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Fingerprint Dive into the research topics where Hideaki Hayashi is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Neural networks Engineering & Materials Science
Electromyography Medicine & Life Sciences
Magnetic resonance Engineering & Materials Science
Time series Engineering & Materials Science
Tumors Engineering & Materials Science
Brain Engineering & Materials Science
Experiments Engineering & Materials Science
Music Therapy Medicine & Life Sciences

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Research Output 2013 2020

  • 51 Citations
  • 4 h-Index
  • 14 Article
  • 13 Conference contribution
  • 2 Chapter
4 Citations (Scopus)

Infinite Brain MR Images: PGGAN-Based Data Augmentation for Tumor Detection

Han, C., Rundo, L., Araki, R., Furukawa, Y., Mauri, G., Nakayama, H. & Hayashi, H., Jan 1 2020, Smart Innovation, Systems and Technologies. Springer Science and Business Media Deutschland GmbH, p. 291-303 13 p. (Smart Innovation, Systems and Technologies; vol. 151).

Research output: Chapter in Book/Report/Conference proceedingChapter

Magnetic resonance
Tumors
Brain
Medical imaging
Neural networks

A Trainable Multiplication Layer for Auto-correlation and Co-occurrence Extraction

Hayashi, H. & Uchida, S., Jan 1 2019, Computer Vision - ACCV 2018 - 14th Asian Conference on Computer Vision, Revised Selected Papers. Jawahar, C. V., Li, H., Schindler, K. & Mori, G. (eds.). Springer Verlag, p. 414-430 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11362 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Autocorrelation
Multiplication
Neural networks
Backpropagation
Pixels

Biosignal Generation and Latent Variable Analysis with Recurrent Generative Adversarial Networks

Harada, S., Hayashi, H. & Uchida, S., Jan 1 2019, In : IEEE Access. 7, p. 144292-144302 11 p., 8794813.

Research output: Contribution to journalArticle

Open Access
Labels
Time series
Deep learning
1 Citation (Scopus)

Combining noise-to-image and image-to-image GANs: Brain MR image augmentation for tumor detection

Han, C., Rundo, L., Araki, R., Nagano, Y., Furukawa, Y., Mauri, G., Nakayama, H. & Hayashi, H., Jan 1 2019, In : IEEE Access. 7, p. 156966-156977 12 p., 8869751.

Research output: Contribution to journalArticle

Open Access
Magnetic resonance
Tumors
Brain
Medical imaging
Neural networks

Efficient Soft-Constrained Clustering for Group-Based Labeling

Bise, R., Abe, K., Hayashi, H., Tanaka, K. & Uchida, S., Jan 1 2019, Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings. Shen, D., Yap, P-T., Liu, T., Peters, T. M., Khan, A., Staib, L. H., Essert, C. & Zhou, S. (eds.). Springer, p. 421-430 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11768 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Labeling
Clustering
Endoscopy
Medical Image
Clustering Methods