatsuya Harada, Ryosuke Araki, Giancarlo Mauri, Hideaki Hayashi, Wataru Shimoda and Kohei Murao. Their work appears in journals such as IEEE Access, SLEEP and BMC Bioinformatics.
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.