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Yasuhiko Igarashi

Showing results (1-10 of 17) with videos related to

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Microscopy (Oxford, England)|October 24, 2025
Domain-Specific Simulated Data Enhances Knife-Mark Noise Suppression in Microscopy Images of MaterialsMasato Suzuki, Yasuhiko Igarashi
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|March 10, 2012
Theory of correlation in a network with synaptic depressionYasuhiko Igarashi, Masafumi Oizumi, Masato Okada
Chemical Communications (Cambridge, England)|May 20, 2021
Yield-prediction models for efficient exfoliation of soft layered materials into nanosheetsKyohei Noda, Yasuhiko Igarashi, Hiroaki Imai, et al.
Nanoscale|February 10, 2021
Lateral-size control of exfoliated transition-metal-oxide 2D materials by machine learning on small dataRyosuke Mizuguchi, Yasuhiko Igarashi, Hiroaki Imai, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 7, 2016
Estimation of the reaction times in tasks of varying difficulty from the phase coherence of the auditory steady-state response using the least absolute shrinkage and selection operator analysisYusuke Yokota, Yasuhiko Igarashi, Masato Okada, et al.
Physical Chemistry Chemical Physics : PCCP|June 15, 2018
Liquid electrolyte informatics using an exhaustive search with linear regressionKeitaro Sodeyama, Yasuhiko Igarashi, Tomofumi Nakayama, et al.
Nanoscale|December 16, 2025
Prediction of the phase transition temperatures of functional nanostructured liquid crystals: a machine learning method based on small data for the design of self-assembled materialsShingo Takegawa, Haruka Tobita, Yasuhiko Igarashi, et al.
Frontiers in Computational Neuroscience|July 31, 2013
Recurrent network for multisensory integration-identification of common sources of audiovisual stimuliItsuki Yamashita, Kentaro Katahira, Yasuhiko Igarashi, et al.
Nanoscale Advances|June 23, 2025
Data-scientific validation of prediction models for the controlled syntheses of exfoliated nanosheetsYuka Kitamura, Yuki Namiuchi, Hiroaki Imai, et al.
Discover Nano|July 3, 2025
Sparse coding-based multiframe superresolution for efficient synchrotron radiation microspectroscopyYasuhiko Igarashi, Naoka Nagamura, Masahiro Sekine, et al.
Pageof 2

Showing results (1-10 of 17) with videos related to

Sort By:
Pageof 2
Microscopy (Oxford, England)|October 24, 2025
Domain-Specific Simulated Data Enhances Knife-Mark Noise Suppression in Microscopy Images of MaterialsMasato Suzuki, Yasuhiko Igarashi
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|March 10, 2012
Theory of correlation in a network with synaptic depressionYasuhiko Igarashi, Masafumi Oizumi, Masato Okada
Chemical Communications (Cambridge, England)|May 20, 2021
Yield-prediction models for efficient exfoliation of soft layered materials into nanosheetsKyohei Noda, Yasuhiko Igarashi, Hiroaki Imai, et al.
Nanoscale|February 10, 2021
Lateral-size control of exfoliated transition-metal-oxide 2D materials by machine learning on small dataRyosuke Mizuguchi, Yasuhiko Igarashi, Hiroaki Imai, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 7, 2016
Estimation of the reaction times in tasks of varying difficulty from the phase coherence of the auditory steady-state response using the least absolute shrinkage and selection operator analysisYusuke Yokota, Yasuhiko Igarashi, Masato Okada, et al.
Physical Chemistry Chemical Physics : PCCP|June 15, 2018
Liquid electrolyte informatics using an exhaustive search with linear regressionKeitaro Sodeyama, Yasuhiko Igarashi, Tomofumi Nakayama, et al.
Nanoscale|December 16, 2025
Prediction of the phase transition temperatures of functional nanostructured liquid crystals: a machine learning method based on small data for the design of self-assembled materialsShingo Takegawa, Haruka Tobita, Yasuhiko Igarashi, et al.
Frontiers in Computational Neuroscience|July 31, 2013
Recurrent network for multisensory integration-identification of common sources of audiovisual stimuliItsuki Yamashita, Kentaro Katahira, Yasuhiko Igarashi, et al.
Nanoscale Advances|June 23, 2025
Data-scientific validation of prediction models for the controlled syntheses of exfoliated nanosheetsYuka Kitamura, Yuki Namiuchi, Hiroaki Imai, et al.
Discover Nano|July 3, 2025
Sparse coding-based multiframe superresolution for efficient synchrotron radiation microspectroscopyYasuhiko Igarashi, Naoka Nagamura, Masahiro Sekine, et al.
Pageof 2