Suguru Kanoga

发表

Deep Neural Networks for Grid-Based Elusive Crime Prediction Using a Private Dataset Obtained from Japanese Municipalities

Suguru Kanoga, Naruki Kawai, Kota Takaoka, 2020 .

Semi-simulation Experiments for Quantifying the Performance of SSVEP-based BCI after Reducing Artifacts from Trapezius Muscles

Mitsunori Tada, Masaki Nakanishi, Suguru Kanoga, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Motor Imagery Classification of Finger Motions Using Multiclass CSP

Suguru Kanoga, Masaki Kato, Takayuki Hoshino, 2020, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Construction of predictive models for bicycle riding comfort evaluation using electromyogram and electroencephalogram

Yasue Mitsukura, Suguru Kanoga, Noriki Toyoshima, 2016, 2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA).

Erratum: Robustness analysis of decoding SSVEPs in humans with head movements using a moving visual flicker (2019 J. Neural Eng. 17 016009)

Mitsunori Tada, Masaki Nakanishi, Suguru Kanoga, 2020 .

Proposed blink artifacts rejection method mixing with electroencephalographic recordings using single-channel electroencephalographic recordings and non-negative matrix factorization

Yasue Mitsukura, Suguru Kanoga, 2014, 2014 IEEE 13th International Workshop on Advanced Motion Control (AMC).

Analysis of Prefrontal Single-Channel EEG Data for Portable Auditory ERP-Based Brain–Computer Interfaces

Suguru Kanoga, Yasue Mitsukura, Mikito Ogino, 2019, Front. Hum. Neurosci..

A COMPARATIVE STUDY OF FEATURES AND CLASSIFIERS IN SINGLE-CHANNEL EEG-BASED MOTOR IMAGERY BCI

Suguru Kanoga, Hideki Asoh, Atsunori Kanemura, 2018, 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

Transfer Learning Over Time and Position in Wearable Myoelectric Control Systems

Suguru Kanoga, Atsunori Kanemura, Masashi Matsuokal, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Review of Artifact Rejection Methods for Electroencephalographic Systems

Yasue Mitsukura, Suguru Kanoga, Suguru Kanoga, 2017 .

Corrigendum to "Multi-scale dictionary learning for ocular artifact reduction from single-channel electroencephalograms" [Neurocomputing 347 (2019) 240-250]

Suguru Kanoga, Hideki Asoh, Atsunori Kanemura, 2019, Neurocomputing.

Robustness analysis of decoding SSVEPs in humans with head movements using a moving visual flicker

Mitsunori Tada, Masaki Nakanishi, Suguru Kanoga, 2019, Journal of neural engineering.

A study of pattern recognition in children using single-channel electroencephalogram for specialized electroencephalographic devices

Yasue Mitsukura, Suguru Kanoga, 2016 .

A No-Reference Metric of Cerebral Blood Flow Extraction for fNIRS Data

Takeshi Ogawa, Suguru Kanoga, Takayuki Hoshino, 2018, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Independent Low-Rank Matrix Analysis-Based Automatic Artifact Reduction Technique Applied to Three BCI Paradigms

Takayuki Hoshino, Suguru Kanoga, Hideki Asoh, 2020, Frontiers in Human Neuroscience.

Are armband sEMG devices dense enough for long-term use? - Sensor placement shifts cause significant reduction in recognition accuracy

Suguru Kanoga, Hideki Asoh, Atsunori Kanemura, 2020, Biomed. Signal Process. Control..

A study of pattern recognition in children using single-channel electroencephalogram for specialized electroencephalographic devices

Yasue Mitsukura, Suguru Kanoga, Y. Mitsukura, 2017 .

Eye blink artifact rejection in single-channel electroencephalographic signals by complete ensemble empirical mode decomposition and independent component analysis

Yasue Mitsukura, Suguru Kanoga, Y. Mitsukura, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Proposing an eye blink artifact rejection technique from single-channel EEG signal using positive semi-definite tensor factorization

Yasue Mitsukura, Suguru Kanoga, 2015 .

Construction of the interest prediction models for nursery school child using a single-channel electroencephalograph

Yasue Mitsukura, Suguru Kanoga, Y. Mitsukura, 2013, 2013 IEEE Conference on Systems, Process & Control (ICSPC).

Subject Transfer Framework Based on Source Selection and Semi-Supervised Style Transfer Mapping for Semg Pattern Recognition

Takayuki Hoshino, Suguru Kanoga, Hideki Asoh, 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Assessing the effects of voluntary and involuntary eyeblinks in independent components of electroencephalogram

Masaki Nakanishi, Yasue Mitsukura, Suguru Kanoga, 2016, Neurocomputing.

Analysis and Usage: Subject-to-subject Linear Domain Adaptation in sEMG Classification

Suguru Kanoga, Takayuki Hoshino, Atsushi Aoyama, 2020, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Eye-Blink Artifact Reduction Using 2-Step Nonnegative Matrix Factorization for Single-Channel Electroencephalographic Signals

Yasue Mitsukura, Suguru Kanoga, Suguru Kanoga, 2014 .

Assessing the effect of transfer learning on myoelectric control systems with three electrode positions

Suguru Kanoga, Atsunori Kanemura, A. Kanemura, 2018, 2018 IEEE International Conference on Industrial Technology (ICIT).

ICA-based positive semidefinite matrix templates for eye-blink artifact removal from EEG signal with single-electrode

Yasue Mitsukura, Suguru Kanoga, Y. Mitsukura, 2015, 2015 10th Asian Control Conference (ASCC).

Exploring optimal myoelectric feature indices for forearm control strategy using robust principal component analysis

Mitsunori Tada, Suguru Kanoga, Akihiko Murai, 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Multi-scale dictionary learning for ocular artifact reduction from single-channel electroencephalograms

Suguru Kanoga, Hideki Asoh, Atsunori Kanemura, 2019, Neurocomputing.

Semi-supervised style transfer mapping-based framework for sEMG-based pattern recognition with 1- or 2-DoF forearm motions

Suguru Kanoga, Hideki Asoh, Takayuki Hoshino, 2021, Biomed. Signal Process. Control..